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Why Decision Modelling? (In 1000 Words)

Blog: Lux Magi – Decision Management for Finance Blog

In a recent article we explained why any organisation that makes business decisions needs decision management, what it is and how it helps them become more effective.

Decision Management is a means of explicitly identifying your business’s operational decisions—much as you would any other vital business asset (like data or process)— so that you can describe, share, change manage and monitor their performance to see how they are contributing towards the goals of your enterprise. Decision Modelling focuses on representing decisions in a precise, standardized way.

Through Decision Modelling businesses can build and share a robust documentation of how their business decisions work, rendering them transparent and open to wide review. Modelling reveals how decisions can be decomposed into smaller sub-decisions for scalability and exactly what data and business knowledge are required to make them work effectively. This thorough understanding of decision dependencies enables effective impact assessments and leads to agile change cycles.

Modelling is also the first step in automating decisions to reduce the cost of manual processes and capturing the expertise of manual decisions to avoid losing business expertise when key members of staff leave a company.

If your business systems make any kind of manual or automated decisions that influence your operations then you need to adopt Business Decision Modelling as a matter of priority. It’s as simple as that. Companies that leave their business decisions embedded in obscure program code, or implicit in the heads of staff who manage manual operations, will be outmaneuvered by competitors who practice Decision Management and Decision Modelling. In this article we explain the reasons why Decision Modelling is so important to your enterprise.

What is Decision Modelling?

We assume that readers of this article are already familiar with operational dec

Decision Models Specify Decision Requirements

isions and are convinced by the importance of Decision Management. Decision Modelling (DM) has three main goals:

Providing a precise, standard and transparent presentation of each business decision in business terms
Analyzing the requirements (dependencies) of every decision, including data, business knowledge and other, subordinate decisions

Decision Models Specify Decision Logic
Supplying a framework to define the logic of all decisions and make them traceable and mutually consistent

Six Reasons to Model Your Business Decisions

1 Transparent and Precise Communication of Business Policy

DM’s principle motive is to capture and communicate business decisions in a manner that are easy for business subject matter experts to understand, verify and even simulate. A business-oriented representation that is separate from implementation details, yet precise enough to inform developers. Explicit representation of business decisions liberates them from the bowels of IT systems and from the heads of subject matter experts, bringing them out into the light for all to see and avoiding loss of business expertise caused by legacy system and staff attrition.

DM aims to increase the effectiveness of communication between business analyst and development team so that fewer mistakes are made and time can be spent more productively in discussing the correctness and ramifications of requirements rather than resolving misunderstandings about their meaning. DM is about making the structure and logic of decisions transparent to stakeholders and precise for developers. The transparency DM provides makes it easier for experts to spot and correct flaws in decision making, improving accuracy.

2 Separation of Concerns

DM also serves to separate but connect definitions of:

business process – when, in what order and by whom decisions should be made, how the outcome affects our business process;
business data;
implementation – the code that automates decision making and
business decision – the business logic of the decisions themselves, their behaviour in exclusively business terms.

This separation permits the succinct capture of each of these facets in an appropriate representation and allows each to evolve at their own rates.

3 Managing Complexity, Maintaining Integrity

Unlike ad-hoc spreadsheets and even Business Rules, Decision Models are designed to scale effectively while remaining easy to understand. They achieve this by ‘divide and conquer’: separating complex problems into logical hierarchies of simpler concepts which can then be expressed and evolve independently, but yet collaborate explicitly and effectively.

A Decision Model is explicit about logical dependencies between business decisions, policies, mandates, laws and business data which makes it easier to determine the impact of changing one part—this is a key benefit of decisions not shared by Business Rules. Furthermore, DM gathers all related logic in one place: promoting logical integrity within rule sets, helping to identify gaps and inconsistencies as requirements are being formulated and thereby reducing errors from the start.

4 Agile Change Management

Explicit definitions of business decisions that can be understood and simulated, allows business analysts to take direct control of the evolution of business policy, rather than having to intermediate through IT teams that own the systems that implement this policy. Analysts can correct mistakes and make improvements with little IT involvement, deploying changes to a production system only when they are sure they are correct.

5 Standardization

DM standardizes the format of requirements so that there is little variance between different business analysts: a big improvement over the ‘everyone has their own spreadsheet format’ free for all. This increases transparency: allowing effective review of business requirements by all stakeholders across the world, not just those in the inner team. It also promotes consistency between different decision authors, different teams and over time.

6 Traceable Specification of Business Rules

Logic that is structured into a decision model is very well suited to implementation within a Business Rule Management System (BRMS). Many decisions can be transplanted, with very minor modifications, into BRMS decision tables. Decisions can be implemented by BRMS Decision Services.

DM and business rules together support traceability from policy mandate to production system, allowing every outcome reached by a decision to be accompanied by a justification (in terms of the policy mandate) which can be examined in hindsight. This can assist in meeting regulatory requirements by demonstrating compliance with a regulation and help to diagnose faults quickly.

Bottom Line

If your business has important operation decisions ensure they are modelled.