Market Highlights Q1 2014
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Decision Management SolutionsDecision Management Market Highlights Q1 2014

There have been interesting developments in the Decision Management market this quarter. In particular the focus is clearly shifting from Decision Management simply as a better way to manage business rules to one where analytics, especially predictive analytics, is central. 

This quarter there are three things I want to highlight:
  • New Gartner MQs
  • Innovation in advanced analytics
  • Expansion of the Decision Management value proposition

New Gartner MQs Reflect Changing Market Dynamics

Gartner released the new Magic Quadrants around analytics this quarter. First was the updated "Magic Quadrant for BI and Analytics Platform" (Gartner Feb 2014). For this MQ Gartner dropped predictive and prescriptive analytics from the main BI/Analytics report – moving those to a separate MQ - and focused instead on whether the BI/Analytics platforms could let users consume embedded PMML or other models built elsewhere.

This is a great development – the best way to make predictive analytics pervasive has always been to make it easy to consume predictive analytic models throughout an organization’s operational environment. This, of course, is one of the key ways in which Decision Management drives success with predictive analytics. Having Gartner acknowledge this and move away from the implicit “business people have to be able to build predictive models” of the previous MQ should be a strong driver for Decision Management when it comes to embedding advanced analytics in operational systems.

Gartner also identified a gap in the market around what they call "governed data discovery" platforms. These address both business users' need for ease of use and Enterprise IT-driven requirements (for governance, admin, scalability, etc). This too is an opportunity for Decision Management, specifically for Decision Modeling. The kinds of decisions that these business users need a governed data discovery platform for are repeatable, largely operational decisions. Decision Management shines in helping manage these decisions and our experience with Decision Modeling demonstrates that modeling these decisions improves the ability to effectively apply analytics while providing a common notation and vocabulary for IT, analytic and business people to share.

The new Magic Quadrant report on Advanced Analytics focused on tools for the "analysis of data using sophisticated quantitative methods to produce insights that traditional BI approaches such as query and reporting are unlikely to discover". Gartner sees this as a $2B market and considers new entrants and new approaches to be disruptive to what was until recently a fairly stable market for predictive analytic workbenches.

The net effect of this innovation and change is that analytic vendors need to be thinking about an integrated portfolio of capabilities. As Gartner begins to write about Decision Management more (see below) we expect that the growing emphasis on deployment and platform management will expand to include integration with business rules and Decision Management platforms.

Expansion of Innovative Approaches to Advanced Analytics

We are also seeing more and more innovative approaches to advanced analytics. In particular we see:
  • New entrants adding predictive analytics by embedding R, leveraging the huge growth in the popularity of the R language (for more, see our recent report on Standards in Predictive Analytics).
  • Some of these new entrants are delivering predictive analytic capabilities that are Hadoop-centric rather than traditional data–centric. While many platforms support traditional and “big data”, this focus on Hadoop first is becoming interesting (Hadoop is also covered in our standards paper).
  • In-database and in-memory analytic approaches are radically disrupting both the performance characteristics of predictive analytics and their deploy-ability (see our recent paper on In-Database Analytics for instance).
  • Cloud-based solutions are becoming more common even as existing products support cloud deployment more extensively. Having cloud-friendly tools as part of your predictive analytics portfolio is becoming critical (as witness the recent purchase of Infocentricity by FICO on the heels of last year’s acquisition of KXEN by SAP).
  • Machine learning is back with a vengeance. More and more we are hearing from and about analytic companies that focus on machine learning algorithms rather than on supporting analytic modelers and data scientists.
This explosion of new approaches and capabilities is going to make differentiation on the basis only of model building harder for analytic vendors and we expect therefore to see more value in emphasizing deployment and integration capabilities, as well as support for ongoing model management and other Decision Management elements.

Meanwhile we continue to see outsiders acquire predictive analytic capabilities with Dell acquiring Statsoft, an analytic company who has been adding business rules and decision management capabilities in recent years. We expect to see more of this as predictive analytics becomes critical to any software portfolio.

Decision Management Value Proposition Expands

Decision Management is becoming an increasingly mainstream value proposition. Every major business rules management system vendor is using it as positioning as well as an increasing number of analytic tool vendors. Gartner recently issued a Decision Management Report, "Find the Best Approach to Decision Management," that was an excellent summary (blogged about here) of the potential for Decision Management. My key takeaways were that Gartner “gets” the value of Decision Management and has a nice clean separation between Decision Management and Decision Support. They also see the potential, as I do, of decision modeling especially given the range of technologies involved in a strong Decision Management platform. Look for more on decision modeling from Gartner soon.

As part of the longer term growth of Decision Management we have seen important progress on standards. The OMG Board of Directors has adopted the Decision Model and Notation submission, putting decision modeling on a solid footing. This provides a critical platform for decision management requirements and should drive new tooling and capabilities across the board. Our consulting suggests that the decision models are good for Decision Management AND Decision Support requirements as well as for driving decision-centric requirements for predictive analytic projects. Expect to see more on this in the coming months. 

Decision Management Solutions Research Update

We continue with our focus of responding in real-time and operationalizing analytics with decision management. We recently completed a sponsored paper and webinar on Real Time Responses. We will kick off shortly research on how decision management builds better mobile applications, where limited real estate makes the value proposition of delivering actionable insights. not just data, even more compelling. Also look for Version 5 of our widely read Decision Management Systems Platform Technologies Report in early April.

Our research plans include:
  • Data Platforms for the Real-Time Enterprise
    The explosion of new data platforms for Big Data leads to a natural question about their support for real-time enterprises. A preliminary assessment is planned.
  • Decision Modeling for Governed Data Discovery
    The role of decision modeling in addressing ease of use and IT requirements for data discovery design and implementation, independent of the balance of decision support versus decision automation.
As always we are interested in the areas of the Decision Management market that interest you so please reach out with your questions and ideas.

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