Traditionally, business leaders have depended upon ERP or BPM systems to automate and optimize business processes. Resulting in long implementation cycles, a number of complexities and variations that are unique to each business. Thus, slowing down the organizations value realization process. This is where Decision Engines come into play.
How does it work?
Enter digital age business leaders → input their need to be dynamic in supporting faster change cycles → push them to address gap areas and changing priorities → plug-in decision engines to recommend/automate sub-processes.
Real World Applications
A trucking company’s implementation of a Transportation Management System wasn’t managing truck-to-trailer allocations in the most efficient way, due to the inability to leverage its new IoT data sources. To assist with this issue, we built out a recommendation engine with Machine Learning, enabling the planners to make quicker decisions while reducing sub-optimal allocations.
A life insurance company’s implementation of their core application and process was not setup to leverage the new datasets and attributes created from capturing unstructured PDF form data. To support their applicant engagement strategy, we were able to build out a decision engine based on specific guidelines which would automatically trigger the appropriate tasks in their workflow.
What does this mean for you?
Data systems should be built out with the anticipation that supporting decision engines can optimize business processes and fill gaps. Technology is now available that will embed decision engines into databases and integration processes, along with the ability to support rule engines. It’s important that IT leaders continue to expand their knowledge and stay up to date with the technology evolution to ensure their business receives value in a timely manner by using data and machine learning algorithms.
While data awareness is pervasive, adoption is still a challenge. Having business analysts and process leaders become a part of the program, focusing on enabling them to make less decisions, more accurately. Making quicker decisions while minimizing errors is something everyone could get on board with.
Believe it or not, it’s not much extra work to identify gap areas in business processes. First, you must prioritize them based upon their value, analyzing and understanding the population to build out segments. Then, strategize and establish recommendations or automation guidelines, to build it into a decision algorithm and plug into the ERP or BPRM system or custom workflow apps.
From here, move on to the next one and repeat. Then, voila! Allowing you to reach your desired value faster.
Thiag Loganathan President, Data Solutions, IoT & Analytics Unit