A Decision Intelligence Platform will Empower Organizations to Model, Execute, and Deploy Semi and Fully Automated Decisions of All Kinds.
Decision automation is a very hot topic, especially with the emergence of different techniques and technologies helping AI to be adopted in organizations across any industry easily. However, 85% of AI projects fail to meet business objectives, in fact, less than 10% of AI pilot projects will be productionized. Organizations are spending more than 37.5 billion on AI projects by 2019; this translates to an investment of more than 33.7 billion dollars without bringing in any business value whatsoever!
These reports and numbers show the gap between business expectations from their investment in AI and their expected ROI from their AI-driven, in particular decision automation projects.
The goal of a decision intelligence platform is to close this gap by providing a unified, extensible platform covering all the requirements of decision automation involving traditional and advanced techniques to support full and semi-automated decisions.
In order to have a true decision intelligence platform that provides the next level of intelligent automation, the platform should enable organizations to apply decision automation in many different levels and a wide range of use-cases.
To empower organizations for all possible decisioning situations i.e from semi-automated to fully automated for both probabilistic and deterministic use-cases, the decision intelligence platform must combine the process automation, business rules, data & analytics, robotics, and machine learning technologies and allow human intervention when required for both stateless and stateful decision-making processes.
No matter, what technology to be used to the automation of business decisions, the very important part of any step is understanding how the new and existing operational decisions are working and how they impact the business operations. Therefore, it is very critical to ensure, operational decisions and decision modeling is considered as part of the decision intelligence platform.
Modeling, understanding, and automating business rules is a must when we consider a decision intelligence platform. Business rules are a vital part of organizations and to provide a successful solution in decision automation there will need to be part of the decision automation projects. They are not only about laws and regulations but are in corporate internal and external policies as well.
Data and Analytics
When we look at data and analytics, many people think of dashboards and gages and graphical user interfaces, that is very essential to communicate and display insights. But data and analytics are more than just dashboards when it comes to decision intelligence platforms. It is a capability to collect, receive, and connect to different data sources, and share the required structure from the raw data for decision making.
Machine learning enables us to learn from data, identify patterns and predict, forecast, and categorize cases with a certain accuracy. Therefore, the ML is a very important part of decision automation and decision intelligence platform. It also enables organizations to change the problem of probabilistic scenarios to more deterministic cases with the power of business rules mining.
Part of the decision automation will require interaction with systems, going through applications, forms, and accessing data inside the core organization’s existing solutions and processes. This requirement will generally introduce human manual touchpoints in decision automation. Decision robotics will address this challenge by automating the manual touchpoints as part of the overall solution.
Business processes will orchestrate everything around the decision automation, manage the states of different components, and enable human intervention as part of the decision intelligence platform. Orchestration is a critical part of the decision intelligence platform as it will glue all the components together and integrate the solution successfully to organizations.
So far what we have discussed from the decision intelligence platform point of view was about technology and tooling, but that’s not enough. Because decision intelligence platform is going to combine multiple mindsets and techniques to deliver the business value, therefore, a methodology on what to make, how to make, and how to deliver is as important as the tooling. Hence the platform is about decision automation therefore, the decision-centric approach will be the guideline for delivering the business value using the technology.
And finally, it is critical to understand neither of these is important if the solution cannot deliver the real business value. If the solution does not change organizational behavior and has less or no impact on the business operation, then, it becomes the question of why are we doing this in the first place?
Last updated December 14th, 2022 at 11:02 am, Published September 17th, 2020 at 11:02 am
CEO and the founder of FlexRule – He is an expert in architecture, design, and implementation of operational decisions, business rules, and process automation. Created Decision-Centric Approach, a methodology that brings People, Data, Rules, and Processes together to automate operational business decisions.
This approach is recognized by Gartner as the missing link to provide business value to organizations.