Do you ever have the feeling that running your business is rather like being on the prow of an ocean liner at full speed in a squall? You may have a feeling of progress, your engine-room may be generating considerable power, but ultimately: your route to the destination is not clearly visible, you cannot discern if the ship is tracking the right course towards that destination and you know that it would be difficult to change course quickly to avoid an obstacle if the need arose. Better, perhaps, to be in the bridge of a fully-equipped motorboat where you have charts that clearly define your destination and your route to it, a GPS which shows you how you are tracking that route and the ability to change course quickly and take advantage of ever changing prevailing circumstances.
To control a business effectively you need:
- To have an cogent strategy (a route to a specific destination),
- To understand how well you are currently pursuing this course (performance measurement)
- To grasp precisely why this is the case (transparency) and
- the ability to change it quickly if it proves to be ineffective (agility).
Decision Management (DM) is a technique and a discipline that provides the latter three capabilities: transparency, agility and performance measurement.
DM supports transparency by allowing you to gain a rich and precise understanding of your (current) operational business decisions – the small high volume choices your business makes every day when dealing with clients: should I loan money to this client? What should the upper limit for the loan be? How much collateral is required? What should I charge a client for this service? This understanding is achieved through modelling your business logic, either from scratch, or using an existing implementation as a start point.
Much as a data architect might use data modelling to understand and improve how data is sourced, used and generated by an enterprise, a decision architect uses Decision Modelling to capture and enhance the effectiveness and integrity of business logic. Logic can be modelled using a mixture of simple decision tables and complex analytics. The process of capture makes business logic explicit and visible for all to see. The crucial consequences of this process are:
- that your business logic is liberated from IT infrastructure and implementation detail (or the heads of individual experts) and, instead, expressed plainly in business terms so that it can be reviewed, critiqued and improved by subject matter experts;
- your business logic is simplified by normalization (rather like data is normalized when expressed in third normal form) making it even easier to understand and more self-consistent;
- the dependencies between different aspects of your business decisions are explicitly articulated: you can now understand how each policy impacts others and check their internal consistency; and
- Modelling prevents loss of knowledge by staff attrition and ad-hoc documentation.
Once you have a thorough understanding of your business logic and policies, DM supports agility through automation and governance. When these decisions are automated and their inter-dependencies are understood, they can be controlled more directly (by subject matter experts) and changed much more quickly and accurately. The usual ‘ceremony’ of release can be greatly streamlined. As automation provides the speed, DM’s strong governance process provides the safety by ensuring that all decision modifications are reviewed, authorized and their impact is as well understood as is possible ahead of release. Simulation is used to articulate the full impact of proposed policy changes before any commitment is made. Traceability ensures that the detailed rationale of all automated outcomes can be ‘explained’ by the automated system and used to define changes. DM provides the framework that maximizes the effectiveness of simulations and traceability.
Providing your business decisions are defined within the context of a business process, you can use DM to support a programme of continuous performance measurement and improvement. Defining metrics for your process enables you to continuously measure how effective your decisions are and highlights opportunities for change. Defining a business process to utilize your business decisions also highlights opportunities for reuse of decisions – promoting greater consistency across the process itself and amortizing implementation effort.
Better than Business Rules
It may be that you have heard of, or use, business rules to achieve some of these goals. By making a direct link to business goals and being explicit about dependencies, Decision Management goes one step further and is demonstrably more enterprise scalable and effective that a Business Rule only approach.
The Proof of the Pudding
The real benefits of DM can best be appreciated by practical examples. DM is used today by retail and investment banks, insurers, brokers to:
- Target cross selling of their products
- Price products and assess risk
- Dispatch their KYC and customer eligibility checks
- Guide user interaction with their channels (e.g., intelligent web site navigation)
- Implement channel routing and constraint enforcement
- Ensure (and prove) their compliance to industry regulations (e.g., capital/collateral adequacy, Basel III, withholding tax, volatility buffering)
- Detect and handle fraud
DM is effective in any scenario that involves the need to understand, manage and change non-trivial business logic for competitive advantage.
If you are interested in the benefits of DM and would like to understand them better in the context of a detailed case study please contact us to arrange a review.