Transformation Requires Focus
A Device Management Partner is Essential
— Joel Spittal, industry general manager, life sciences
Transformation Requires Focus
A Device Management Partner is Essential
— Joel Spittal, industry general manager, life sciences
Restrictions on retailing are starting to ease as government officials and public health experts gain more insight into the risks of the COVID-19 pandemic. As retailers prepare for customers to return, they need to start thinking carefully about how to respond most effectively.
Here are six things retailers can do to hit the ground running and maintain their competitive footing:
Retailers will emerge from lockdowns with constrained cash flow. Customers may still be leery of leaving home or spending freely. These realities might seem to argue for a take-it-slow, wait-and-see approach.
But what if your competitors retool during the economic downturn and come back stronger when conditions improve? The only thing worse than months of economic misery would be to discover the competition has been eating into your market share.
Development strategies like Agile and DevOps give companies wide latitude to implement new technologies with speed and effectiveness, which can bolster competitiveness.
Do all you can to reassure customers, employees and vendors that their safety and welfare comes first. You can do this with solutions such as:
As long as the pandemic lasts, consumers will fell anxiety about human contact. With the right technologies, you can help ease their concerns and lock in their loyalty.
As you implement trust-building solutions, always think about reducing the number of things people must do to complete their orders.
If you’re using curbside pickup, for instance, make sure it’s extremely easy for consumers to find out where they need to be when they arrive in your parking lot. Location-based technologies may be able to optimize this process. If people are using a cashless transaction app, make sure to minimize the number steps between the buying decision and closing the transaction.
Frictionless commerce is one of the best ways to craft an unforgettable customer journey.
A slowdown in business activity provides an opportunity to optimize your supply chain, from trucks to warehouses to employee staffing. Analytics software and learning algorithms can scan data from throughout your supply chain and find inefficiencies that would otherwise go undiscovered.
Moreover, solutions like robotic process automation (RPA) can eliminate repetitive tasks and make your workers more productive, which can streamline supply chain processes and improve customer service.
For all the hype about artificial intelligence and machine learning, it’s important to remember that the best solutions use automation to help people work smarter.
Shoot for mixed-cognitive outcomes that use learning algorithms to mimic distinct human behaviors while freeing people to do what machines cannot: connect with customers on an intuitive, purely human level. For instance, learning algorithms can ensure that people find the best examples of the products they’re hunting for, while marketing and merchandising professionals can use their imagination to craft alluring messaging and irresistible offers.
Mobile commerce apps, optimized supply chains and trust-building retail solutions generate massive volumes of data that retailers can leverage to customize their shopping experience. Two advanced technologies can help:
The Experience You Need to Reopen Retail
At DMI, we have the combination of people, skills and strategic insight retailers need to rebound from economic uncertainty and get back to the business of making their customers happy. We’ve worked with retailers of all sizes in multiple sectors, and we have a full suite of retail solutions to improve outcomes at every link in your chain, from supplier to customer to service after the sale. Our dedicated Accelerated Solutions experts use Agile and DevOps methodologies to deliver powerful solutions on tight timelines. Finally, our human-centered approach helps you meet the needs of today’s mobile consumers.
–John Blackburn, executive vice president, commercial
You don’t have to wait months or years to add automation to your supply chain. Many repetitive supply chain tasks can be automated in weeks — helping you respond quickly to new events while boosting your workforce’s productivity.
These short-term gains require identifying simple tasks that lots of people do many times a day. In an enterprise-scale company, automating these activities can generate sizable productivity improvements. Moreover, you’re taking busywork out of your workers’ lives and giving them more time to solve problems that are too tough for the machines.
Two excellent technologies for supply chain automation are robotic process automation (RPA) and natural language processing (NLP). With RPA, you’re identifying a basic task like data entry and developing a bot to automate it. With NLP, you’re using artificial intelligence and machine learning (AI/ML) to build voice and text commands into applications your people use every day.
Six Ideas for Putting RPAs and NLP to Work in a Supply Chain
These examples should give you an idea of the kinds of automation you can accomplish in weeks vs. months or years.
Weekly reports. Middle managers who provide weekly updates on sales, production or inventories could use an RPA bot to automatically grab data from a software package and plug it into a report to their division managers. Normally, this would require the author to have a spreadsheet open in one screen and a document editing program in another — constantly cutting and pasting data manually into their reports.
Invoice data input. Staff who handle incoming invoices often enter data manually, creating the potential for human error. An RPA can grab the data on an invoice and instantly plug it into your corporate financial software, giving your invoicing staff more time to deal with challenging orders and customizations that require more personal attention.
Financial requests. During economic reversals, financial companies often get a massive volume of customers asking for delays on loan payments. Since these forbearance requests typically require the same data from every customer, you can build an RPA into an online interface that dramatically reduces the workload for people handling the requests. RPA bots also can automate processes like loan applications.
FAQs. If you have thousands of customers with three or four questions that they’re likely to ask repeatedly over the next several months, you can use NLP to translate their questions and add an RPA bot to automate the delivery of their answers. Simple chatbots can be spun up quickly to perform these kinds of tasks.
Inspection checklists. If you have people inspecting products or processes manually, you can build simple apps that let people use spoken commands to check items off their lists. This can be especially helpful when the workers need their hands free to touch and lift objects.
Vocal and text instructions. People often navigate through byzantine server hierarchies to find and share documents when collaborating with co-workers. They also might expend multiple clicks to find a specific feature within a large software suite. Adding a basic NLP bot to a digital interface can allow them to use voice or text commands to access these features and documents much faster.
Quick Tips for Adding RPA and NLP Bots
A Partner for Rapid Supply Chain Automation Solutions
DMI has the people and the technologies required to deliver supply-chain solutions in tight time frames. We have experts in accelerated software development and system design who use Agile methodologies to create fast prototypes and iterate quickly based on user feedback.
With these tools, you don’t need to build an elaborate distribution center with robotic carts to realize the benefits of automation. You can start with your people — automating repetitive tasks, streamlining efficiency and using intelligent bots to help everybody work smarter. And you can do it soon.
–Niraj Patel, director, artificial intelligence
–Varun Ganapathy director, digital technology office
Getting work done remotely gets more attractive every year, thanks to improvements in mobile device capabilities and expansion of network bandwidth and coverage.
Mobile computing became more urgent when the Covid-19 pandemic of 2020 forced companies worldwide to embrace remote work. Within days, enterprises had tens of thousands of mobile devices to worry about. Fortunately, many could turn to mobile device management (MDM) technologies to supervise massive fleets of smartphones, tablets and laptops. MDM technologies help companies:
All these variables have to be managed cohesively, as slip-ups in any one area can undermine the effectiveness of the entire remote-work enterprise.
How Mobile Device Management Works in Practice
Let’s draw an example from a market sector on everybody’s mind in the midst of the pandemic: clinical trials to develop vaccines and new drug regimens. Pharmaceutical manufacturers partner with contract research organizations (CROs) to conduct most clinical trials. CROs, in turn, are looking to do more virtual clinical trials because potential volunteers feel safer and more comfortable in their homes and would prefer not traveling to a trial site.
While virtual clinical trials are attractive, they pose several challenges:
Inventory management. Somebody has to manage an inventory of mobile devices like phones, tablets and connective devices. They all have to be monitored and have alert systems set up to tell managers if something has gone wrong.
Configuration. Every device’s software must be installed precisely to match the trial’s needs. “Bring your own device” doesn’t work well because each user’s smartphone adds too many variables. Each trial requires only a few specific apps and has to limit functionality to maintain scientific validity of the data collected.
Security. Each device must be protected against unwarranted intrusions while preventing breaches of sensitive personal data. HIPAA compliance is mandatory.
Pairing. A smartphone or tablet may be connected to a blood-monitoring device for a diabetes patient. Other devices might track blood pressure or physical activity. These interactions must be closely supervised.
Cost. Devices must be purchased and data plans set up according to specific clinical parameters. This prevents misuse and ensures that proper trial controls remain in place.
Replacement. Once the trial is finished, device data must be erased to prevent accidental release of volunteers’ personally identifiable information (PII).
MDM technologies identify every device in an enterprise’s fleet and monitor them all in real time. This helps managers slam the door on security breaches and control the cost and scope of mobile device networks.
An Expert Partner for Mobile Device Management
MDM helps private, public, and government agencies orchestrate networks of mobile devices for tasks like inventory control and production line inspections. In the public sector, MDM can help police agencies fight crime and military organizations track their equipment inventories in hazardous settings.
As a top provider of mobile application development and mobility services including mobile device management, DMI has the skills and a track record to deliver end-to-end mobile solutions to any sector of the economy, public or private. We focus on rapid time-to-market to improve ROI and user-focused system design to streamline adoption. Finally, our consulting approach ensures you get a partner committed to finding the best solution for your exact needs, in order to meet your business goals and objectives.
–DJ Oreb, president, managed mobility services
An elastic, cloud-based commerce environment has the potential to improve customer engagement and enhance website performance.
But it’s not a sure thing. If you don’t follow specific steps in your system’s design and implementation, you may be surprised to learn that your new technology is actually degrading performance.
This can happen because a cloud-based commerce operation has so many interconnected parts moving data across networks. For example, most cloud commerce operations rely on web services and APIs to fine-tune the customer experience. Alas, many of these solutions are somewhat abstract and often beyond your direct control. This obliges you to develop your commerce architecture carefully up-front to optimize performance and prevent hang-ups.
Possible Issues Affecting Performance
Here are two common scenarios that may crop up in modern cloud commerce environments:
A single microservice somewhere in your purchase process could be the culprit. Or perhaps an API has a subtle flaw in its implementation or the processing time of the services is not efficient on the front-end.
These kinds of problems are not inevitable — especially if you plan ahead and follow the steps required to ensure top performance. Of course, you can’t anticipate every challenge in a complex commerce environment; that’s why you need tools to identify factors that are slowing system performance.
Monitoring Cloud Commerce Performance
No matter how well you plan, from time to time a glitch will sneak up on you and start degrading your shopping experience. System monitoring tools can sound the alarm and help you diagnose problems and then fix them quickly and effectively.
Platforms like Microsoft Azure and Google Cloud provide tools to monitor clusters and support applications. Open-source technologies like Grafana and Prometheus also deliver strong monitoring options. These and many other monitoring tools are essential.
If your site is running slow and your customers are noticing, you have to respond quickly. Monitoring is a huge help, though the tools might not be as “out-of-the-box” as you might hope. You have to invest some time in figuring out how to make them work best with your environment.
Also, remember that monitoring is crucial throughout the development, implementation and iteration phases of cloud commerce.
Getting Help with Performance and Monitoring
Embracing cloud commerce successfully means creating systems and procedures to diagnose issues and cure them before customers notice. The trouble is, there’s always something waiting to reveal a flaw in your best-laid plans.
That’s why it’s so crucial to work with a seasoned cloud commerce development partner like DMI. Our system architects and technical leads have deep experience and broad training in multiple markets and commerce verticals. This track record gives us the insight required to develop robust cloud strategies that protect performance and prevent slip-ups.
We’ve seen enough to anticipate the most common issues and adapt effectively to the outliers. That’s what you need to draw maximum value from your cloud commerce ecosystem.
—Andrew Powers, senior vice president, solutions delivery, digital commerce
A headless commerce system is a marvel of flexibility. You start by building an ideal frontend platform —the “head” that integrates with headless commerce and/or CMS platforms . That empowers you to craft unique customer experiences and intuitive user interfaces that strengthen your brand and business.
Best of all, you can do it fast. Introducing new features, implementing new user interfaces, adding new touch points and releasing software can happen in two or three weeks — a quantum-leap over legacy commerce systems that lock the frontend and backend together, slowing development to a snail’s pace.
But you shouldn’t underestimate the intricacies of making all this happen. You need a robust methodology and strong buy-in from everybody involved — UI and system designers, coders and team leaders, operations and support teams, marketers and analytics experts. Here’s a quick look at pulling them all together.
Agile and DevOps: Essential Methodologies for Headless Commerce
The old waterfall methodology where you create a list of requirements and build out a system over many months is so slow and rigid that it defeats the purpose of adopting headless commerce. That’s why headless developers typically prefer Agile and DevOps methodologies.
Securing Buy-in For Your Headless Transition
Getting everything working in unison with headless commerce requires buy-in from everybody. Although Agile and DevOps optimize speed and flexibility, these methodologies still require time-intensive steps like drawing up requirements and rollout plans, and then distributing them to everybody who needs them. Thus, all of the teams — business, marketing, development and operations — responsible for designing, building and implementing your headless system must be on board and moving together.
Buy-in also means convincing executives, middle managers and rank-and-file employees of the importance of the transition. The complexity of your environment and the age of your current systems will help determine how much training and change management you’ll need.
Your Partner for Fast, Nimble Headless Commerce
There’s no doubt that the future of commerce is headless. To thrive in a rapidly evolving marketplace, you need nimble frontend software that communicates with backend systems without the shackles of legacy monolithic commerce packages.
DMI’s experts have been enabling digital commerce for decades, which gives us the breadth of experience and knowhow to ensure our clients get the headless solution that best suits their business needs. Our system architects, Agile developers, UI designers and data experts have mastered the tools and methodologies required to thrive in the headless world.
These are the skills you need to stay ahead of the competition.
—Atul Bhammar, senior vice president, solutions architect, digital commerce
Tell us about JTV.
JTV (Jewelry Television) is the premier online jewelry shopping destination specializing in extraordinary jewelry and gemstones at extraordinary prices. JTV is an omnichannel retailer with live broadcasts 24 hours a day to over 84-million homes. We serve our customers through robust online and mobile platforms, as well as streaming devices such as Apple TV and Roku, and on social media. Since JTV.com launched 20 years ago, it has become one of the largest non-bridal jewelry e-Commerce websites in the country. Our mission is to open the world of jewelry and gemstones to everyone.
How did JTV find DMI?
DMI came highly-recommended through a contact of mine at Oracle nearly three years ago. We were in search of a trusted partner to support our re-platforming initiative as we transitioned from our flagship website, www.JTV.com, to new technology. Specifically, we needed to enhance our e-Commerce infrastructure and move from a hosted platform to a platform we hosted ourselves.
How complex was JTV’s re-platforming initiative?
It was a large-scale, high-stakes project. In short, our website needed to do more and operate more quickly. We needed more control and flexibility over our digital properties, features and functionalities including authentication management. We needed to seamlessly integrate our live television information and data with our digital commerce customer interactions. We had to remove all friction points for our customers so more web transactions could be facilitated.
In leading digital transformation for JTV, describe your leadership style and what’s the secret to your success?
At the end of the day, it’s the team and culture you build that leads to success. It’s a group of talented computer scientists and engineers wholly focused on delivering quality, useful solutions to make our business successful. So, the secret, I guess you could say, is buried inside of a lot of decisions made over time and if those decisions take your culture into consideration and put your people first, then that leads to something special. I appreciate a culture that combines academia with corporate success, one that allows people to take risks and learn. While I’m a computer scientist, my main job is to create an environment where my team can be successful and thrive. I love to work with people who are unique. I love to work with people who LOVE computer science and engineering, who are passionate and do things the right way to build technology that not only achieves success for JTV, but technology that is elegant and optimized, paying attention to details so we don’t, for example, throw hardware at a problem to cover up a software issue. On my leadership style, well, I like to say that anyone can make you a manager, but no one can make you a leader. That’s earned. My approach is let’s have a great time doing what we love and support each other both personally and professionally.
