Trusting and using Actionable BI

Actionable BI

At a recent conference, I had an opportunity to interact with a lot of clients and I realized there is a lot ambiguity and confusion about Actionable BI. While there is a lot of demand and appetite for it, there is a lack of clarity on the subject… So I thought of exploring Actionable BI through a series of blogs to share my thoughts on it. Here is the first post in the series that will first introduce what is Actionable BI for you. In the next three posts, I’ll attempt to discuss:

• How to achieve Actionable BI
• How do we make data for Actionable BI trustworthy?
• Role of AI in making data for Actionable BI Trustworthy

Organizations spend millions of dollars on producing thousands of BI reports that may provide operational or historical data to show past trends and spikes. But business users need to do a lot of investigations through drill downs and additional reports or queries to make them actionable.

Difference between BI and Actionable BI
Techopedia defines actionable data or insight as “information that can be acted upon or information that gives enough insight into the future that the actions that should be taken become clear for decision-makers.” So while Business intelligence (BI), is often described as “the transformation of data into relevant and useful information for the purpose of business analysis” the term Actionable Intelligence is defined as “information that can be acted upon, with the further implication that actions should be taken.”

Characteristics of Actionable BI

1. Drillable and On Demand – It should be available when you need it at the point of interaction with customers, partners and other stakeholders in the complex supply chain and ecosystem so that business users don’t have to go to a separate report or dashboard. It should also be easy to drill down to the level where the BU report not only highlights the area that needs attention but take you down to the level so that you know exactly which customer or supplier you need to call and why.
2. Contextual – It should know the context in which you need the information e.eg if you are making a decision about an ordering a part from a supplier, it should know suppliers’ past performance about delivering the part in terms of quality, timeliness. It should align that with demand for the part and tell you if the part is likely to arrive on time.
3. Integrated with business process – Actionable BI is really effective when business users don’t have to jump through hoops to get to it. If it is integrated with the application or business process so that it can provide contextual business intelligence on demand. In the above example, if BI about the supplier performance is integrated with the procurement system, users will have the intelligence available without having to log into another BI system.
4. Smart Alerts – Smart Alerts allow users to receive critical business information in the quickest and most efficient possible way. For example, a store manager can be automatically informed when in-stock levels of critical items fall below or rise above a certain level.
5. Augmented Intelligence – Augmented Intelligence can analyze huge amounts of data generated from machines, GPS devices, and other IoT sensors to glean insights and provide human experts to take appropriate actions
6. Constant Feedback Loop – For the system to provide accurate and reliable intelligence for effective decision making, BI systems need to stay up to date through constant feedback loop based on the results of the actions taken based on the intelligence provided. I designed a system for an aircraft engine repair company that allowed them to recommend specific actions to optimize the cost to repair the engines. Shop floor technicians would track the recommended actions and provide feedback to the system on the new estimated cost to repair the engine.