The need for a new decision architecture as a basis for enterprise decision management.


Decisions are made at every level of the business and both within standard business processes and on an ad-hoc basis. Each option available a decision has an inherent risk and benefit to the organisation’s value/objectives/results.  The risk or benefit is the outcome of the choice made whether the decision was right or wrong.

However, very rarely does anyone actually understand all the decisions being made in an organisation. Decisions are often left out of architectures and form a minor part of process maps. It follows that the aggregate risk/benefit of getting each decision right or wrong is often unknown at a management level. So how can we improve the quality of our decision-making processes to improve the aggregate benefit to the organisation?

We need to know the impact of decisions already made in order to predict whether each choice will be the right one. We need to know what decisions are being made, how often they are made and whether they are part of a structured process or ad-hoc. For each decision, we must know the choices available and the likely risk and benefit of the choice, in the case of the decision being ‘right’ or ‘wrong’. We need to provide appropriate and accurate information to the player making the decision and track the results of the decision based on the possible choices and the information. We need to know the assumptions used as the basis for the decision so that we can manage the feedback loop and improve the risk/benefit of the choices next time.

The old ‘decision architecture’ that provided the basis for ‘decision support systems’ focused mainly on strategic, executive level decisions. An enterprise decision management approach would segment all enterprise decisions as required, one set of segmentation criteria being the level of automation possible and another being the value at risk/benefit of getting it right or wrong. Behind this is the level of judgement required. The new decision architecture will address, within an enterprise architecture approach, the elements that we discussed in the paragraph above:

  • Decision catalogue
  • Fit with (or outside of) business processes
  • Repeatability of decisions
  • Typical choices for each decision
  • Implicitness or explicitness of the decision
  • Likely impact (risk/benefit) of making each choice
  • Aggregation into decision yield
  • Information requirements
  • Inherent assumptions (and whether these are decisions themselves)
  • Feedback loops

In my next posts I will discuss (and evolve) these thoughts in more depth.


One Response to “The need for a new decision architecture as a basis for enterprise decision management.”

  1. Hi Nathan, I think that you are on to a winner here. The meta conversation that you seem to be raising is that of a methodology for decision analysis, design, and implementation (aka decisioning). You highlight some analysis and design considerations, to which I would like to suggest some more:
    • Would automation of the decision allow construction of a zero touch process? Transforming a high touch process into a zero touch process represents orders of magnitude improvement in timing and cost. Also:
    – Could the new zero touch process allow development of new frontline products and customer touch points?
    -Could the zero touch process allow automation of data acquisition, thereby allowing direct integration with third party systems and wholesale process re-engineering?
    • Does the decisioning implement any aspect of corporate policy? Policy is a statement of corporate intent that is implemented through decisioning. By building the decisioning against the policy, both can be validated and strengthened – that is, the decisioning is an active component of strategy development.
    • Does the decisioning change the state of any artifact that is represented on the balance sheet, whether directly or indirectly. If so, it is a critical part of the organization’s value proposition. Tracing the value changes represented by decisioning provides the backbone for additional analysis:
    – It helps complete the strategic picture.
    – The confirmed existence of the artifacts, and the data implied by the decisioning, provides a basis for database design.
    – The value change must be event driven, leading to event analysis.
    – And finally, decisions representing value change must be implemented by processes that respond to events, which acquire and create data, and which implement corporate policy.

    Ultimately the decision analysis is the analysis core that binds strategy to systems. If you are interested in more on this topic, you might also have a look at this paper

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