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 and nuturing 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 your enterprise goals. Decision Modeling focuses on representing decisions in a precise, standardized and transparent way.
Through Decision Modeling, businesses can:
- Build and share a robust documentation of how their business decisions work, rendering them transparent, open to wide review and revealing any hidden flaws.
- Tame complexity by decomposing complex decisions into smaller sub-decisions for scalability.
- Prepare their decisions for external (compliance) audit by ensuring their behaviour can always be explained and justified against a specification.
- Understand quickly exactly what data and business knowledge are required to support their business decisions.
- Through a thorough understanding of decision dependencies, enable effective change impact assessments and agile change cycles.
These advantages cannot be provided by existing approaches like Business Rules alone.
In addition, decision models can be made so precise that they are executable. Modeling can also be 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 manual or automated decisions that influence your operations then you should consider adopting Business Decision Modeling as a matter of priority. Companies that leave their business decisions embedded in obscure program code, ‘technical’ business rules or in the heads of staff who manage manual operations, will be outmaneuvered by competitors who practice Decision Management and Decision Modeling and will be less able to justify the behaviour of their systems to an auditor. In this article we explain why.
What is Decision Modeling?
We assume that readers of this article are
- Providing an explicit, 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
- Supplying a framework to define thelogic of key 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 way that’s visible to business subject matter experts. Allowing them to understand, verify and even simulate decisions using test data. DM provides 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.
Decision Models are not ‘Visio model shelfware’. They can be executed allowing them to become an executable representation of a specification that can be directly deployed into a decision service. This saves time by avoiding the error-prone translation step usually performed by IT.
DM aims to increase the effectiveness of communication between business analyst and development team so that fewer mistakes are made. DM is about making the requirements, 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 and reducing time to market.
2 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 decision requirements: 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.
3 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 (using simulation and impact analysis), deploying changes to a production system only when they are sure they are correct.
4 Traceable Specification of Business Rules That Supports Audit
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.
In addition to helping with compliance, traceability helps us to align business decisions with measurable business goals (KPIs) which makes the effectiveness of our decisions easier to measure on an on-going basis.
4 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 eases the capture of each of these facets in an appropriate representation and allows each to evolve at their own rates. It also promotes reuse across the enterprise.
DM standardizes the format of requirements, using standards like DMN, 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. Again, this advantage is not shared by Business Rules.
If your business has important operational decisions ensure they are modeled.