I am at Decision Camp today and Carole-Ann Matignon of Sparkling Logic kicked off the event talking about Decision Management. Carole-Ann and I have a lot of shared background in Decision Management so don’t expect any major disagreements…
As readers of this blog know, Decision Management is an approach to automating and managing operational decisions. This can be for real-time or batch environments focused on increasing profitability, quality or revenue while decreasing inconsistencies, TCO and time to production. Decision Management, she says (and I agree) is a cross-industry approach with strong use cases in every industry.
- Relies on business logic to describe how to make these decisions. This might come from policies, regulations or expertise.
The original format of most business logic is hard to manage so we replace these sources with the equivalent business rules and then manage those business rules to keep them current and accurate.
- There is also insight hidden in the data a company has that can be used to improve decision-making
This insight gets extracted using analytics, especially data mining and predictive analytics, so it too can be applied
But everything is becoming BIG – Big Data being the most obvious trend. The value of Big Data is that it makes more kinds of analytics possible such as analyzing a social network to see how that can be used to influence decisions. Social networks might show fraud rings or people like you for marketing purposes. New uses of Big Data in Decision Management show up all the time – in fact I believe (like Carole-Ann) that the best use case for Big Data is Decision Management and real-time operational decision-making (see this series of blog posts for instance)
Carole-Ann also sees “Big Knowledge” emerging more and more too. Sharing and coordinating knowledge around the globe in areas like fraud detection or medicine in a way that can be operationalized has tremendous potential. This too can result in better, more accurate and effective decisions.
Next up, my co-author on Smart (Enough) Systems, Neil Raden.