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Decision Management and Analytics 3.0


Syndicated from my blog on the International Institute for Analytics Site

IIA is talking about analytics entering a new era, Analytics 3.0, The Era of Impact. What is Analytics 3.0?

According to IIA, Analytics 3.0 marks the stage of maturity where leading organizations realize measurable business impact from the combination of traditional analytics and big data. High-performing companies will embed analytics directly in decision and operational processes, and take advantage of machine-learning and other technologies to generate insights in the “millions per second” rather than an “insight a week or month.”

Tom Davenport, IIA Director of Research, goes on to describes some interesting characteristics of Analytics 3.0, here are just a few:

  • Faster technologies, such as in-database and in-memory analytics, are being coupled with “agile” analytical methods and machine learning techniques that produce insights at a much faster rate
  • Many analytical models are being embedded into operational and decision processes, dramatically increasing their speed and impact
  • Tools that support particular decisions are being pushed to the point of decision-making in highly targeted and mobile “analytical apps”

Given this definition of Analytics 3.0, what is the role of Decision Management and of Decision Management Systems?

First I should re-iterate what Decision Management and Decision Management Systems mean:

  • Decision Management is a proven approach for automating and improving high volume, operational decisions. Growing out of work in retail credit over 20 years ago, Decision Management has become an established way to describe how to apply predictive analytics in day to day operations.
  • Decision Management Systems are the result of applying Decision Management, combining predictive analytics and business rules into systems that make decisions. In contrast to typical information systems, Decision Management Systems focus on making decisions rather than workflow processing or managing data. They are built to be agile, because decision-making is high change; analytic, so they can make use of data to make better decisions; and adaptive so they can learn and improve over time.

For organizations planning for Analytics 3.0, Decision Management has much to offer:

  • With its focus on embedding analytics directly into operational processes, Analytics 3.0 requires an approach that focuses on day to day operational decisions (as Decision Management does). Analytics 3.0 organizations are going to find they need their systems to become partners in decision making in new ways  and will have to balance building Decision Support Systems –  focused on helping a person make decisions, with Decision Management Systems – focused on making decisions more automatically.
  • Analytics 3.0 delivers more analytic models, built more quickly, delivering insight more rapidly. A real-time focus is inevitable with Analytics 3.0 and that means embedding analytics into Decision Management Systems is becoming more critical. Humans are not good at real-time. While visualization and presentation technologies take time to absorb and use, executable predictive analytic models can be scored and used in real-time by Decision Management Systems.
  • Analytics 3.0 focuses on turning insight into impact, even to the point where tools, including mobile applications, are pushing decisions and not just data. It’s often more practical to drive recommendations to this point, by embedding analytic insight into Decision Management Systems, than to push the decision-making down to the user of these devices. With a limited form factor and more mobility, the mobile user wants recommendations – not reporting.

Analytics 3.0 organizations will find themselves building out what they need for Decision Management. To deliver the integration and operational focus required they will bring business, analytics and IT organizations together more closely than ever (what I call the three legged stool). To deliver the increased analytic insight they need they will industrialize their analytic development processes. To embed analytics into operational processes they will identify and understand the decision points within those processes. Decision Management, and a focus on Decision Management Systems, will pull these threads together and maximize the value of Analytics 3.0.

As described in my book, Decision Management Solutions, the key to the intersection of analytics and Decision Management is a three step process:

  1. Decision Discovery: Identify, describe and model the decisions that matter to your business. Make sure you understand the decisions you are applying analytics to, and how they contribute to your business. Begin with the decision in mind.
  2. Decision Services: Build coherent, independent decision services to make decisions. These can be plugged into business processes or enterprise applications, be delivered in the cloud and turn your predictive analytic models into accurate, real-time decisions.
  3. Decision Analysis: Implement decision traceability and logging, map decision performance to business performance. Use analysis of decision performance to drive continuous improvement – don’t rest on your laurels when the first version is done. The power of analytics grows the more you use it to improve.

Decision Management, I believe, will help maximize the value of Analytics 3.0. And as a result, as IIA says, Analytics truly becomes the competitive differentiator for enterprises who capitalize on the possibilities of this new era.

If your company is interested in becoming a member of IIA, check out the  iianalytics.com website or email sales@iianalytics.com


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