Stephen Hendrick, Group VP at IDC, delivers a talk on Decision Management. You may be well acquainted with Stephen, who, among other responsibilities, covers the BRMS and Decision Management spaces for his organization.’
Stephen started his talk with a statement that we’ve been doing event-based decision management for all our life as a species: reaction to events, adaptation to new states, flexibility and evolution being rewarded. His formal definition is ‘the application of technology to manage the processes that solve the decision problems presented by the intelligent economy” (liberal and approximative quote). The key shift Stephen sees is the transformation of the information economy to the intelligent economy characterized by
- ubiquitous data tracking
- networked interaction
- pervasive analytics
- real time interactions
- system to person interactions
- social collaboration and flattening of the enterprise
Of course, this translates (in the way I position it) by the exponential growth of accessible and relevant mostly unstructured business data, and the exponential rate growth of accessible and relevant ever shifting business events. The two trends we discussed with Charles Forgy and Carole-Ann at RulesFest 2011 last week.
This trend both enables better decision management – as Stephen’s states – and challenges most current approaches.
Stephen listed what he considers are the key components of a decision management solution. All typical components are in there, but with a particular emphasis on the social and collaborative aspects to support the management work, as well as on the tracking of business performance to ensure that you don’t just manage decisions as they are, but that you also enable their evolution and optimization.
He made the distinction between
decisions, and the different activities involved in the corresponding processes – leading to a categorization of the various types of products and approaches that support them.
Stephen presented an updated IDC Decision Management Model (reference to it here). This model is rooted on work Stephen has been doing over the years. One key challenge Stephen insisted on is the fact that there is no unified Decision Management solution that covers strategic, operational and tactical decisions. Only point solutions exist – and Stephen highlighted how little known some of the tools that address strategic decision management. Many of those have less than 100 customers.
This is an interesting point. In simpler or better known areas such as Business Intelligence similar segmentations do exist. A key question is what the root cause is. It may well be that the nature of the problem is different enough to warrant different solutions – and that the real solution is to have good exchange and traceability between these levels rather than unified approaches.
Stephen went through an additional categorization of the activities involved in decision management
- identity and initiate
- analyze and decide
- act and evaluate
- measure and archive
with a central place to “state change”.
Stephen provided his outlook on the market’s growth potential, which he sees as bright:
- Project-based DM (strategic) – 2009-2014 CAGR 13.2%, at ~$2.7B in 2011
- Tx-based DM (tactical) – 2009-2014 CAGR 17.5%, at ~$4B in 2011
I am not 100% clear on exactly what products & platforms are included in each section, but combined, we are talking in excess of $6B and a significant growth. It represents around 3% of the overall spend on application and tools. It’s always difficult to figure out the real market share for Decision Management – but the order of magnitude is realistic.
Stephen later went into a catalogue of various decisioning technologies, including rules and various statistical, analytic, optimization and collaborative technologies. One interesting point is that he places Business Rules on the opposite extreme to Adaptive Systems when classified along the lines of decision granularity, uncertainty, complexity and flexibility. Interestingly enough, Carole-Ann and I have a patent (pending) on rules-driven adaptive models – providing a solution to the vexing problem of how to manage the learning process in adaptive analytics.
As a note, part of Stephen’s categorization approach is based on the Cynefin framework – also used by our friends at IBM.
Stephen later went into a categorization of the collaborative decisioning dimensionality, something I had not seen Stephen address before. He made the distinction between various roles: leader, critic, BFF, advisor, friend, etc, and how their various input may be managed – scored, weighed, etc. In his perspective, a lot of the complexity in managing the collaborative process comes from the modality of the decision making (from autocratic to consensus) and the type of decision process (from single-pass to delphi and iterative).
His conclusion captured the key guidance
- if you cannot measure, you cannot manage your decisions
- all decision management activities need to be supported
- feedback-driven decision optimization is key
- the tools to do decision management are mostly here
- making strategic and operational decisions relevant to tactical decisions is complex, and still needs work in terms of achieving consistency and normalization.
To the question on “what will the DM vendors focus on in the next few years”, Stephen’s response was:
- sensor response processing (data and event driven decisions)
- platforms coming together combining technologies addressing multiple aspects of decision management for the intelligent economy