What’s it like working with DMI?
DMI is a fantastic partner. These guys are brilliant. They’re central to our success in transitioning off our website to the new platform and new systems. I think at the heart of our strong working relationship is that both companies really have similar values; do the right thing and work with transparency. We are definitely all one big team.
What does the future hold for JTV?
We’re really moving toward a headless platform. That will put us at the forefront of the entire jewelry industry and it’s exciting. When we envision what the future looks like for JTV, we will have the leading platform for selling jewelry and gemstones in the entire world.
Business teams face huge pressure to build engaging mobile apps that will improve their customer experience, attract consistent feedback and deliver higher app-store ratings.
The Apple and Google ecosystems already have millions of apps. Countless more will arrive as mobile technology becomes thoroughly mainstream. How will organizations develop mobile apps that break out from the pack and provide an irresistible customer experience in the 2020s?
A lot depends on the scope of the challenge and the nature of their industries:
Though the specifics will shift from one organization to the next, these five factors will be pivotal to succeeding at mobile application development in this decade:
Business vision. You need a solid vision to address the entire customer journey in your mobile apps. As you know, mobile won’t be optional — it will become central to companies’ approach to engaging customers, collaborating with vendors and expanding market share.
Whether you’re a venture-funded startup hoping to disrupt a market or a corporate titan building a mobile-app lab, you’ll need to stay attuned to the shifting demands of customers and the challenges you’re trying to solve.
Customer experience focus. There will be no easing in the push to develop mobile apps that give users exactly what they want, when they want it. You need to pay extra attention to customer experience and visualize the entire journey before you build mobile apps.
Make sure you have a product owner who truly owns the product backlog and churns high-value features that are delivered in iterative way.
App analytics. Data science, machine learning and natural language processing will transform mobile apps in this decade. As 5G bandwidth becomes widespread, massive volumes of data will pave the way to advanced analytics that improve predictive capability.
Mobile developers will have to fully understand how to pull these capabilities into a holistic user experience that can be highly customized without intruding on the customer’s sense of privacy.
You need to have a clear strategy to act based on app analytics.
Culture of agility. Companies that develop mobile apps will have to move quickly to adapt to new technologies and competitive threats. Moreover, future-focused developers will lean even more heavily on Agile and DevOps principles to speed new products into the marketplace and manage their software update cycle.
Though Agile processes are more often associated with startups and digital natives, companies of all sizes and scopes will have to find nimble, fast and flexible approaches to mobile app development to drive business value.
Delivery consistency. Expanding enterprise app portfolios will require standardization of development, collaboration, testing and other crucial functions to deliver consistent apps. This is especially true for large companies with multiple product lines that each have their own apps.
Companies need to look at cross-platform app development frameworks like React Native or Xamarin that eliminate duplication of effort in developing for Android and iOS. But even cross-platform apps will require standard practices and methodologies if companies hope to develop sophisticated app factories serving the entire enterprise.
Few companies have the resources to fold these five factors into a cohesive approach to mobile application development. DMI closes this gap. We are one of the early adopters of mobile app technology and have been building mobile apps for more than 10 years. We’ve developed more than 3,000 mobile apps for global enterprise companies, government and federal agencies and nonprofit organizations. We also have managed mobile services that help large companies tackle the complexities of mobile workforces. Analysts consistently rate DMI as a leader in the mobile apps space, and our apps have won many industry awards.
Our experts in customer experience, system design, mobile app development, analytics and microservice architecture cover the full mobile stack. Moreover, our consulting approach ensures everything we build aligns with our clients’ business strategy. These are the kinds of skills that make DMI globally one of the top mobile development providers.
— Rajesh Pawar, VP, Mobile Apps Practice Head
It seems easy at first. People convene Zoom meetings from their living rooms and share documents on Microsoft Teams. But companies soon find out that keeping remote workers happy and productive is more like navigating a maze. Then, a solution starts looking like a remote possibility.
It doesn’t have to be that way. You can spin up a host of powerful technologies supporting your remote workers — typically in 30 days or less — that can streamline workflows, automate repetitive tasks and generally make life easier for people accustomed to working together in the same office.
At DMI, we get client calls daily asking for guidance on remote work technologies. Companies often have a confusing mishmash of collaboration tools, data center architectures and application portfolios. Many depend on connectivity tools like VPN that aren’t designed for scale. Others impose an abundance of tasks on workers that could be readily automated.
And, of course, everybody wants fixes as soon as possible. Here’s how we help clients find solutions in tight time frames.
Optimize Collaboration Tools
If your people are using Microsoft Teams for family meetings and club get-togethers, that’s telling you something: Maybe they don’t need Zoom, WebEx, Slack or any of a dozen other productivity tools that Teams can handle. Or, maybe you’re not a Microsoft shop, so you need to find the optimum blend of tools for chatting, videoconferencing, file sharing and so on.
The more departments and silos you have, the more imperative it becomes to bring order and sanity to your collaboration-tool portfolio. Whatever your situation, you need to assess which applications to keep and which ones to let go. And then you need to create standard workflows so that everybody does essentially the same things the same way to get their work done.
Leverage Cloud Platforms
If you’re hosting most applications in on-premises data centers, then you’re at a natural disadvantage when time is of the essence. With cloud software platforms, your service provider maintains all the infrastructure and keeps the software updated. Cloud architecture makes it easy and fast to spin up all sorts of software in short time frames because there’s very little to install.
Perhaps the greatest challenge with cloud platforms is integration — finding the right match for your business from the vast variety of cloud apps and folding it into your current technology stack. You also have to make sure the cloud platform’s cost structure matches your budget. Cloud services charge for the processing and bandwidth you consume, and that can add up quickly for big companies with large remote staffs.
Build Low/No-Code Apps
Every company needs software unique to their workforce and business environment. It used to take months or even years to build these kinds of applications, but the rise of low/no-code applications has squeezed these time frames down to weeks.
Low/no-code technologies let companies give their remote workers access to mobile apps for specific tasks on their smartphone or tablet rather than a laptop or home PC. This adds even more mobility to a remote workforce. Moreover, these apps can automate manual tasks like data entry and validation, freeing workers for more important assignments.
In theory, anybody with a computer can build a low/no-code app. Schoolteachers have built them for their classes, for instance. But companies need seasoned developers to weave low/no-code components into intuitive, easy-to-use applications that their workers will enjoy using.
A Partner for Accelerating Remote Work
DMI’s Accelerated Solutions practice specializes in delivering high-performance technologies in short time frames. These experts include two Microsoft MVPs who have advanced training and experience across the full spectrum of Microsoft technologies. They’ve succeeded in enough projects in multiple industries to know how to avoid the trial-and-error that bogs things down.
We also use time-tested Agile methodologies that iterate quickly and deliver speedy time to value. Moreover, our proprietary Agile Performance Index (APIX) provides a unique ability to assess the progress and success of Agile development. Finally, our experts in system architecture, user experience design and business strategy provide the end-to-end expertise that tight timelines require.
The best work-from-home solution should help remote employees enjoy their work without having to jump through a bunch of digital hoops imposed by the IT department. Our user-centered development philosophy can help your company do that.
— Matt Jimison, vice president, accelerated solutions
— Corey Roth, director, accelerated solutions
— Brandon McGhan, director, accelerated solutions
A headless commerce architecture provides expansive options to fine-tune your customer experience. But flexibility has a cost: It takes a lot of time and effort to select a software stack that aligns with your technical skills, customer expectations and business objectives.
The right headless software stack can give you nimble, powerful tools to adapt to an ever-changing commercial landscape. Let’s break this challenge down into two parts — selecting a software stack and making sure you have people with the right skills to implement and manage it:
Finding the Optimum Software Stack for the ‘Head’ in Headless Commerce
Headless commerce decouples the frontend of your e-commerce system from the backend, where most of the business logic resides. Going headless also means choosing a frontend software stack to build out a new presentation tier.
Making the right choice starts out with clearly defining your requirements and evaluation criteria for the presentation tier — focusing on customer experience (functional and non-functional), business objectives and business user empowerment. Enabling business users is key to keeping long-term operational costs low and ensuring high business value.
When shortlisting the software stacks, it is advisable to consider the experience and skills of your IT team. However, the final decision typically comes down to finding balance between the needs of the business and the software stack that satisfies the most requirements within the context of the size, scope and skills of your whole team.
Ensuring Skills Alignment for a Headless Transition
If you have a small IT operation, you might work with an integration partner who will supply the technical skills required for headless commerce. A midsize IT operation might merge its in-house skills with those of a technology partner. A large enterprise, by contrast, might have all the requisite skills in-house.
Conventional monolithic commerce systems required an abundance of backend talent — people who created all the customizations on the computing end to suit a host of business needs. In the headless world, most of the differentiating customizations happen in the frontend, so your skill requirements generally shift from back to front. To make that transition, you may have to retrain your people, hire new staff or work with an outsourcer.
And don’t forget that most modern frontend software stacks require a wealth of experience with cloud technologies and networking protocols. Each cloud provider has specific methodologies that require training and a track record.
A Skilled Partner for Choosing Your Software Stack
Headless commerce requires a software stack that meshes with your technical acumen and business objectives. It’s a tall order for any company.
At DMI, we have people with decades of experience in both online retail and advanced IT system design to augment and contribute to your decision-making process. We’ve helped companies of all sizes across multiple market verticals. That means we know how to anticipate the inevitable challenges that bedevil any large-scale technology project. In addition, we are very comfortable with Agile and DevOps methodologies to assist you through the transition process.
This experience gives us the tools to streamline your journey to headless commerce.
-Atul Bhammar, senior vice president, solutions architect, digital commerce
Moving to cloud-based commerce technologies requires learning new skills and mastering more nimble development methodologies.
In the cloud, you may work with the global providers like Amazon Web Services or Microsoft Azure. You might end up embracing new technologies like Node.js and Kubernetes. Cloud-based apps and platforms will give you the flexibility to adjust your customer experience rapidly, if your staff has proper training and experience. Development cycles that used to take months can happen in weeks, if you use the right methodologies.
Moreover, you have to think in terms of two development challenges: migrating to new cloud technologies and getting the most benefit from the cloud in the years to come.
These are the primary knowledge and methodology factors to keep in mind when you’re moving to a cloud-based commerce platform:
Managing Skillsets, Knowledge and Experience
Running an on-premises commerce suite is much different from a cloud-hosted commerce system. For instance, cloud commerce requires more knowledge on the intricacies of networking. And just because you know how to manage VMware doesn’t mean you know how to manage Google Cloud. Development that happened in hypervisors in your legacy commerce system will run in clusters and pods in the cloud. You can’t assume that this kind of knowledge translates easily.
The same concept applies to your developers and tactical leads. No matter how many years they’ve been managing applications in hosted environments, they must be trained to do the same work in the cloud.
Thus, when you’re planning to migrate commerce operations to the cloud, you have to take the learning curve into account. Progress will be slow in the beginning as people learn the ropes. After the migration, you have to adapt your development methodologies to the new cloud environment.
Mastering Cloud Development Methodologies
Conventional waterfall development is usually too rigid and time-consuming. By contrast, Agile methodologies help you iterate quickly in sprints of two weeks. When you’re running a cloud commerce migration, Agile sprints and teams help you quickly organize and implement your new environment.
Once you’ve moved your commerce to the cloud, you need strong processes and policies governing software release cycles. Here, pairing Agile practices with DevOps principles packs a powerful punch.
Even if you already use Agile and DevOps, you need rigorous planning and thorough training up-front to apply them successfully in the cloud. Don’t assume it’s easy to adapt Agile and DevOps in an unfamiliar ecosystem.
Getting Help with Skills and Methodologies
At DMI, we’ve found that it’s most helpful to figure out as much as you can up-front, before you migrate to a cloud commerce environment. That means acquiring the required skills and processes before you dive too deep into the process.
Our teams have decades of digital commerce and development experience. We’ve done enough cloud commerce migrations in enough sectors to know the common pitfalls and best practices. That’s the kind of technical acumen you need to thrive in the age of cloud commerce.
—Andrew Powers, senior vice president, solutions delivery, digital commerce
DMI is excited to be a Mirakl partner. How did Mirakl get its start?
Mirakl powers tomorrow’s e-commerce by providing the technology, expertise and partner ecosystem needed to launch an eCommerce marketplace. Retailers, brands, manufacturers and distributors use the Mirakl Marketplace Platform to offer their customers and partners anything, anytime, anywhere. With their marketplaces, they’re able to increase the number of products available for buyers, grow the lifetime value of customers, and anticipate buyer needs and preferences. We also have a team of more than 60 marketplace experts who help our clients adopt best practices and provide long-term strategic guidance. Overall we have more than 200 retail, manufacturing, distribution and procurement customers operating marketplaces in 40 countries.
What is the StopCOVID19.fr marketplace and how is it helping to curtail the PPE shortage in French hospitals?
StopCOVID19.fr is a project we worked on with the Ministry for the Economy and Finance in France to make vital supplies like hand sanitizer, masks, and protective clothing easier to source. The traditional supply chain for these critical products wasn’t able to keep up with demand. With Adobe Magento, we quickly launched a Mirakl-powered Marketplace in just 48 hours that matches French healthcare institutions with these providers of critical supplies. It uses the platform model to organize the distribution chain connecting producers of materials with packaging manufacturers and, ultimately, the hospitals, clinics, and other organizations that need these products the most. As of late April, StopCOVID19.fr had facilitated orders of more than 30 million critical supplies for more than 6,000 clients in France.
How do you see Mirakl helping businesses get a fast start coming out of the COVID-19 crisis?
We believe the companies that will come out stronger will be the ones who don’t delay in investing in future business models. Mirakl can help businesses quickly adopt a platform business model strategy. This means setting up an online marketplace to rely more on ecosystem partners to do business and not depend solely on their own sourcing, manufacturing and supply chains to meet buyers’ needs. Investing in an innovative, asset-light, agile platform strategy will be key to scaling faster and thriving in the post-COVID future.
How do you see the continuing adoption of platform-based solutions impacting medium and large businesses around the world?
There’s a huge opportunity for incumbent businesses to create platform strategies of their own. Gartner has projected that by 2023, 15 percent of medium-to high-GMV digital commerce organizations will have deployed their own marketplaces. When incumbents move boldly with these digital strategies, they actually command four times more market share than digital natives encroaching on their territory. The organizations that recognize the power of the platform model will win.
Mirakl’s client list is impressive. What’s the key to engendering the trust of so many large brands?
Mirakl has the expertise, an advanced technical platform, and a vast partner ecosystem that when combined, are truly the recipe for our success. We have dozens of marketplace experts who partner closely with our customers and partners to help them achieve their true potential, and in many cases they actually operated marketplace projects of their own before joining us. But we wouldn’t be able to build these close partnerships if our solution didn’t deliver results – and it does. It increases customer lifetime value, improves the customer experience, and can actually even do things like increase in-store sales. We asked Forrester Research to determine the ROI of a Mirakl-powered Marketplace and they found that it can deliver a 162 percent return on investment within three years. We’re the only solution that can offer that return at the scale and quality our customers expect.
