I was reading an article on The top 10 CIO concerns and I was struck by the first four:
- Business productivity and cost reduction
- IT and business alignment
- Business agility and speed to market
- Business process re-engineering
It seemed to me, reading this list, that all four of these were concerns that could be addressed by the use of decision management.
- Applying decision management allows more decisions to be automated. This improves business productivity by allowing those who used to spend their time making operational decisions to spend that time, instead, on higher-value tasks. Instead, for instance, of rubber-stamping every policy that comes in they can spend their time on the tricky ones. Automated decision-making saves time and money over manual processes both in terms of staff time and often in terms of fees for data - automated systems regularly show a return by only paying for external data or inspections when they will make a difference.
- Business rules, a core technology for decision management, is ideal for bringing business and IT staff together to collaborate on the behavior of their system. Dramatically reducing the number of degrees of separation between developers and business people, a business rules driven approach helps drive business alignment.
- The same approach and technology dramatically improves agility.With business users able to make changes directly and effective, declarative technology to implement business logic companies can have systems that are easy to change and intensely agile.
- The power of decisioning to make processes simpler, smarter and more agile is real. Companies that adopt decision management in parallel with process management develop processes that are more streamlined, easier to evolve and more optimized. If you want to re-engineer a process, integrate decisioning.
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interesting information
James speaks about these issues better than just about anyone I know. He's being a bit modest. He's Chair of the Enterprise Decision Management Summit the first week of November in Las Vegas (Bellagio), which very specifically covers these four issues. Good stuff, James!
While I would agree that applying decision management is an obvious gap and that improving decision lifecycle management has significant benefits, a business rules engine is not nearly enough. What is needed instead is a means to model manage and measure the impact of a decision on desired business outcomes, and to do so not in a silo of a process but in the context of a business activities, a variety of changing market conditions and business scenarios. The notion of making decsions based on either historical data or using predictive analytics or rules engines is contrary to becoming agile. Agile implies proactive so these days decision making is not about playing "what if", it's about playing "then what". Enabling a decision maker to measure the value of a decision criterion against other criteria and make the appropriate trade-offs in advance of a market condition creates the still elusive agility companies seek. Further trade-off management enables organizations to mitigate risk and lower cost in decision making, while speeding time to decision and therefore time to value.
Automating a decision using a rules engine does not allow an organization to make more informed decisions because the rules are not conditional upon non-included variables - and even if they are, then the exception becomes the norm and
norm the exception.
Lastly to the point on policy, too often its the squeaky wheel that gets the oil. In many cases decisions are based on satisfying one stakeholder group when in fact the agenda touted by that group may be a quick win with long term ramifictions that do more to hinder than to help drive the revenue growth or improved effectiveness the organization desires.