In a lecture at Stanford, I grew quite interested in the topic of business innovation. Roger Martin’s book “The Design of Business” was featured as a great theory defining the mechanism at play in the process of designing strategies. The key here for me was to take off my usual Decision Management glasses and embrace a different perspective on the very same topic of growing a competitive advantage.
When you think about it, the evolution from Mystery to Heuristics to Algorithms defined in the Knowledge Funnel resembles the Decision Management discipline in a somewhat different order. A fresh new take on concepts we know quite intimately is always intellectually exciting.
If you allow my over simplification of the core concept here, Roger Martin in his book describes an evolution of understanding of the business:
The level of sophistication of the strategy greatly depends on the level of understanding of the problem and the mechanisms governing the business. This sounds like a no-brainer but as highlighted very appropriately this is not really how the market always operates. Although a Heuristic leading to great growth may sound intuitively good, the public market only values the predictability of Algorithms — being able to anticipate to the penny a company earnings is what matters. This is mind-boggling though since Innovation comes from the exploration of Mysteries and a first-mover advantage in that space might create a major disruption of the market. This is an interesting conundrum, isn’t it?
Granted, Decision Management discipline often addresses the problem in a slightly different way. The purpose of such an implementation is to automate part of the business rules. So the Mystery phase is often only looked at as part of the requirement gathering phase. In many projects the starting point is a known problem though. The Heuristic ends up being a partial implementation aiming at reducing the level of manual processing so that skilled personnel can focus on those “difficult” cases. A true Algorithm implementation would like involve predictive models and a fair amount of testing and/or simulation. Another way or looking at it might be to say that BRMS technology is typically applied to Algorithm-type of problems. If we know how to make decisions, BPM and BRMS technologies can be deployed to implement such algorithms.
I expect that going forward disciplines or approaches such as Pattern Based Strategies as described by Gartner might change somehow the way we apply Decision Management technologies. Clearly, there are a number of problems that are in the Quest category (we know the desired outcome but not necessarily the way to get there) where Decision Management technologies could be leveraged. The current methodologies and possibly technologies do not yet lend themselves to this usage but I sincerely believe that the need will create the opportunity here. Gartner is on the right track if you ask me.
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