Describe how a partnership with DMI makes sense for Mirakl?
DMI fits nicely into our partner ecosystem because the company has deep eCommerce experience with Oracle Commerce and SAP Commerce. This experience allows us to work together closely to expand our clients’ commerce platform incorporating a Mirakl strategy. We’ve successfully completed multiple projects with DMI. DMI has the unique ability to quickly implement Mirakl so customers can start to achieve revenue through the solution.
The value of remote work became clear as a health emergency spanned the globe. And it’s a fair bet that work-from-home scenarios will remain popular long after the pandemic of 2020.
A smart response to an expanding remote workforce is to remain attuned to the human challenges: Preserving social interactions, shoring up productivity and adapting quickly to changing needs. Getting all these things right leverages the flexibility of remote work while nurturing the human relationships that form the core of working for a living.
Therefore, IT departments supporting more remote workers should be thinking about nurturing people’s ability to be social, productive and adaptive.
In years past, supporting remote workers required a patchwork of applications and technologies that were difficult to implement, support and manage. Lately, however, innovations in four core technologies are making life easier for remote workers and IT teams alike.
Large companies may have thousands of remote employees using phones, tablets, PCs and purpose-built devices — and apps spanning multiple operating systems installed on all of them. Managed mobile services have emerged to help companies ride herd on their massive fleets of mobile devices and applications.
Managed-mobility providers offer depot services and specialize in overseeing devices, system infrastructure and financial issues. These companies also provide service and support desks to ensure users get productive responses to issues that crop up.
The emerging field of mobile experience management (MEM) is helping organizations optimize the user experiences of their remote teams. Because every user generally customizes their work experience, they create a massive need to standardize and organize things behind the scenes.
MEM works by monitoring the data flowing to and from devices and software, then applying algorithms and automation that make it much easier to diagnose problems and ease the strain on mobile device support teams. Artificial intelligence and machine language can help these tools self-diagnose and self-heal problems in remote devices, improving worker productivity.
Industry mainstays like Microsoft Office 365 and newcomers like Zoom and Slack play central roles in the productivity of remote workers. Moreover, technologies like virtual desktop infrastructure (VDI) and low-code apps can help companies better support remote workers.
The challenge is getting all these tools to work in unison across the remote workforce’s disparate devices and applications. Security gaps must be patched and upgrades must be implemented. Many companies offer dedicated productivity services to simplify, manage and support these tools and, ideally, integrate them into a cohesive worker experience.
If you rapidly turn 1,000 office workers into remote workers, the demands on your IT support team will surge. Applications crash, devices get lost or damaged, and remote teams feel unique work-at-home frustrations.
Conversational AI in the form of chatbot systems can quickly ease the workload on your support team, answering easy questions and handing off tougher ones to real people. The data gleaned from these interactions helps the bots get smarter over time, thanks to pattern-matching learning algorithms. Over time, you can develop intelligent virtual agents (IVAs) that automate more sophisticated user-support challenges.
Starting from a Position of Caring
Neither distance nor separation should thwart our natural human urge to socialize, create things and adapt to a changing world. At DMI, our commitment to human-centered system design and computing reflects this principle. Before we implement tools or recommend technologies, we take the time required to understand the full scope of the human problems our clients need solved.
Yes, it takes skill, experience and strategic insight to preserve the human component of remote work. But it also takes something more: simply caring about the people using the technologies we deploy. Nothing can replace that human connection.
— Michael Deittrick, senior vice president digital strategy, chief digital officer
This is the third in a three-part blog series about the use of Magento.
Magento may have started out as a small-scale e-commerce solution. But the latest versions of the platform are empowering innovative customer experiences for the biggest — and most ambitious — digital commerce operations.
Released in November 2018, Magento 2.3 ushered in robust e-commerce capabilities that have been strengthened with each incremental upgrade. These tools help retailers apply technologies that suit their specific needs with laser precision. Moreover, Magento 2.3.x makes it easier to scale up or down with fluctuations in demand while delivering a more consistent buying experience. That makes it easier to thrive in an age of disruption.
One of the biggest sticking points with early e-commerce platforms was lack of flexibility. A platform might have a muscular backend and a weak frontend, or clumsy integration with applications for resource and customer management. With the tools in Magento 2.3.x, you can decouple your frontend from your backend and integrate with other critical software applications without major headaches.
These four capabilities make it possible:
Magento 2.3.x. Requires Deep e-Commerce Experience
Getting all these features to work to your advantage requires a partner who can serve the needs of retailers and customers while applying the best Magento features and avoiding the pitfalls that bedevil complex e-commerce operations. That’s the skill DMI delivers to our clients. We understand retail and we have the skills you need to combine Adobe tools with APIs, PWAs and headless commerce.
— Jon Wovchko, vice president of operations & strategy consultant, digital commerce
What is Art Basel and tell us about your role within the organization.
Art Basel is the leading global platform connecting collectors with galleries and their artists. Art Basel’s fairs in Basel, Hong Kong, and Miami Beach are a driving force in supporting galleries from across the globe. I am Art Basel’s Director Digital.
Tell us about Art Basel’s Online Viewing Rooms.
In March, Art Basel offered its first Online Viewing Rooms. For its first iteration, more than 230 galleries displayed over 2,000 works of art with an estimated value of about $270 million, including 70 items over $1 million.
We noticed the large amount of press the Online Viewing Rooms garnered. What drove the media coverage?
Indeed, the initiative was widely discussed in the media and generated a lot of attention. There was particular interest, as it was a very timely topic. Lockdown as a result of the pandemic was underway and everyone was keen to turn to online to stay connected with the arts community. It was the first time Art Basel had implemented Online Viewing Rooms, so there was also a lot of interest to see how we approached the topic. It was also the first time for many galleries and collectors to explore the concept of Online Viewing Rooms.
What made the Online Viewing Rooms innovative?
I think we’re at an inflection point and people are open to trying out new channels. At the same time, we strongly believe that digital platforms cannot replace the experience of seeing art in person or visiting the fair itself. However, digital provides us with an exciting additional platform for our galleries.
Tell us about Art Basel’s partnership with DMI.
We’ve worked with DMI for five years now on both our website and app. I asked the team at DMI if we could implement Online Viewing Rooms and I was happy to hear the DMI team had the expertise to get the platform up-and-running successfully. I greatly appreciated their “can-do” attitude and technical expertise.
What plans do you have going forward for Art Basel’s digital platform?
We’re continuing to invest in and enhance our new digital platform, the Online Viewing Rooms, as a way to support galleries during these challenging times.
This is the third in a series of blogs about improving your call center.
Upgrading your call center in a crisis has a middle phase that’s critical to achieving your long-range goal of implementing an intelligent virtual assistant (IVA) system.
Call centers IVA use advanced learning algorithms that train their attention on the speech patterns of callers. Over time, they analyze enough data to learn how to answer more caller questions correctly and make fewer mistakes.
Learning automation can be a major boon to call center efficiency — if you follow the ideal path to IVA implementation. It’s a delicate choice because it’s so tempting to throw everything at the challenge. That runs the risk of trying too many new things and faring poorly at all of them.
In a previous blog on automating healthcare call centers, we recommended getting off to an easy start that provides rapid relief to your call agents or patient-support staff. Now we move to the middle phase that forms the bridge to your ultimate goal — a fully functional IVA that eases the burden on call center reps while also pleasing your patients.
The Middle Phase: Adding Channels and Verification
In the first phase of this model, we suggested choosing a single channel like a webchat and targeting a few easy questions whose answers are easy to automate.
That simple bot generates training data about your patients’ most pressing concerns, creating a baseline for the middle phase — automating new channels and verifying identities. There’s plenty to think about here. You might consider boosting the capabilities of the text-messaging channel and queries arriving via email and social media posts. Much of these channel-choice decisions depend on data insights from your initial automation phase.
As you might expect, the middle phase can tackle more difficult questions. For example, one of the most important goals here is identifying exactly who is contacting your patient-support reps.
Consider the patient asking about paying a bill — a financial transaction that’s an excellent candidate for automation. Your challenge is building a transaction bot that confirms their identity correctly every time while protecting their sensitive medical and financial data in accordance with regulatory requirements.
Verification is a big job. Getting it right early will pay dividends throughout your call center upgrade.
The middle phase also is the right time to start training your call center staff on the subtleties of automation. They must understand that bots are there to augment their capabilities, not put them out of a job.
The stickiest IVA challenge is yet to come: Using learning algorithms for sentient analysis and to examine the intent of complex questions in a voice call and supply the right answer without human intervention. You also want to use caller behavior data to predict and project their future needs.
That’s your IVA system’s ultimate goal, which we’ll cover in the final phase of this blog series.
A Partner for Every Stop on Your IVA Journey
It takes a wealth of knowledge, vision and experience to automate a call center with IVAs that combine the latest innovations in data science, analytics and machine learning. Our experts include data scientists, user experience designers, system architects and project managers schooled in the Agile and DevOps principles that ensure speedy solutions to intricate technology challenges.
As a system integrator with clients in health care, finance, government, retail and automotive sectors, DMI has the skills and the track record to help clients succeed with IVAs and many more next-generation digital technologies.
–Niraj Patel, director, artificial intelligence
Shifting from a legacy commerce platform to cloud-based technologies requires a deft balance of skills, technologies and cost considerations. A well-thought-out strategy is fundamental to achieving this balance.
The ecosystem of cloud technologies is so immense that there are almost infinite ways to make the cloud a part of your commerce system. To narrow things down, we’ll focus on two kinds of common enterprise commerce challenges: working with cloud-based components you own or manage, or interacting with third-party cloud components that other companies own.
Here’s a quick look at three critical components of a cloud commerce strategy.
Skills. Moving to the cloud means you have to dovetail the work of system architects, team leaders, database administrators, coders, support personnel and more. To gain the flexibility of cloud commerce, you need methodologies like Agile and tools such as Terraform and Jenkins X to iterate quickly and manage your software release cycle. In addition, people must be trained on the new cloud technology prior to working with it so they are able to accomplish their jobs in the new environment.
All of these skills-based challenges must work together when you shift to cloud-based commerce. A sound strategy and well-developed roadmap give you a foundation to deal with skills challenges.
Platform choice and rollout strategy. Choosing a cloud platform, SaaS tools and APIs to connect cloud services requires a sophisticated architecture that accounts for how all these tools interact.
For starters, you have to choose a migration strategy. Will you do everything at once or move things piece-by-piece to the cloud? If you do an incremental rollout, what’s the impact on your system architecture? You might be able to port an existing system to a cloud-hosted platform with only minor changes to the technology.
Every decision’s costs and benefits depend on merging existing systems and skills with the future state you envision. A strategy and roadmap that account for these factors will streamline operations and reduce financial risks.
TCO, hard/soft savings and ROI. In the cloud, your total cost of ownership (TCO) changes dramatically because you rent hardware on a pay-as-you-go basis and stop paying to build and manage datacenters. Running microservices, for instance, might generate costs measured in fractions of a penny. Holiday traffic spikes, by contrast, can send bandwidth costs skyward.
Moving commerce to the cloud yields a mix of straightforward hard-cost savings (owning vs. renting) and less-obvious soft-cost savings (speed and flexibility). All of these factors influence your ability to generate an attractive return on investment that will satisfy investors and executive leadership. Thus, financial considerations have to be baked into your cloud commerce strategy.
Thinking Beyond Strategy with DMI
At DMI, we strongly recommend building a sophisticated cloud commerce strategy before starting up a project to migrate your commerce applications to the cloud. But strategy is only the beginning. Because our developers have decades of experience in system design and digital commerce best practices, we can consult with clients and help them succeed in every phase of the transition, from strategy to roadmap development to migration to long-term development.
—Andrew Powers, senior vice president, solutions delivery, digital commerce
Accelerated time-to-market is one of the best things about headless commerce.
But the promise of speed may create a misconception about the transition to headless commerce. First off, getting started can take a lot longer than you might suspect. Moreover, the complexity of headless commerce requires a comprehensive strategy to keep all the moving parts rolling in the same direction.
Companies have excellent reasons to modernize their commerce platforms. After all, legacy platforms usually have a rigid structure that requires changes on the frontend to coordinate with planned backend releases. This structure binds the hands of people trying to react quickly to changes in their marketplace.
Headless commerce decouples the frontend from the backend, enabling fast development timelines that are more difficult with a conventional monolithic commerce platform. But enjoying all this speed comes at a cost: You have to invest plenty of time at the beginning of the headless transition to formulate a strategy that will ultimately save time in the future.
Getting Your Headless Commerce Strategy Right
There’s a lot of due diligence, planning and execution to navigate:
These and many more variables must mesh with your current IT configuration, governance and marketplace expectations. And everything needs to be flexible enough to support rapid changes in the years to come. Limitations in your platform of choice that seem minor today could prove major in 18 months.
To navigate these variables, it helps to start with a gap analysis that describes your current environment and the future state you hope to achieve. The skills and technologies you’ve already mastered will play a significant role in the transition. You’ll want to build on your strengths rather than create everything from scratch.
Thorough due diligence lets you build a roadmap that identifies new technologies you need to implement and provide a timeline for getting it all done.
Giving Yourself Enough Time to Succeed
And now for the bad news: There will be meetings — lots of them.
Embracing a new commerce platform requires an immense number of decisions, most of which are interrelated. These choices require consensus based on feedback from your staff and advice from your technology partners. And you have to weigh the impact on customers, suppliers and co-workers.
Gaining frontend flexibility opens up a universe of alternatives. You can’t weigh them all, but you will want to consider the most promising ones. Your strategy builds a foundation for the future of your commerce operations. That’s not something to rush through. The more you get right in the early meetings, the fewer meetings you’ll need to fix glitches down the road.
DMI: A Strategic Partner for Headless Commerce
At DMI, we’ve implemented headless commerce architectures for companies across a wide spectrum of capabilities and technology maturities. Some clients have no in-house IT, while others have the resources to develop in-house platforms. Our edge in digital commerce is our deep experience with both legacy and modern commerce systems at every level of the software stack.
We help clients formulate the optimum headless commerce strategy based on their current realities and their business goals. And we help them formulate a timeline for getting it done right.
— Atul Bhammar, senior vice president, solutions architect, digital commerce
Cloud-native development can drive a wealth of business value — if you utilize the correct strategy.
Lots of developers love to build apps on cloud platforms from Google, Amazon, Microsoft and other providers because the cloud is a fast, easy to use and cost-efficient alternative to conventional development environments. Cloud providers offer popular services in the Platform as a Service (PaaS) and Function as a Service (FaaS) categories, including AWS Lambdas and Azure Functions. Such technologies take care of most, if not all infrastructure concerns so your developers can pay more attention to building responsive, adaptive solutions that drive business results.
The great thing about the cloud is that you pay only for the resources (compute, storage, network) you use. The pay-as-you-go model encourages developers to create microservices that spin up for a specific job and then go dormant again, generating a small fee for each request. Microservices are pivotal to the event-driven performance of modern, cloud-developed applications. Each microservice operates independently and must be able to scale up easily in response to shifting user requirements and demands.
Containerization is another popular tool for cloud-native development that’s often reserved for enterprise-level applications. Containers work a bit like an operating system in that they let you implement an application and its dependencies in one place where they can operate together and are portable, allowing businesses to avoid cloud vendor lock-in.
Containers add cost and complexity, so you have to carefully weigh whether you actually need them. Many times, a cloud-native microservices-based architecture that does not utilize containers is cheaper, simpler and can easily perform the heavy lifting, even with apps that serve large audiences and contain both a wide breadth and depth of functionality.
Deciding on the use of containers is just one of the complexities of organizing and orchestrating all the moving parts in a cloud-native application. A robust development strategy is mandatory to navigating all these issues.
These are the pillars of a cloud-native development strategy:
Business need. You don’t go cloud-native because it’s a hot trend. You go there to solve a vexing business challenge. Your strategy must be able to exploit the inherent speed, agility and economy of cloud-native development to address that challenge.
Continuity. Strategy starts with the first meeting and continues through all the iterations of your cloud-based software. It’s too easy to expend all your strategic energy on getting an app up and running and then lose focus after a few release cycles.
User experience. Your cloud-based app is a digital product, not a project. Therefore, you have to think strategically about how users navigate through each of your application’s features and capabilities. Your personas, user interface and customer experience must align with your overall strategy.
Methodology. Cloud-native development typically uses Agile methods and DevOps principles to produce software in time frames as short as two weeks. Agile teams build iterations of the software and DevOps guidelines enable a consistent, effective delivery and release cycle.
Skills. Building applications on a cloud platform requires unique experience and training. Experience in other development environments doesn’t always translate. Your strategy cannot assume you have all the skills you need in-house. It must account for training and recruiting people with talents that align with how to best meet your business goals.
Culture. The advantages of microservices and the cloud allow for nearly infinite scaling and incredibly rapid, frequent updates and improvements to cloud-developed applications. This is a totally new mindset for many organizations, especially those that have not yet embraced Agile and DevOps. You need buy-in from the ground up and the top down in order to successfully instill a culture that will exploit these advantages.
A Strategic Partner for Cloud-Native Development
At DMI, our Agile teams and DevOps expertise help clients implement comprehensive strategies for developing applications natively in the cloud.
We’ve seen it time again: Hours upon hours of meetings produce a strategy that collects dust once development starts. That’s not how we do things. We give clients the guidance they need to align their development goals with their business strategy.
Cloud-native applications should advance your business goals in every phase of development. Our decades of experience and commitment to strategic solutions ensures our clients enjoy that kind of strategic alignment.
— Kyle Klimek, vice president, application development practice
For all the terabytes of consumer data brands collect around the clock, the personalization of shopping experiences can feel like an elusive goal.
Every time your mobile device delivers an ad for a product you already own, you’re seeing the limits of personalization. the brand knows you’re interested — they just don’t realize their timing is off.
Brands that want to eliminate these kinds of personalization foul-ups have to overcome four daunting challenges:
A Partner for Commerce Across the Entire Technology Stack
Personalization in commerce requires a broad spectrum of talents in system integration, data analytics, AI/ML, customer experience, user interfaces and high-level business strategy. DMI is unique in that we can bring all these talents to bear on your personalization challenges. We start from a strategic perspective based on a company’s unique marketplace challenges and skillsets. We also apply Agile and DevOps methodologies to accelerate the time-to-market of our technology solutions.
That’s the blend of skills, experience and insight you need to succeed with commerce personalization.
— Allison Lee, practice leader, digital marketing
— Paula Moniz, practice leader, customer experience
This is the second in a series of blogs about improving your call center.
When a hospital, clinic or medical practice gets flooded with calls from worried patients, it’s only natural to think automation is the answer. If a bot can handle the easiest calls, the reasoning goes, then the humans can spend more time answering questions that befuddle the smartest learning algorithms.
A new breed of tools called Intelligent Virtual Assistants (IVAs) can indeed transform your patient-support experience. The trouble is that for all the advantages of IVAs (which are abundant), they can’t cure today’s crush of patient calls because:
These challenges underscore the value of thinking in terms of a journey to IVA functionality that starts out simple by automating a single communication channel. Once you’ve done that, then you can move to automating multiple channels and then, finally, implementing a robust IVA solution.
Let’s say you’re getting about three-quarters of your patient communications from three channels: voice phone calls, text messages and a web input form. The other one-quarter comes from channels like social media and popular chatting platforms.
You want to pick a channel that gets enough usage to provide valuable data but is still fairly easy to automate. This channel also should carry the lowest risk of unexpected glitches angering large numbers of patients.
Often, a webchat is a useful starting point. An automated script can answer the easiest questions like “what are your office hours?” or “where do I go to schedule an appointment?” Just being able to automate a of couple of common questions takes some of the load off of your human patient-support team.
This gives you help when you and your patients need it most — without an extended wait for a full IVA system.
Moreover, within hours you’ll start getting precious data signaling patients’ intent. Learning algorithms can be trained to identify the patterns in people’s questions. As the algorithms build a massive dataset of right and wrong answers, they teach themselves to anticipate people’s desires and serve them even better.
Training data from people’s questions and other online behaviors makes artificial intelligence and machine learning possible. In the weeks and months to come, you’ll feed more and more training data into newly automated channels that will form the bedrock of a full-functioning IVA system.
A simple chatbot can get you on the road to IVA functionality and leave you better prepared for the next new influx of patient calls.
At DMI, we’ve implemented IVAs in a range of sectors including health care, finance and government. We have a deep, rich pool of talent in business consulting, automation, system architecture, machine learning, data science and customer experience. We also use Agile methodologies to get the optimum solution into our clients’ hands in tight time frames.
These skills make all the difference when your call center is at risk of being overwhelmed.
–Niraj Patel, director, artificial intelligence
This is the second in a three-part blog series about the use of Magento.
Magento Commerce has some of the world’s best tools for creating best-in-class customer experiences that can give enterprises a digital edge over their competitors. But there’s no easy button for getting the best performance out of Magento, which Adobe acquired in 2018 to beef up its Experience Cloud platform.
You need an experienced system integrator to find the most painless and efficient ways to deal with implementation issues and ongoing operational headaches that are bound to crop in when you tap into popular Magento features like these:
Next-generation development tools. Adobe’s acquisition of Magento converges two powerful software suites: Magento Commerce and Adobe Experience Manager. The merger enables developers to couple Adobe’s design tools with relevant content and Magento e-commerce software to craft world-class customer experiences that mine the full potential of APIs, PWAs and headless commerce. Today’s most innovative shopping experiences use PWAs (progressive web applications) on the front end to pull mobile-app functionality into web pages. APIs link the PWA-empowered frontend to whichever backend provides the best performance.
Unbundling the front (the “head”) from the back is the core appeal of headless commerce, which gives retailers unprecedented flexibility. On paper it sounds wonderful. In reality it takes people with years of experience in digital commerce and system design to fine-tune headless commerce and ensure that it delivers the rich shopping experience customers have come to expect.
Application integrations. Magento’s modern API framework connects your e-commerce system to your CRM and ERP platforms, payment gateways and other crucial business systems. Because these platforms have hundreds of moving parts that all need to move in the same direction to serve your company’s goals, the complexities can seem almost endless.
Indeed, for all the challenges of headless commerce, application integrations often are the most difficult component of designing, implementing and managing a Magento digital commerce operation. Getting all these integrations to work well together requires people who have seen pretty much everything and know how to anticipate difficulties specific to your business and respond effectively to new ones that crop up.
Global developer community. Thousands of developers around the world are building plug-ins and enhancements to Magento’s core code. That lets you choose a tool for, say, payment gateways, that integrates most efficiently with your existing systems.
But what if there are five promising payment gateway solutions available? How do you pick the right one and ignore all the wrong ones? The essentially endless customization options from the Magento developer community are awe-inspiring but also paralyzing. Choosing badly can stall your progress and aggravate your customers.
Think about what happens when you miss a left turn in your car. You can take three right turns to get moving in the right direction again, but it’s not the most direct route. Digital commerce system developers often face a similar quandary — choosing between one and three turns when resolving system challenges.
Experience is the best teacher for making the most productive turns. At DMI, we have experts with years of experience inside retail companies in addition to our decades of core technology expertise. We’ve leveraged the power of APIs and PWAs to build headless systems for multiple clients. We’ve done the application integrations and chosen the best plug-ins from the Magento developer community.
That’s how we sharpen our clients’ competitive edge.
–Jon Wovchko, vice president operations & strategic consulting, digital commerce
When a company first decides to move their commerce platform and supporting toolsets to the cloud, they typically focus most of their attention on deciding what type of cloud (private/public) and provider (AWS, GCP, Azure) they want, and then picking the supporting technologies (Spring Boot, Node.js, React, Kubernetes, etc.).
While these choices are important, they are actually less impactful to a successful migration than you might suspect. All of the providers and supporting technologies are mature: They provide what is required for a commerce platform to run in the cloud. Quite often, it’s the things that don’t get the attention they deserve — or get overlooked entirely — that can make or break a migration project.
This blog covers seven of these often-overlooked factors. The advice below applies to two common scenarios: Working with cloud-based components you own or manage, or interacting with third-party cloud components.
Whichever way you go, you need to pay close attention to these points:
When your customer experience is on the line, you can’t afford unexpected glitches that chase people to the competition or projects that aren’t delivered on time and on budget. This reality underscores the inherent tradeoff of moving to the cloud: To get massive flexibility you have to deal with complexity and up-front cost.
At DMI, we have experts with direct experience in e-commerce operations across multiple retail sectors. We don’t tell clients what they need to do. We scrutinize their marketplace and current technology environment, and help them formulate a strategic, proactive approach to doing what’s best for their customers and their business.
It’s not easy to figure out. But it’s easier if you choose the right partner — one that is committed to the client’s success and knows how to successful navigate the unexpected pitfalls.
—Andrew Powers, senior vice president, solutions delivery, digital commerce
It happens to every hospital or healthcare provider: A crisis or emergency erupts and suddenly patients are calling in droves with urgent questions — overwhelming your patient-care staff. You know this aggravates your patients and you want it fixed now.
You’ve probably heard about intelligent virtual assistants (IVAs), which use machine learning to automate a full range of activities in the patient support process. And you’re wondering: Can IVAs lighten the load on your call-center crews?
They can, but not soon enough to put today’s fire out. When you need help in time frames measured in days, not months, it’s best to think in terms of a journey to IVA, with small intermediate steps that lay the foundation for advanced automation a few months down the road.
While the initial phases do not put every fire out, they still provide priceless data about users’ habits. This data fuels intent-analysis processes that will help your IVA system make smart decisions down the road. Over time, user-intent signals will help you predict future patient support needs.
Thus, all of your patience and preparation early in the journey pay off all along the route. There’s no wasted effort.
These are three optimal phases for making the transition to IVA capability:
It’s best to start with a single on-ramp in your journey to an automated patient experience. It could be a simple webchat bot that asks a patient one or two basic questions before forwarding the call to a human representative. This simple solution automatically eases the strain on your staff and doesn’t take long to implement.
Remember: Everything your patients do in this webchat bot will generate data that trains the IVA system to make smarter decisions as time passes. You can use any channel your patients prefer. The point is, you want to work the bugs out of the first automated process before moving on to more complex capabilities.
With your basic bot up and running, it’s time to add a few more on-ramps to your IVA journey.
That means using bots to answer more difficult questions and automate more of the patient support experience. You might also customize the responses depending on the channel — phones, email and text messaging, for instance.
Now, you have to focus more deeply on thorny issues like authentication: validating the identity of each person and remembering their favorite authentication methods.
Here, it becomes more important to train your support staff properly and confront any shortcomings in your backend IT systems. You need to make sure your legacy systems have enough power to process complex learning algorithms.
Again, you’re feeding data into your intent analysis process to ensure that each user can log in with their favorite methods in the future. Their questions and your automated answers will produce smarter bots, streamline the experience and improve patient satisfaction.
Phase 1 and 2 gave you a firm foundation to implement an intelligent virtual assistant that can respond automatically to calls from a wide range of patients and tailor these responses to their unique preferences.
A full IVA system identifies callers and remembers their habits and behaviors on previous calls. Learning algorithms teach it to take on more complex challenges because it also folds in data from the rest of your patient calls.
The ultimate goal is to free up your patient-support staff to handle jobs that computers aren’t good at — like using their intuition and training to provide a savvy, humane response to a complex patient support issue. That helps improve job satisfaction, potentially reduce turnover costs.
DMI has an extensive track record with IVAs in multiple sectors like health care, finance and government. Our vast pool of talent in business consulting, automation, system architecture, machine learning, data science and patient experience ensures we have the right skills. Our focus on Agile methodologies gets the right solution into our clients’ hands in tight time frames. When you have big fires to put out, these are the skills you need.
–Niraj Patel, director, artificial intelligence
You can’t avoid every bump in the road to modernizing your e-commerce infrastructure. But you can anticipate the most common roadblocks, wrong turns and traffic jams.
E-commerce modernization usually means transitioning to a headless IT infrastructure. With headless, you decouple the frontend of your IT infrastructure — typically the presentation tier — from the backend, where most of the business logic resides. Headless lets you rapidly iterate your frontend to finetune your customer experience without having to coordinate everything with the backend, which would bog down development.
Avoiding these six pitfalls can make your journey to headless commerce go much more smoothly:
Strategic oversights. You can’t afford to scrimp on strategy in your headless commerce journey. That means starting with a discovery process and gap analysis that assesses your current IT state — systems, hardware, personnel, skills, partners and methodologies — and lays out a roadmap for moving toward a headless ecosystem that meets your current and future needs. The more planning you build into your strategic roadmap, the better your chances of success in the long haul.
Time-frame miscalculations. It’s easy to underestimate how much time is involved in a headless transformation. Every company has unique IT challenges and marketplace realities. You may have a small IT team that needs lots of help, or a large IT team that needs only highly specialized assistance. It takes a lot of fact-finding, research and meetings to figure everything out. That can take more time than you might expect.
Platform and software stack slipups. Missteps in choosing the right headless e-commerce platform or software stack for the head can cause headaches for years to come. Choose the platform that meets your current and future needs. Every software stack approach for building the head (presentation tier) has pros and cons. The best route is to draw up a list of requirements, assess your current IT skillsets and pick the software stack that gives you the most of what you need with the fewest compromises.
Skill misalignments. Conventional e-commerce platforms need abundant expertise in the backend, while developing the head on a headless commerce platform requires a separate set of frontend skills. Moreover, headless commerce requires a wealth of experience with cloud technologies and microservices. Your headless commerce journey must assess your skillsets across all the new technologies and plug any gaps you discover.
Methodology missteps. Headless commerce allows a rapid release and iteration cycle that requires continuous integration of skills from multiple disciplines beyond IT, such as UI design, digital marketing and product development. Agile and DevOps methodologies provide the framework for keeping everybody aligned during two- or three-week development cycles.
Botched buy-in. Everybody must pull together. Otherwise, all the benefits of headless commerce collapse. That’s why it’s essential to secure buy-in from everybody involved in the transition — not only the leadership but also the rank-and-file technical teams and support people.
Headless commerce delivers immense value in the digital marketplace, but you have to pay a cost in complexity to enjoy that value. To make it all work, you need a partner with deep experience in online commerce and broad technical expertise across frontend, backend and cloud software platforms. These are the capabilities that DMI brings to your headless commerce transition. Our consultants know how to merge commerce domain knowledge, IT infrastructure, marketing and user experience design to give our clients a head start in their headless transition.
—Atul Bhammar, senior vice president, solutions architect, digital commerce
This is the first in a three-part blog series about the use of Magento.
Headless commerce is changing the face of digital commerce because it allows companies to craft experiences that customers can’t get anywhere else.
A headless system decouples the frontend (typically the user interface layer) from the backend, where most of the computing power resides. This allows developers to customize user experiences for phones, PCs and other devices on the frontend while keeping a standard backend for the most demanding computing tasks.
Retailers are warming to headless commerce because it gives them a chance to set themselves apart in an era of relentless competition. Magento is an attractive option for headless commerce because it provides boundless flexibility to e-commerce system designers and managers.
On the front end. Magento allows frontend designers to leverage the powerful features of Adobe Experience Manager. Adobe has been building best-of-breed visual design software for decades. Adobe Experience Manager has everything website and application designers need to craft seamless shopping experiences across multiple media platforms — smartphones, tablets, websites and more.
Before headless commerce came along, companies often had to choose an e-commerce platform on the strength of its backend computing power, regardless of any weaknesses in the frontend design system. There’s no more grin-and-bear it with headless computing. Designers can pick the best frontend tools for their specific needs. That leads to better experiences and happier customers.
In the middle. Magento has robust frameworks for the APIs (application programming interfaces) and PWAs (progressive web applications) that maximize the impact of headless commerce. APIs let multiple applications share data and communicate with each other (the GraphQL support added in version 2.3.x of Magento makes API communications more efficient). PWAs bring the functionality of a mobile app into a web page, providing app-like services without requiring users to download an app and update it themselves.
As customer experience developers implement more machine learning to customize and streamline online shopping, PWAs and APIs will become even more crucial to headless commerce.
On the backend. Rich consumer experiences powered by machine learning require substantial computing muscle. So, the same Magento flexibility that gives experience designers an edge also ensures that IT teams can implement the most powerful computing resources. Moreover, Magento’s advanced API frameworks ensure that retailers can plug their ecommerce systems into their systems for managing resources and customers.
While monolithic, all-in-one digital commerce systems are fading into history, Magento is leading the charge into the future because it helps developers get next-generation user experiences into the marketplace much faster. Bear in mind, however, that if your legacy backend system still performs to your satisfaction, you can keep it while leveraging all the frontend advantages of headless commerce.
The flexibility of headless commerce accelerates development timelines because you don’t have to align frontend development with your backend e-commerce computing infrastructure. But immense flexibility comes at a price: You have to invest time and energy in creating a well-thought-out roadmap to implement headless commerce.
That means taking extra care to account for variables like search engine optimization, bots masquerading as humans, proper analytics tracing and monitoring for errors that may no longer show up in traditional server application logs.
Magento has a global community of developers providing a galaxy of precise solutions to all manner of e-commerce challenges. With so many options available, a few stray missteps can undermine all your progress. At DMI, we draw on a deep well of experience in both the retail and the system development sides of the equation. We put these skills to use helping our clients craft an effective, efficient roadmap for implementing and managing Magento.
— Jon Wovchko, vice president operations & strategic consulting, digital commerce
In an age where consumers are in control, brands have to work harder than ever to cut through the noise to reach their consumers. Then they must also engage their audience in meaningful ways to earn their trust and loyalty. That means marketers are having to get creative. The brands that are willing to take a leap and do something bold are the ones that will reap the rewards.
When the International Spy Museum, a partner of DMI’s since 2014, was planning to move locations into a new, bigger, better, purpose-built facility across Washington, D.C., we knew we needed to do something big. The museum would be closed for more than four months for relocation, but this time was essential for generating buzz in advance of the grand opening.
Here are the four key principles we followed to build the wildly successful “Mission countdown” activation:
For the Spy Museum, we had the benefit of four years of understanding their audience prior to the big move. We knew they had a core set of very loyal and very knowledgeable fans who followed the various Spy Museum social channels. We knew that if we wanted to connect with the fan base, we were going to need to speak their language. We had to create an experience that felt truly ‘insider’ and not like a marketing campaign.
We decided to send our followers on their own undercover mission in the real world. Over the course of four weeks leading up to the opening of the museum, we released clues to 36 different dead drops hidden in the D.C. area that contained prizes from free museum tickets to access to the opening gala. To participate, fans had to crack clues to unlock the secret location of the dead drop, then go to that place to either collect the physical dead drop container or claim the digital dead drop pinned to that location. The technology we implemented enabled thousands of individuals to play at the same time while giving each their own unique experience, and allowing just 36 skilled agents to claim the prizes. The activation was a major hit with the Spy Museum fans, leading them to tag their friends to participate. It also generated a 28% increase in organic Twitter impressions month-over-month, as well as garnering earned media impressions to further build excitement and awareness for the museum.
The key is authenticity.
Don’t do a filmed stunt just because everybody else is doing it. Don’t post about an issue that is taking over social if your brand has no business being in that conversation. Start with your mission, and you can’t go wrong. Your brand is what it is, and if your marketing doesn’t represent that, the brand lift will be short-lived at best and tarnish your reputation at worst.
For the Spy Museum, we could have done a simple ticket giveaway or social media contest. But none of that felt right for their brand. It took a tremendous amount of research and effort to create an experience that would surprise and delight the most knowledgeable spy enthusiasts. Each of the 36 dead drops was placed at a location where a moment in spy history occurred, like an actual dead-drop site, or a restaurant where clandestine meetings occurred.
The 36 clues were all different puzzles, challenging our audience’s spy skills, like analyzing intel and cracking codes. This also enabled all players to engage, even after the prizes were claimed. The entire experience was carefully designed from start to finish to really put the audience into the shoes of a spy in the way that the new museum would upon opening. During a time the museum was closed, we actually turned the entire city into a museum where history came to life.
For the Spy Museum’s Mission, we released the clues in batches over the course of several weeks, giving more fans more opportunities to engage and win. We launched the game to the Museum’s followers first, giving our most loyal fans the first chance to win. Over the course of several weeks, we released more batches of clues and slowly began to use paid media to drive traffic. As the activation built momentum the earned press began, and as a result the final release of clues had the highest engagement of all the releases.
In the case of the Spy Museum activation, we built an experience like nothing that had ever been done before using a technology platform that was new to the market. While we did everything we could to ensure success, there was still an element of uncertainty. But with great risk comes great reward. All 36 prizes were claimed. Most of them were claimed within just a few hours of the clues being released, one prize took just 23 minutes to be claimed. Thousands of existing fans were engaged, and thousands more became fans. Earned, owned and paid media generated more than 2 million impressions. Most importantly, the museum delivered an authentic experience and delivered on its mission to educate, even when their doors weren’t yet opened.
— Elizabeth Van Blargan, associate creative director, DMI’s Brand Marketing & Customer Experience Division
The appeal of a digital twin is obvious: You deploy a digital model that mimics real-world behavior — detecting inefficiencies, optimizing performance and learning to improve in real time.
Digital twins are starting to generate buzz in the tech sector because they represent the next phase in the evolution of computer modeling. Conventional digital models attempt to predict future results before building complex systems, anticipating problems in the virtual realm before they cause expensive trouble in real life. Digital twins build on these strengths by providing instant feedback and machine learning.
Fortunately, the sensors, networks, software and computers required to build digital twins are readily available. Indeed, they’re already finding a home in Industry 4.0 applications, where they’re streamlining production and enabling predictive maintenance.
Moreover, there are strong incentives to move these interactive replicas into new realms. After all, if digital twins can optimize machines, why can’t they improve human outcomes?
That’s where things get complicated.
Consider a sophisticated digital twin used by a professional sports team. It’s conceivable that wireless sensors in clothing and equipment combined with digital video cameras, 3D modeling and advanced learning algorithms could mimic an entire game while it’s being played. Sensors and software could detect which players are off their games and recommend improvements in real time.
This futuristic scenario is easy to envision. Embracing the full potential of digital twinning, however, is a lot more challenging.
Pretty much any behavior in the natural world is a candidate for digital twin development. It’s not just people and machines. It could be weather, the flow of water or the accumulation of pollutants.
Thus, you’re looking at a veritable mountain of distractions and dead ends. To mine the nugget of productive opportunity with digital twins, you have to narrow your focus.
To do that, ask some basic questions: Do you have a process where you’re reasonably certain that a better understanding of customer behavior will improve revenues or profitability? Do you sell a complex product with a steep learning curve that would benefit from insights on user behavior?
Zero in on a few processes you’d like to optimize and build from there. Remember, machine learning is a core component of a productive digital twin. If you build it right, it will teach itself to work better over time.
It’s imperative to avoid bright-shiny-object syndrome. You have to start with a pressing need — not a nice-to-have.
After you’ve targeted your best digital-twin opportunity, you have to amass the skills required to make it happen. These skills span four disciplines:
Your digital twin solution will need equal measures of design creativity, strategic vision and technical acumen. Dovetailing all these skills is a non-trivial task.
Admittedly, digital twin technology is in its infancy. In the years to come, innovations in edge computing and the growth of 5G wireless networks should expand its horizons. Advances in artificial intelligence, machine learning and neural networks will open even more opportunities.
Even if you don’t think digital twins are a good fit for your business today, it’s a good idea to monitor developments — especially in the consumer sector. If a breakout innovation hits the mass market, it could be as big as the smartphone.
We’re not predicting the future at DMI, but we do know promising technology when we see it. As we gather more insight and experience designing and implementing digital twins, we’ll make sure our clients benefit from everything we learn.
–Michael Deittrick, senior vice president digital strategy, chief digital officer
Tell us about the LivePerson mission.
Our mission is to make life easier for people and brands though trusted conversational AI. Leveraging decades of data and a powerful AI-engine, we develop conversational experiences for top companies including HSBC, Home Depot, Orange, and GM Financial, helping to ensure today’s consumers are served with the personalized customer experience they have come to expect.
Explain the “Fourth Industrial Revolution.”
The term “Fourth Industrial Revolution” represents the blurring of boundaries between the physical, digital and biological worlds. We are at the start of a convergence of advances in artificial intelligence (AI), robotics, the Internet of Things (IoT), 3D printing, genetic engineering, quantum computing and other emerging technologies. This convergence is the force behind many products and services that are quickly becoming indispensable to modern life, GPS for example. This is also paving the way for a seismic shift in the way people live day-to-day and the way business is conducted. We at LivePerson are excited to be helping to manage this change on behalf of our customers.
How is the “Fourth Industrial Revolution” affecting consumer behavior?
Differentiation based on brand is rapidly disappearing. As technology has enabled businesses to offer more connected experiences, today’s consumers have many more options and are not afraid to switch brands to find a better experience. In fact, 73 percent of consumers will give up on a brand if they cannot get an answer to their question within 10 minutes. Consumers have come to expect immediacy when it comes to brand engagement.
What percentage of consumer inquiries can be automated?
Nearly 70% of consumer inquires can be automated. What’s more, 90% of consumers begin their shopping journey online but in the U.S., less than 15% of sales are completed online. Consumers need to ask questions, get advice and understand their options before making their purchases. Conversational interfaces make this possible without the shopper ever having to visit a store or place a call. Today, 50 percent of all conversations (tens of millions) on our platform are automated; that’s a jump of almost 200 percent over past year-and-a-half!
How difficult is it for companies to implement conversational interfaces?
Building automations can be slow and fragmented with a heavy reliance on developers. However, our Conversation Builder is an all-in-one platform tailor-made for conversational commerce, giving brands a dramatically faster and non-technical way to implement automation. Additionally, team members, such as customer care managers and even qualified agents, can participate in creating and optimizing chatbots.
What role does messaging play in the future of commerce?
Today 13 million texts are sent every minute in the world. There are 100 million messages sent every day on platforms like WhatsApp and Facebook messenger. That’s astounding. Thus, many of the tasks we now do, such as shopping, will be shifted to messaging and voice platforms such as WhatsApp, Apple Business Chat, and Alexa. Conversation is just a much more natural way to interact with brands. For businesses to scale this, they’ll need the help of really effective conversational AI, which is where we come in.
What has your experience been like working with the DMI team?
We at LivePerson have been extremely pleased with the DMI partnership. The team’s technical expertise is impressive and we share a common vision and passion for digital transformation. Additionally, with DMI’s deep roots in the government contracting sector, we look forward to exploring opportunities to enhance the customer experience for U.S. federal agencies and the Americans they serve.
As a technology professional focused on retail and commerce, this was my 15th NRF Expo and Show (but who is counting?). The venue is, of course, enormous, yet convenient. The content is breathtaking and well …breathtaking. The experience can be a bit like drinking from the proverbial fire hose. At certain times over the years, it was difficult to differentiate between an actual positive technology trend or just hoopla.
I have been here before to hear about everything from RFIDs, a new company named Amazon that was suddenly selling more than just books and CDs (remember those?), self-checkouts and the promise of kiosks, and of course, the “elusive” predictive merchandise and financial planning solution everybody seems to always be looking for. Here’s what REALLY impressed me this time around:
At DMI, we use technology to solve business problems — which creates a winning strategy. Of course, we have a lot of smart technical folks, but our focus is on how we can make your business successful. We care fanatically about how your customers and prospects perceive your brand for example. We make it our business to help you build the right ROI model for your particular project. And because of this, we have an army of very happy customers to back us up.
If you feel overwhelmed by the amount of stories coming out of NRF2020, get in contact with us at DMI. We will help you navigate the technology while we listen to YOUR story.
— Pablo Pazmino, senior client partner, consumer vertical
Using predictive algorithms in customer care poses a challenge you might not anticipate: Accurate predictions don’t automatically generate better business outcomes.
When you’re automating elements of your customer care system, there’s a strong tendency to prize accuracy over everything else. After all, inaccurate predictions defeat the purpose of deploying artificial intelligence and machine learning.
But zeroing in on predictive accuracy is not the whole story — predictions have to be helping you improve the customer-care experience. Thus, you have to prioritize impact over accuracy.
Let’s take a look at how this works.
Machine learning algorithms comb through billions of data points, using pattern matching to distinguish between the outcomes you want and the ones you hope to avoid. With a large enough set of training data, the algorithms learn to create more accurate predictions over time.
All of this is built around complex mathematical formulas that analyze previous patterns of behavior and predict the likelihood of these things happening again. The more accurate these calculations are, the better your predictive capability.
Every time you accurately anticipate a customer’s behavior and help improve their satisfaction with an engagement or transaction, you’re producing better business outcomes. Thus, accuracy matters — as long as it’s generating the impact you want.
In the call center, you want customers’ questions answered and complaints resolved as quickly as possible. With predictive modeling, you correlate data from multiple sources to understand the context of customer calls, answering questions such as:
You also have to track customers’ behavior throughout the customer-care journey. Do you force them to scroll through a long menu of choices, or do you use automation to anticipate their needs and reduce their menu options to one or two?
You also can create AI-enabled chatbots to assess exactly what the customer wants. If they want something that the bot can do easily with little risk of failure, then you keep the user within the automated voice interface.
If, however, the customer has a more complex challenge that requires human intervention, then your bot should forward them to the right person. Your customer reps should have all the data they need about the product and the caller to produce a happy outcome.
Why Impact is More Important than Accuracy
With a large enough dataset, a robust statistical model and a well-designed algorithm, you can accurately predict how people will answer the questions listed above. Indeed, you can expend considerable resources producing accurate predictions of their replies.
But you have only so many people, only so much budget, and only so much time to spend on automating your customer care system. Moreover, algorithms can provide uncannily accurate predictions that have no measurable influence on your business.
Thus, you have to think first about impact. Which predictions get customers what they want sooner? Which ones streamline your operations? Those are the kinds of questions your algorithms should answer.
At DMI, we urge our clients to start with the goal of using AI to predict a single useful outcome. You don’t need a moonshot that automates your entire customer care system. You just need a solid foundation to build upon.
Learning to prize impact over accuracy is central to making that happen.
— Niraj Patel, director artificial intelligence
They all have to come together — people and data, assets and inventions.
The 2020s will bring technologies like digital twins, swarm intelligence and virtual/augmented reality into the mobile mainstream. Fatter networks, faster computers and ubiquitous sensors will produce vast torrents of real-time data. All these advances, in turn, allow increasingly accurate predictions that reinforce the need for transformative technologies.
It’s tough enough mastering any one of these challenges. The future belongs to those who converge them all. At DMI, we’ve identified four pillars of digital convergence:
We find that companies often excel on the human side but lag on the data side. Or they excel with data but need help developing human-centered user interfaces. DMI’s convergence framework acknowledges that companies often have worthwhile systems and might not require a rip-and-replace project. It also encourages clients to invent new, potentially disruptive products and services that strengthen their competitive position.
Any of these efforts is worthwhile on its own. But with technology evolving so quickly in the 2020s, organizations have to succeed at all four. That’s why our convergence framework pulls these forces into alignment.
What Convergence Looks Like
Consider the challenge of developing new pharmaceuticals. It takes years of effort in laboratories and clinical trials to bring effective cures into the marketplace, pushing costs into the stratosphere. Technologies that shrink development times while ensuring safe treatments can save lives and earn substantial fortunes for their inventors.
Technology convergence can help with:
Excelling in one or two of these areas would have been a laudable achievement in years past. But in the years to come, there will be no choice but to do all four.
Converging in the 2020s in Every Industry
Complex industries like pharmaceuticals, health care and automotive manufacturing have strong incentives to embrace a converged digital transformation model. With upstart competitors bringing new ideas to market every month, incumbents can’t afford complacency.
But we believe the DMI framework applies to any kind of organization or enterprise. We built flexibility into our framework to ensure that companies of any age or size can find a model that suits their marketplace and business goals.
Just consider the virtual/augmented reality example: Call center representatives wearing 3D AR/VR goggles could envision the products they support from every angle, making it much easier to answer callers’ questions and then move on to the next customer. A human-centric system like this would require a sophisticated interplay of data, invention and leveraged assets.
At the same time, weaknesses in any of the four pillars of convergence would undermine everything.
A Convergence Partner
DMI’s converged framework accounts for the entire digital transformation process. We start with a sound technology strategy built upon the client’s precise business requirements and competitive environment.
From there, we build a strategic framework for organizational change to ensure that everybody who matters to the client — employees, customers, vendors, etc. — contributes to the transformation project. Once we’ve laid that groundwork, we create a roadmap describing how to get all these efforts moving in the same direction at the same time.
That’s where our skills and our clients’ priorities converge.
-Andrew Brockett, senior director/digital technology office
It’s not enough to produce speed and value in Agile product development. You have to provide speed TO value.
Making that happen requires a sound strategic footing. You have to understand why your company needs to use agile methodologies and how they will outperform conventional methodologies like waterfall.
Winning with Agile requires a sound time-to-value strategy. Here are three keys to formulating that strategy, based on DMI’s deep experience with Agile development across multiple industry sectors.
Agile cannot happen in a vacuum. It has to work in the context of your company’s primary goals. Moreover, Agile performs best when you can merge speed and value to do the most good.
If you’re getting disrupted by a well-funded startup, for instance, you have no time to waste on rigid waterfall methodologies. You need a fast, flexible route to value — whether you’re adding revenue, reducing risk or building market share. Agile gives you that.
However, waterfall may be the better choice if you expect minimal changes to a project’s scope, schedule and budget. You have to find the best fit for your specific objectives.
Agile development typically happens with small teams working in sprints of two to four weeks. Teams create a prioritized backlog of tasks to perform, tracking their progress on a burndown chart. While this approach is effective, focusing only on progress and productivity does not paint the full picture when Agile’s primary objective is to produce speed-to-value.
At DMI, we prioritize Agile development like this: Value > quality > progress > productivity. All of these factors are absolutely crucial to Agile success, but we find that progress and productivity don’t mean much unless they serve higher goals of adding value and upholding quality.
Thus, we emphasize delivering value supported by high-quality software with a minimum of bugs. Emphasizing value and quality also eliminates slip-ups that thwart progress and productivity.
Agile doesn’t have the hard-and-fast structure of waterfall methodologies, so it can be difficult to quantify your success. But it can be done.
DMI developed a proprietary formula to measure the success of Agile teams. We named it APIX (Agile Performance IndeX) and we designed it to address a well-known phenomenon: measuring something influences your outcome. When you track Agile success only with burndown charts, for instance, you can emphasize progress even without enhancing time-to-value.
APIX measures Agile success by prioritizing value and quality over progress and productivity. Measuring Agile this way encourages teams to pursue the most valuable outcomes.
We customize APIX’s parameters to suit the needs of each client. Contact us to find out how to put APIX to work in your next Agile development initiative.
— Brian Andrzejewski, vice president, business transformation services
Tell us about your work at General Motors.
I’m proud to have worked at General Motors for 26 years. I recently began a new role leading Product Marketing for our Full-Size Vans and Light Commercial Vehicles. It’s an exciting space, as the number of fleets of corporate EV’s is rapidly growing thanks to the expansion of online shopping and a need for vehicles to deliver packages. Through the years at GM, I’ve also held operations leadership roles helping to build organizational effectiveness and driving continuous process improvements.
We understand GM’s mobile inspection app is set to be rolled out in early 2020. Why was there a need for such an app?
General Motors sells over 100,000 cars a year in the used car space; many are rental return vehicles. There are numerous intricacies involved in the inspection of these vehicles to ensure they can be turned around quickly and safely to be sold online or at auction. We needed a solution to transition from our legacy digital picture-based inspection tool, which was not uniform across our inspection providers, to a new AI-based tool that could be deployed quickly to any supplier in any location. I’m excited to report that the proof-of-concept we worked on last year was successful and demonstrated significant efficiencies. The app is being rolled out to our 35 suppliers in February.
Describe the inspection apps’ functionalities.
Simply by scanning a vehicle’s VIN number, the app extracts data about condition history of the car. Inspectors have the ability to submit photos and comments via mobile devices. Thus, the technology allows inspectors to easily identify and report possible issues, including open recalls, before any time and money are spent on labor. Instead of waiting for paper forms to cross their desks, administrators are alerted to issues promptly so vehicles can get on the road more quickly.
What’s the most exciting part about seeing this proof-of-concept be deployed into production?
First, the inspection app can continually be improved. Being able to roll out a solution that empowers us to move quickly when we find issues or desire improvements is tremendous. The second most exciting part is the amount of money projected to be saved annually. In the wholesale market, speed and efficiency translate into significant cost savings for OEM’s and rental companies, as well as auctions and dealers. Timeline improvements benefit all segments of the supply chain.
What was your experience like working with the DMI team on development of the inspection app?
Through our work on the inspection app we’ve formed a trusted working partnership and great relationship with DMI. The team is highly-innovative. When we had challenges, it seemed like overnight they’d come back and say, ‘This is what we figured out. What about doing it this way?’ In the two years we’ve worked with DMI, I’ve never felt like we were getting a sales pitch. The team is super collaborative and creative. It’s been fun.
You have to be Agile these days. That’s what all the Agile true believers say.
But those are just words if you’ve used waterfall methodologies for years. Perhaps you’ve suffered through a worst-case waterfall project — wasting millions on software that’s obsolete when it hits the market. You know you need a better way, especially with technologies changing so quickly.
Agile methodologies have proven their superiority to waterfall across a vast range of use cases. But where do you start? All those books, articles, videos, blog posts and conferences devoted to Agile are overwhelming.
Before you charge headlong into the Agile ecosystem, it’ll help to answer three fundamental questions:
Everything about Agile boils down to producing value quickly. Agile teams of about 8-12 people build a high-quality minimum viable product (MVP) as quickly as they can — typically in less than a month — and then rely on user feedback to fix bugs and add features in future iterations.
This is a sharp departure from waterfall developments, which prioritize scope, schedule and budget. Waterfall works fine if you anticipate little or no change in a project. But change is inevitable with most technology projects, so you have to be able to adjust on the fly. Where should you adjust first? Agile says, “let’s prioritize the changes that drive the most value.”
Agile is a mindset, so you have to change how your people think about getting products to market quickly. That change starts in the C-suite and runs all the way through to your managers and technical teams.
A shift this substantial cannot happen overnight. You need training programs and a game plan to implement your changes. At DMI, we’ve helped dozens of companies make the shift to Agile and scale it over time. We’ve learned that even highly regulated companies like medical device manufacturers can thrive with Agile methodologies. Making your culture more Agile is central to making this happen.
Metrics are the one authentic advantage of waterfall — you always have data on budget, scope and schedule. While these suit the needs of CIOs and their C-suite colleagues, these stats don’t measure the right things in the Agile world.
At DMI, we’ve learned you need to quantify value, quality, progress and productivity — prioritized in that order — to measure Agile success. In fact, we have developed a proprietary formula for Agile metrics that rival the clarity of waterfall data. If you’re interested in Agile metrics, ask us about APIX (Agile Performance IndeX).
Measuring the right things in the right way can make all the difference in Agile development.
— Brian Andrzejewski, vice president, business transformation services
The internet of things (IoT) is a complex expression of a simple idea: connecting a sensor to the internet in any time or place where it’s useful.
But there’s one formidable challenge: How do you make sense of all that sensor data? The best answer is to apply artificial intelligence/machine learning (AI/ML) algorithms that automate the collection, storage and analysis of IoT device data.
IoT devices come in countless forms — phones, wearables, smart speakers, video cameras, location beacons and things that haven’t been invented yet. In theory, IoT applications can converge data from all these sensors to generate unique insights and unforgettable customer experiences. In reality, AI/ML is mandatory to make everything work together.
A quick look at three emerging connectivity technologies of the 2020s — 5G networks, geospatial commerce and smart-cities applications — illustrates the crucial role of machine intelligence in IoT.
The next generation of wireless networks will generate a massive boost in mobile bandwidth in the 2020s. That will flood the internet with rivers of new data. IoT applications will inevitably spring up to leverage this new bandwidth.
Mobile devices and remote locations will provide two of the most logical use cases for 5G networks. It won’t just be consumers downloading 4K movies to their iPads. It’ll be medical providers live-streaming patient data to specialists in far-flung locales. Safety inspectors will use video and AI to scan for hazards that still images miss.
These high-bandwidth applications can generate mega-volumes of data that enable predictive AI. Algorithms that accurately forecast future outcomes allow people to be proactive vs. reactive, which has immense value. Now, imagine subtracting the predictive-AI component of 5G and IoT. The value proposition is far less clear.
Smartphone apps and location beacons enable the creation of geofenced areas that can document the positions of people and products in three dimensions in real time.
Geospatial Applications have profound potential in the commercial realm. Sensors can detect when consumers enter a specific section of a store, and notifications can direct them to the exact location of a product. On a cruise ship or in an amusement park, families can coordinate their activities and use mobile maps to find their favorite attractions.
But think about how much data these applications generate. And consider the ethical implications of tracking people’s behavior on such a broad scale. AI algorithms are essential to crafting consistent, highly personalized user experiences that stay within the bounds of humane privacy guidelines.
Smart cities represent the pinnacle of geospatial IoT applications. Sensors in traffic lights, bus stops and scooters will be able to work together to optimize traffic patterns and help urbanites travel to jobs, stores and entertainment venues.
In the public safety realm, IoT sensors and geofencing can help law enforcement agencies target their efforts where they can have the most impact. That could reduce the likelihood of unnecessary run-ins with people going about their business. Predictive AI could presumably make this kind of application even more effective.
While commercial IoT raises ethical concerns, smart-cities applications must deal with legal mandates. Again, this is an area where machine learning can help ensure that IoT initiatives conform with local ordinances.
5G networks and geospatial/smart-cities applications are only the most likely trends to emerge in the 2020s. More beguiling is the possibility that the application that pulls it all together does not even exist today.
Of course, a lot of uncertainties remain. Will 5G become pervasive enough to enable widespread IoT applications? Will public objections stall the progress of real-time behavior analysis? Will cities find the resources to embrace smart technologies?
We suspect the answers to these questions will emerge from use cases — people and companies trying, failing and trying again to profit from ubiquitous connectivity. The people who master the combination of AI, IoT and analytics cannot be known today, but it’s safe bet that they’ll be household names before the decade ends.
— Niraj Patel, director artificial intelligence
As the decade ends, we are witnessing a tremendous acceleration in the utility and capability of artificial intelligence and machine learning as business tools. This trend will only continue as the calendar changes from 2019 to 2020.
At DMI, our clients and partners are already seeing the benefits of using new technologies. By putting learning algorithms to work to streamline operations and develop predictive capability, using chatbots and other conversational AI technologies businesses are opening up new avenues for improving customer service. While these trends have transformative potential, they also pose thorny ethical questions that cannot be ignored.
These questions will be critical to consider in the next year and decade to come as businesses grapple with the need to improve their processes with the moral imperative to respect their customers. There are a number of areas where these questions will play out.
Retailers are using AI to automate and streamline back-office applications to improve efficiencies: to control supply chains, to connect customers to purchases, to track and predict behaviors to improve the consumer experience.
Increasingly, we aren’t just using machines as tools – we are communicating with them. We ask and they respond, just as Alexa and Siri answer our questions, customers are able to get assistance from businesses ranging from banks to their doctor from machines, who have intuitively learned how to guide people to good decisions.
As impressive as these applications are, they challenge us to know their limits – to know when a machine’s capabilities are not up to the challenge, to know when a human being must answer the questions being asked, to know the difference between information and knowledge, between data and wisdom. Failing to recognize the limitations of technology can set up both businesses and customers for failure.
In the retail sector, we will continue to use AI to streamline the customer experience. One example of this will be tightening and improving supply chain processes.
In looking at customer service, using AI chatbots can make life easier for agents. Chatbots can process information quickly, handling more requests, while prioritizing particularly challenging questions. Some applications will have customers welcoming the AI, for example, people can be more comfortable talking to a bot about personal issues they’d rather not reveal to a person. In a more common scenario, you can automate simple queries like basic product information that a bot can deliver more efficiently than a human. As our survey revealed, resistance to AI happens on a continuum. You’re much better off embracing the low-resistance end of that range.
Government agencies face challenges the private sector does not privacy regulations and public accountability chief among them. Those challenges make deploy AI in government processes complicated.
Nevertheless, agencies are launching AI pilot projects and inviting companies to compete for a chance to participate. As these small projects expand, federal agencies will gradually add more AI/ML to their technology portfolios in 2020 and throughout the decade. DMI’s work in this area can provide a roadmap for these efforts.
Ultimately, the federal government and the private sector reach their destinations via wildly diverging routes, but they share the same desire — using thinking machines to unleash the superior power of human cognition.
While not the public sector, the finance world provides many of the same challenges. The paramount importance data protection, the need to protect institutions from legal liabilities and stiff regulations governing transactions and data.
While AI offers potential solutions, it can be taxing to seamlessly integrate these new tools.
Data comes from multiple sources in many formats. We have to assess whether the data is accurate or producing false-positives. If inaccurate data pollutes useful data, we have to scrub out the inaccuracies.
Across the board, the business environment is becoming more integrated, more connected and more dependent on intelligent machines to think and learn and provide value for companies.
DMI is committed to moving forward with our partners across a variety of sectors in ways that best suit their business models. Helping them to cede a measure of control to machines while leaving ultimate authority in the hands of humans. Our experience with machine intelligence gives us the grounding to help clients find thoughtful, humane ways to strike that balance.
We want to help leaders maximize the potential AI can bring to their businesses. By harnessing the power of machine learning and artificial intelligence, and doing so responsibly, businesses can improve their own processes and the experiences of their customers.
Automakers face nonstop demands to embrace new technologies. One year, it’s smartphone integration. The next year, it’s big data. Then it’s artificial intelligence and machine learning (AI/ML).
In such a highly competitive industry, GM and Toyota can’t afford to let Ford and Volkswagen gain a technology edge. Thus, it’s only natural that industry players tend to be reactive to demands for new tech. The trouble is, companies across the sector have created patchworks of solutions and silos that are becoming increasingly difficult to manage. Technical debts are piling up amid mounting consumer demands and rapid-fire technology innovation.
In the 2020s, automakers will face a reckoning. They can’t just keep plugging in new technologies as the need arises. They need a more proactive, strategic approach:
Why will this shift be so important in the coming decade? These challenges spring to mind:
Consumers expect their vehicles to be computing devices that anticipate their needs and improves their lives. Everything is getting smarter — from the speakers in people’s living rooms to the cities where they work and play. Technical behemoths like Google, Apple and Microsoft are getting into the connected-transportation business.
These and many more social and technical developments will pick up speed in the 2020s. But they won’t happen in isolation. They’ll converge. Automakers need a robust, sophisticated technology strategy to navigate this convergence.
Most cars rolling off assembly lines in 2019 still have 3G communication modules. Meanwhile, everybody in the technology sphere is gearing up for 5G. The best news for OEMs is that consumer adoption of 5G is at least two years away.
Sure, some consumers will use tethered 5G smartphones to bring high-bandwidth infotainment services into their cars within a few years. But it’s a safe bet that 5G won’t be a mainstream technology until mid-decade.
Nevertheless, automakers have to start planning for 5G in 2020. Given the long production cycles of the automotive industry, OEMs cannot risk getting outmaneuvered by disruptive startups. They need to be ready when 5G hits the mainstream.
Though self-driving vehicles pose immense technical challenges that may well delay Level 5 autonomy until the end of the 2020s, the evolution of in-car automation will bring a host of new driver-assist features. At the same time, electric cars and trucks will become increasingly common. Moreover, smaller battery-powered devices like scooters and drones could have a significant impact on mobility and transportation as the decade unfolds.
Advances in AI/ML and robotic process automation will be central to the rise of electrification in the coming decade. Learning algorithms, data science and advanced analytics have the potential to transform transportation, from sourcing to production to marketing to service. These are profoundly complex innovations that must dovetail with a forward-looking technical strategy.
Everybody in the transportation business needs to think deeply about how data is used, stored and protected. Customers and colleagues must be able to trust that tracking and personalization technologies won’t be misused.
As the risks of automation and connected travel start to rival the rewards, governments will get more deeply involved in creating standards and boundaries to protect people and their data. Complying with these rules will be a constant challenge for OEMs in the years to come.
DMI’s automotive industry experts know how to build delightful consumer experiences, implement automation and ensure compliance. These are tough jobs in their own right. Doing them together brings a quantum leap in difficulty.
That’s why we developed a converged framework that gives OEMs precise guidance on transforming their corporate culture while crafting an in-depth technology strategy. The framework starts with consulting workshops that help companies author a persuasive narrative for change. Next, it shows OEMs how to choose technical solutions that best fit their change narrative.
The technology reckoning of the 2020s will happen. DMI’s convergence framework gives OEMs the tools they need to confront it.
— James Bydalek, automotive and transportation, industry general manager
Artificial intelligence can help retailers craft remarkable customer experiences. Natural language processing can improve customer service and spare employees from boring, repetitive chores.
It’s all good until you crash into reality. Customers and employees aren’t always excited about change. Some are outright resisters. Meanwhile, questions about next-gen technology’s financial impacts and return on investment can cloud the judgment of top executives and key decision-makers.
Retailers used to have a lot more time to overcome the pitfalls of adopting next-gen tools. But with disruptive threats coming at them from every direction these days, retailers have to adapt to change and adopt new technologies as quickly as possible.
DMI developed a program called VisionNEXT to help companies rapidly adopt new technologies. VisionNEXT operates as a pair of workshops that help companies explore all of their options and find the most practical ways to embrace next-gen hardware and software.
The point of these workshops is to get you to “why.” That is, we help retail clients explore the crucial forces motivating their need to adopt the next generation of retail tech.
We’ve adapted this process to modern-day realities. The old people-processes-technologies framework that was popular for years worked best with monolithic systems and top-down management. In today’s world of VC-funded platforms and rapid disruption, you need a much more flexible model built around collaboration and consensus.
VisionNEXT helps companies craft a narrative around the imperatives of technology change. The goal is to persuade people that it’s in their best interest to adopt next-gen technologies. We recommend getting the program’s detractors directly involved rather than ignoring them and hoping they go away. Because time is of the essence, you can’t afford to let naysayers slow progress. But you also can’t afford to let their expertise go unused.
This kind of real-world perspective defines the VisionNEXT approach. We sit down with your technology leadership and help them chart a path to disruptive innovation.
Nobody should be innovating for innovation’s sake. There’s too much time and money at risk. Instead, you should be finding the best ways to improve competitiveness and ensure adoption of new technologies.
DMI’s VisionNEXT workshops help you clarify the right and wrong ways to go. It’s not just choosing apps and targeting APIs. For instance, you can use the program to reassure employees that automation won’t take their jobs away.
When you know why you’re changing, it’s that much easier to persuade everybody else — co-workers, customers, vendors, directors — to adopt the right tools to get you there.
— Varun Ganapathy, director, commercial/consumer: digital technology office
What is the Takeda mission?
Takeda is an innovative, values-based global pharmaceutical leader that services the needs of patients and physicians worldwide. We’re proud to be a world-class R&D organization dedicated to delivering transformative therapies to patients. Our R&D efforts are focused in the following four areas: Oncology, Gastroenterology (GI), Rare Diseases and Neuroscience. We also make targeted R&D investments in Plasma-Derived Therapies and Vaccines. Takeda has approximately 50,000 global employees.
Tell us how Takeda first began to partner with DMI on digital transformation.
Our relationship with DMI initially began in Zurich more than two years ago when DMI supported Takeda in developing a Digital Center of Excellence to accelerate change across the enterprise. DMI was Takeda’s strategic partner responsible for all of the frameworks, governance, marketing, everything required to put our Digital Service Line in place. Since then, DMI has served as a trusted delivery partner in certain technology areas across the globe, including projects in Asia, Europe and the U.S.
Tell us about your role at Takeda.
For the past several years I’ve been responsible for all of Takeda’s collaboration tools across Microsoft Office 365. I help determine how Takeda can leverage its investment in Office 365 to drive solutions more quickly, whether they are for a finance group, clinical trial partners, etc., and ultimately, how we can derive business value for the organization. My new role as Digital Products Lead entails scaling services from the digital incubator phase to full enterprise solutions ensuring a maximum level of quality.
What is the Microsoft MVP (Most Valued Professional) Award and how does being a Microsoft MVP help you in your role at Takeda?
The Microsoft MVP Award grew out of the software development community and is given to technology experts passionate about sharing their technical expertise with the community, whether their knowledge is directly or indirectly related to Microsoft. I believe as a Microsoft MVP, one of the unique areas of value I bring to Takeda is knowing the right talent to hire. Being a member of the Microsoft MVP community connects you with an ecosystem of unparalleled technology peers. In fact that is how I met DMI’s Chris Kent, whom I frequently collaborate with in my role at Takeda. Chris is a fellow Microsoft MVP, as is DMI’s Corey Roth.
How is partnering with DMI a Value-Add for Takeda?
DMI brings a dedicated team whose technical expertise is second-to-none. What’s more, DMI team members work seamlessly, spanning business units and geography. We at Takeda can honestly say that from a customer perspective, we find the concept of “One DMI” to be right on target.
The U.S. government won’t miss out on the wave of artificial intelligence and machine learning (AI/ML) coming in the 2020s.
That’s not to say it will be an easy ride. Federal agencies have to figure out how to accomplish ambitious AI/ML goals within the bounds of budget, personnel and political necessity. If they get it right, they’ll hand some tasks over to AI algorithms while freeing more people to work on solving human problems beyond the ability of machines.
These are three of the most likely ways that AI will help federal agencies in the 2020s and beyond:
Predicting Likely Outcomes
If AI/ML algorithms have enough data across a long enough time span, they can scan for patterns repeatedly and teach themselves to predict likely outcomes. Because the U.S. government has some of the world’s largest repositories of data, it’s well positioned to develop predictive AI. Likely use cases:
Tightening Security and Compliance
It’s easy to imagine government agencies using AI for the espionage and secret missions that fill so many TV and movie scripts. Some of that will be happening in the 2020s, of course, but with much less pulse-pounding drama. Examples:
Automating Manual Processes
Robotic process automation (RPA) is making waves across the private sector in factories, distribution centers and other commercial applications. The federal government is also getting into RPA. Examples:
What’s on the Horizon in 2020
Federal agencies face constraints that private businesses rarely endure. For instance, rules requiring data privacy and public accountability give the federal government a small threshold for failure. It’s no small challenge to develop AI systems in this environment.
Nevertheless, agencies are launching AI pilot projects and inviting companies to compete for a chance to participate. As these small projects expand, federal agencies will gradually add more AI/ML to their technology portfolios in 2020 and throughout the decade.
Ultimately, the federal government and the private sector reach their destinations via wildly diverging routes, but they share the same desire — using thinking machines to unleash the superior power of human cognition.
–Varun Dogra, chief technology officer
What is the ADESA mission?
ADESA delivers wholesale vehicle auction solutions to professional car buyers and sellers. From data-driven research tools to comprehensive reconditioning services, ADESA simplifies the entire auto auction experience. ADESA is a business unit of global automotive remarketing and technology solutions provider, KAR Global. KAR Global has made strategic investments in acquiring, developing and improving technology that better fuels its online, digital and physical marketplaces to meet customers where they want to do business, providing them with smart, intuitive technology for a seamless customer experience. ADESA has 74 auctions throughout North America.
What are your strategic priorities as ADESA’s CIO?
As CIO, my biggest area of focus, opportunity and challenge is enabling the digital transformation of ADESA, KAR Global and the automotive remarketing industry. We are transforming the people, processes, tools, technologies and, most importantly, the culture of the KAR product development team. We’re leading an industry-wide transformation by implementing a Dev Ops culture and leveraging a hybrid cloud strategy to deliver industry-leading solutions with user-centric design concepts that enable a robust digital marketplace.
As CIO, how would you describe your management style?
Since joining ADESA nearly four years ago, I’ve implemented the Scaled Agile Framework (SAFe) and instilled a servant leadership management style across the KAR Product Development organization. Each of our scrum teams strives to deliver on our three primary metrics: Value, Velocity and Quality. This same approach was used to transform how our relationships with supporting business areas are managed. We quickly transitioned from a “staff augmentation” vendor management strategy to a partnership model. We have aligned accountability and authority. Now our partners have entire scrums teams working to meet their needs. These teams are held accountable in ways that allow ADESA to effectively measure performance relative to all other scrum teams. With this approach, we successfully track the quality and velocity of what’s being produced by all scrum teams across the enterprise.
Describe how ADESA has transformed its vehicle auction simulcast technology.
ADESA is leading the digital transformation of the in-lane buying experience. Nearly two years ago, we came to the realization that our current “simulcast” platform needed significant improvement and modernization. As a result, we kicked off an aggressive project to completely revolutionize ADESA Simulcast. We needed to leap frog over other industry offerings and provide a solution that offered the flexibility to create additional digital sales channels. This solution was one of the most complex projects undertaken by KAR Global during my tenure. It required complex integrations across multiple disparate legacy systems with multiple cloud-based solutions for the improvements needed to ensure extremely low latency (milliseconds) between in-lane bidders and on-line bidders. It also required a complete rewiring of all auction lanes in the 74 auctions across North America. In the end, the 18-month DMI-supported project was hugely successful. We completed the modernization one month ahead of schedule and under budget. We are extremely proud of our industry-leading technology.
Tell us why ADESA’s recent simulcast sale in Las Vegas was so innovative.
In September, we were thrilled to successfully pilot an ADESA Simulcast sale at Fiat Chrysler Automobile’s (FCA’s) national certified preowned vehicle dealer meeting. Vehicles were launched into auction from four ADESA auction locations — ADESA Golden Gate, ADESA Indianapolis, ADESA Kansas City and ADESA Las Vegas. Essentially, we brought the auction to more than 130 franchise dealers, empowering them to participate in a fast, live-bidding virtual auction. This format exposed dealers to a broader buyer base and also helped buyers cost-effectively access hard-to-find vehicle inventory. It was a win-win for all parties and helped introduce buyers to the next generation of vehicle auctions.
How would you characterize ADESA’s partnership with DMI?
DMI is one of our top providers of talent and an excellent partner in the consultant category. We’ve partnered with DMI at scale for two years and currently have about a half dozen fully-formed scrum teams. We’re pleased with the results and how the relationship is managed day-in and day-out. We have a very transparent relationship that works well. As a large organization, DMI has exceeded our expectations.
Artificial intelligence and machine learning (AI/ML) will move out of the shadows and into the mainstream in the 2020s.
AT DMI, we’re already seeing these forces at work in our engagements with enterprise clients. Increasingly, B2B companies are putting learning algorithms to work to streamline operations and develop predictive capability. Chatbots and other conversational AI technologies are getting more sophisticated, opening up new avenues for improving customer service. While these trends have transformative potential, they also pose thorny ethical questions that cannot be ignored.
Here’s a quick look at three of these factors.
AI/ML is moving into the B2B space in a big way. Retailers are using mobile apps, image recognition and robotic-process automation to streamline transactions and improve efficiencies in the storefront and the distribution center. As more consumers shop online but pick up their products in stores, retailers are turning to back-office AI to upgrade their supply chains and inventory controls to ensure these hybrid transactions don’t leave buyers empty-handed.
Intelligent bots also can track in-store traffic patterns to help retailers optimize their store layout and streamline service and checkout. In the automotive sector, back-office AI can help companies improve the driving experience and help dealers deliver offers to the customers most likely to want them. In the world of finance, AI is making it easier to develop more accurate assessments of credit risk and merger/acquisition potential.
Siri and Alexa were early chapters in the story of natural language processing. In the new decade, conversational AI will broaden its appeal in multiple sectors.
In healthcare, chatbots will increasingly know how to identify users and help them navigate to information they need right away. That can put patients in the driver’s seat — letting them decide whether to wait a half-hour to talk to a human or to read a few articles or support threads that solve their problems. Government agencies also will be keen to adopt these tools to bolster constituent services.
Companies like banks and consumer brokerages, meanwhile, will use more chatbots to help customers select investment vehicles, balance portfolios and map out their financial futures.
The accelerating pace of AI technologies creates vast potential but also must confront questions only human can answer.
Consider the possibility of an AI engine predicting the success or failure of a clinical trial. This raises a host of issues in the underlying modeling. How accurate is the data? How trustworthy are the recommendations? It’s no exaggeration to say these are life-or-death challenges.
AI is also enabling sophisticated data-tracking sensors that follow people’s actions and predict their behaviors. Should AI applications secure people’s consent before conducting these scans?
The problems of black-box AI — where users can’t be sure why a bot decides to act — require companies to develop traceability and clarity on the mechanisms driving AI bots. Failing to account for these kinds of challenges could be the one roadblock to the progress of AI adoption.
Moving Ahead with AI/ML
Though advanced automation has raised enthusiasm and unease in equal parts in recent years, inroads in the B2B sector reflect growing acceptance of these next-gen technologies.
At DMI, we’re seeing these trends across the major sectors we serve — automotive, financial, healthcare, government and retail. And we’re helping companies find the best way to adopt transformative algorithms while staying true to their values and their customers.
The coming decade will test everybody’s ability to cede a measure of control to machines while leaving ultimate authority in the hands of humans. Our experience with machine intelligence gives us the grounding to help clients find thoughtful, humane ways to strike that balance.
— Venkat Swaminathan, director, data analytics and artificial intelligence
— Niraj Patel, senior vice president, artificial intelligence
We don’t have to let Amazon write the story of retail disruption anymore.
Of course, Amazon’s Prime Day and delivery deals require retailers to adapt. But all retailers now have the potential to disrupt. The tools and tactics of retail disruption are well understood. Indeed, legacy retailers can be just as disruptive as VC-funded start-ups.
Disruption typically happens via three avenues:
To shake up their industries, retailers can take any or all of these routes. That will require a mindset shift that might not be so easy for retailers who have spent years focusing on other priorities.
Consider one of the most popular retail metrics: ROCI, or return on capital invested. Retailers tend to obsess over ROCI because it helps them assess the value of investing in new stores. But in the era of disruption, you might not need any new stores. Instead, you might invest in digital technologies that are not capital in the conventional sense.
Remember omni-channel? It was hot a couple years ago but already seems ready for retirement. It’s not that retailers won’t keep investing capital and selecting marketing channels. But they will have to adapt to an era where disruption is inevitable.
Getting the Right Perspective on Retail Disruption
Though platforms, crowds and machines are vehicles of disruption, they are not in the driver’s seat. As the author Thales S. Teixeira explained in a recent Harvard Business review article, customer dissatisfaction is the prime cause of disruption. Innovators identify gaps in customer satisfaction and launch services to close those gaps.
This concept gives retailers a straightforward question to ask: What are you doing across your entire value chain that has a positive impact on your customers? Keeping today’s customers happy is a short-term challenge — you also have to think about future customers.
You’ll need a framework to explore and adopt new retail technologies. And you’ll have to measure how these and many more factors affect your customers’ bond with your brand.
Retailers hoping to become disruptors have to remember the big picture. Disruption cannot be a quick fix. It has to be an engine of long-term growth, competitiveness and customer satisfaction.
At DMI, we’ve developed frameworks to help retailers evolve in an era of perpetual disruption. Our expert consultants and technologists can help you simplify your application portfolio and adapt your company culture to do more than keep the lights on.
With our help, you can take the lead and stay there.
— Varun Ganapathy, director, commercial/consumer: digital technology office
Picture yourself relaxing on the deck of a cruise ship, sipping your drink and enjoying the ocean breezes. When you need another drink, you call up the cruise line’s mobile app and order a refill. In a couple of minutes, a crew member brings a fresh drink right to you.
It can happen if the ship is wired for geospatial commerce to deliver customized services to the cruiser’s precise location. On a ship, geospatial commerce can leverage a wealth of crucial technologies:
Machine learning and other advanced algorithms to streamline operations and develop predictive capability.
Now, imagine you’re traveling on that cruise ship with your whole family: Location tracking could help you find where everybody is and send them a reminder to gather for dinner. The cruise line’s app could direct them to the deck and section where they need to be and tell how long the walk will take.
At dinner, you hear somebody at a table nearby singing the praises of the ziplining at the next port of call. Without leaving your table, you use your smartphone to sign your family up for the ziplining tour.
Multiply these activities by the thousands of people on the cruise ship and think of the benefits of collecting and analyzing the data passengers generate. Over time, services could be personalized to a degree that’s difficult to imagine today.
And it’s not just cruise lines. These next-generation technologies hold the potential to drive immense value across the hospitality industry, where individualized pampering can help companies and attractions sharpen their competitive edge. Theme parks, spas, resorts and family entertainment centers all can benefit from being able to track guests’ locations and deliver personalized mobile services.
At DMI, we’ve developed sophisticated technology strategies for these kinds of advanced retail services. Our consulting teams and technical experts can apply our Application Optimization Framework to simplify IT operations and encourage top-line growth. Our Innovation Hub for Retail helps companies strengthen their competitive standing and improve their company culture to embrace innovation and find ways to disrupt their industries.
Fortunately, these innovations do not require travelers to master intrusive, frustrating technologies. All they have to do is pick up their smartphone, tap on an app and start enjoying the fruits of geospatial commerce.
— Varun Ganapathy, director, commercial/consumer: digital technology office
Describe the Credit First National Association (CFNA) mission.
CFNA is proud to be a leader in customer-first payment solutions that earn loyalty and drive business in the communities we serve. We’re one of less than ten remaining special-purpose nationally chartered credit card banks in America. As the consumer credit division and payments arm of Bridgestone Americas, the CFNA payment program for tire services is offered at all 2,200 Bridgestone Retail Operations stores in the U.S. More than 5,500 Bridgestone affiliated dealers also accept the CFNA payment program.
How do you describe the disruption within the financial services world?
Today, everything in financial services is omnichannel. This includes how payment programs are presented, serviced and handled. If you’re not digital, you’re not anywhere. When I joined CFNA three years ago, we were just embarking on our digital transformation journey. We recognized that we needed to invest in enhancing our systems to grow our business and connect with customers where they are. DMI has been instrumental in enabling this effort.
How do you meet the changing needs of your customers?
Our vision is to create a customer experience that is on-demand and self-service. Customers today don’t want to pick up the phone and talk to a customer service agent to resolve an issue or obtain their statement. They want to do that online, and with ease. We’re also exploring developing an app to connect consumers to other products and services within the Bridgestone digital offering. We aspire to offer digital wallet services to securely store customer payment information so customers can purchase items online or with their phone.
As CFNA’s President, what are your business goals?
Our goal is to ensure we’re supporting Bridgestone’s vision to extend the brand. We’re doing this by working to make our payments program part of a loyalty program designed to grow our customer base and get consumers to shop preferentially with us because they know we can effectively help them take care of their vehicle. Consumers need payment options, and we want to be part of their wallet.
How is DMI delivering value to your organization?
As CFNA makes progress on its digital transformation journey, DMI is a strategic partner that has enabled us to transform our service offerings to better service our existing customers and grow our business. We are excited to continue working with DMI to further enhance our offerings and improve the customer service experience.
Agile can’t be measured. We hear that a lot from fans of waterfall development.
We respectfully disagree. It’s true that waterfall provides excellent metrics for benchmarks like spending against budget and progress along a timeline. But more often than not, waterfall development is too rigid to thrive amid today’s perpetual changes in markets and technologies.
That’s why DMI usually recommends an Agile approach to software development, which provides speed-to-value in ways that waterfall typically cannot deliver. We have to admit, however, that we have shared the frustrations of developers who craved useful data on Agile performance.
That’s why we developed APIX (Agile Performance IndeX), which offers the ability to quantify and score multiple benchmarks to help managers track the success of Agile projects. The numbers are a bit softer than the ones you get with waterfall projects. But they can be extremely effective when you apply them to a prioritized list of the things you want to measure the most.
We prioritized what we measure with the Agile index like this: value > quality > progress > productivity
Understanding these priorities — and putting them to work — requires a fundamental shift in perspective. Here’s a quick look at our thinking on these priorities:
Why value ranks first: Agile methodologies were developed to enable speed-to-value. You build a minimum viable product (MVP) as quickly as possible to start producing value — whether it’s revenue, market share, other business priorities or a combination of those things. Then you use short development iterations and frequent customer feedback to keep making the product better. Thus, any attempt to measure the performance of Agile projects must place the highest priority on building value.
Why quality ranks second: Quality represents your ability to deliver an MVP with the most critical functionality and the fewest bugs. Quality has to rank below value because you have to deliver an MVP within a reasonable time frame at a sensible cost. You also have to reduce the risks of failure or delays. High costs, long time frames and overlooked risks all erode value and the total cost of delay grows exponentially over time. Thus, when you quantify value first and measure quality in the context of your value metrics, these numbers help drive success in the next two categories — progress and productivity.
Why progress ranks third: Progress is among the easiest Agile metrics to quantify. Burndown charts, for example, provide an excellent illustration of how far along an Agile team is. Because Agile projects tend to be difficult to quantify otherwise, Agile team leaders tend to emphasize progress. You measure what you can see, after all. But troubles can arise if teams make excellent progress on projects that are not delivering value and full of bugs and hence unlikely to deliver speed-to-value. Thus, progress must support value and quality.
Why productivity ranks fourth: Productivity is among the most crucial measures of performance in any activity. The challenge in Agile projects is that measuring productivity can have unintended consequences. For instance, if you try to quantify the productivity of individual team members, you may miss their ability to help the entire team succeed. Productivity and progress can be interchangeable, depending on the needs of your organization and the skills of your team members. Regardless of your approach to these two metrics, you need to make sure they reflect their contributions to quality and value.
When DMI developed APIX, we acknowledged that metrics drive behaviors. People automatically adjust their priorities to meet numerical goals. Thus, we established our Agile index to prioritize the behaviors required for Agile success. We also built flexibility into our APIX parameters — we tweak them according to each client’s business requirements.
As we see it, progress and productivity are empty data points until they support quality and speed-to-value. In our experience, folding these numbers together in order of priority can deliver metrics that meet or exceed anything a waterfall project can deliver.
— Brian Andrzejewski, director of business transformation services
The evolution of artificial intelligence (AI) and machine learning (ML) is redefining the supply chain.
Until recently, digital technologies reduced repetitive tasks and eliminated waste at each link in the supply chain — clearing an obvious path to ROI. But supply chains aren’t so straightforward anymore. Yes, supply chains still move parts to factories and goods to consumers. But they also use data and advanced algorithms to anticipate future demand, correlate with supply challenges and adapt to emerging competitive threats.
That’s a whole new kind of supply chain.
AI/ML projects have to take these new realities into account to drive value and avoid wasteful missteps. Keeping these seven factors in mind will help you do that:
DMI: A Consulting Partner for AI in Supply Chains
Just knowing where to start an AI project can be confusing and frustrating. At DMI, we recommend small pilot projects you can scale and evolve quickly once you figure out what succeeds.
But how can you tell where to start in a large enterprise? The best route is to join forces with a consulting partner who has a proven track record and a strong reputation for success in your industry.
That’s how DMI drives ROI with AI/ML in the supply chain.
Our Agile methodologies deliver fast prototypes and accelerated time to value. Our deep focus on areas like edge computing, 5G, data science and AI/ML helps our clients deploy the right mix of talent and tools for their unique needs.
With supply chains moving in new and unexpected directions, you need that kind of expertise to succeed with AI/ML.
— Varun Ganapathy, director, commercial/consumer: digital technology office
Tell us about the Altec mission.
Altec has a 90-year history of providing truck-mounted equipment, such as aerial lifts, cranes, chippers, digger derricks, and cable handling equipment to the utility industry. Today, Altec provides products and services to more than 100 countries throughout the world. Since 1929, Altec has been a company committed to excellence. Our products are the industry leaders and consistently raise the bar through innovative design and integrated safety features.
How was Altec initially referred to DMI?
Initially, we were impressed by DMI’s status as a Gartner Magic Quadrant Leader in Managed Mobility Services, Global – four times running. Additionally, I learned later that DMI has been recognized by Gartner six times. We find that when industry analysts provide their stamp of approval, it goes a long way toward building credibility with a new partner.
Tell me about your work with DMI on Digital Transformation.
We wanted to develop a digital platform to deliver the next generation of products and services that would connect our customers to their equipment. Since DMI leads the market in mobility solutions and connected systems, DMI has been integral to realizing our objective. Today’s world is increasingly data-driven. Our customers are seeking metrics surrounding equipment health, safety and productivity. Together, Altec and DMI have implemented a platform that empowers us to respond to our customers’ requests and provide meaningful insights to inform sound business decision-making for our customers.
What is the next step in your transformation?
The ultimate vision is to create and maintain a digital twin of our physical products; resulting in a higher level of support, optimization and automation as Altec equipment progresses through its operating life. The pairing of the physical machine and virtual machine serves multiple purposes; from systems monitoring to technical support to data analytics to improving and planning future products using digital simulation. Altec had the vision and desire to create the foundation for connected products and services that can be further developed and scaled to meet the expanding needs of our customers. DMI understands how a digital twin can help drive innovation and performance.
What has the relationship with DMI been like?
The DMI team had exactly the sort of experience that we were looking for in a partner. This allowed us to jumpstart the program as we developed and expanded our own capabilities. DMI provided the right people with the right skills at the right time. Any project of this magnitude will encounter some technical issues and DMI has worked side-by-side with our team to overcome challenges while continuing to move toward the objective. Working together, the team is consistently bringing creative ideas to the table and delivering high-quality results – and this makes our working relationship truly enjoyable.
DMI is excited to announce our strategic partnership with Crayon Software to become a Microsoft Cloud Solution Provider (CSP) partner. From implementations and migrations to enhancing technology you already own, DMI is known for our strength in modernizing, developing and integrating enterprise strength applications and platforms. Now as a CSP partner, DMI will not only continue to support our clients with the best in class cloud solutions and services but also offer a more holistic experience that includes licensing, support and managed services all through one vendor.
As Microsoft continues to phase out the traditional Enterprise Agreements, Microsoft Cloud Agreements (MCA’s), and Server Cloud Enrollments (SCE’s), organizations are being challenged with how to most strategically and cost-effectively procure and manage their licensing. Through the CSP program, DMI can now offer our clients an agile, scalable buying model where they can scale up or down (not just up) based on their usage, pay monthly instead of being locked into long term commitments, and receive built in support, consolidated invoices and deep discounts.
As a Microsoft Gold partner for 15+ years, DMI is excited to expand our capabilities into in software licensing and additional services. A full suite of our ongoing Microsoft solutions and capabilities is featured on the DMI website.
— Michael Deittrick, senior vice president, strategy, chief digital officer