What are decisions and where are they relevant

Decisions, complex and simple, are made throughout organizations every day. Many of these decisions are manual, but a growing number of them are automated.

Decisions are typically recognized through action words, such as ‘determine,’ ‘calculate’ or ‘estimate.’ For example, through a customer onboarding process, client details are collected and then decisions are made to: ‘determine due diligence,’ ‘determine suitable products’ within the client’s area of interest and associated risk determination, ‘determine risk level for this domain,’ ‘calculate product cost,’ as well as many more decisions throughout the KYC and AML processes. Once onboard, there may be other decisions such as ‘determine upsell products’ to add further value to the customer engagement.

We use the term business logic to represent how the decision conclusion is determined from a set of input data. Traditionally, there has been no robust and rigorous mechanism to extract business logic relating to decision making from process and data domains as well as various non-standard documents and spreadsheet formats. This results in the business logic being lost in a sea of domains, documents and formats. Change and automation becomes expensive and extremely high risk.

Decision management changes the game by creating a specific domain, separate from process and data, where decisions are determined, defined, tested, governed and analyzed. The advent of a robust and rigorous model (The Decision Model) provides the design principles and models that ensure decisions have integrity, and are unambiguous, accurate and consistent across an organization. The combination of intuitive graphics and intelligent tables drives common understanding of the decision business logic irrespective of role (BA, SME, Product Management, Audit, IT, Test, …).

The result is a set of reusable decision services that can be consumed across multiple processes and channels, driving improved omni-channel capability and customer experiences. Change management becomes greatly simplified as the user creates new versions of the decision model from the current model, with the ability to compare, test and release. Regulatory compliance also benefits greatly through the transparency and common understanding of the regulatory decisions interpreted and modeled from the appropriate regulation and/or policy.

Automated decision making

Decision Management entails all aspects of designing, building and managing the Business Logic that an organization embeds into the business systems that manage its business processes. The demand for a Decision Management software platform is growing as companies grapple with the complexity and negative implications of the current manual process involved in capturing, articulating translating and, then, managing Business Logic from business people into IT systems.
Enterprises are also turning to Decision Management technology in order to reap a higher return from previous investments in enterprise architecture and because they are faced with:
  • Increasing Business Logic and business rule complexity
  • Competitive pressure for more sophisticated automated decision-making to provide immediate always on customer engagement
  • Increasingly short windows of competitive advantage – i.e., the speed of business demands is outpacing IT’s ability to react in a timely fashion
  • Meeting organizational change management and business process management requirements – especially under increasing regulatory compliance pressureDecision Management is an emerging discipline that basically describes what business systems do. Technologically speaking, it is trailblazing the evolution from electronic documents and spreadsheets in the same way that calculators have replaced pen and paper.

Today’s business systems – falling short

The process for the creation of Business Logic is still largely manual, incomplete and subject to opinion, error and the inability to see flaws within the model. In order to describe logic, today’s business systems rely on an ad hoc combination of direct communication with business users, documents and spreadsheets prepared by business analysts and business rules engines, such as those found in a Business Rules Management System (BRMS). Finally, the decision modeling process is sometimes governed by a requirements management framework, as detailed in a Zachman Framework ontology.

If the process is not perfectly clear, complete and precise, expect:

  • Lengthy processes for capturing requirements and definitions
  • 10-70% duplication of efforts implementing the same logic in multiple places (i.e. more than one application and database)
  • Production issues, such as missed or incorrect requirements, errors and unforeseen consequences
  • Incomplete rules management and/or decision tree modelling
  • 1,000% more effort required to correct implementation issues found in UAT
  • Manual extraction of existing logic from applications, resulting in errors, 10-50% more burden on application developers and 100-1,000% longer delivery times
  • De-scoping of automation

Combined, these factors lead to longer times to market, higher costs of error detection and resolution and, ultimately, to increased operations costs and compliance failures.

Here and now

When requirements, policies and business rules are formulated using a structured process and template, that enforce a clear method for their articulation, the result is a clear, complete and precise model for Business Logic. This model can be:
  • Governed by a requirements management framework such as a Zachman Framework ontology
  • Validated and tested for integrity, precision and completeness in the requirements authoring phase
  • Implemented by IT or automatically transformed into executable code
  • Used as a hub for the most current Business Logic within an enterprise, in order to:
    • Share the model and apply it consistently across multiple processes and applications
    • Enable modifications to the Business Logic with clear change impact visibility thanks to enhanced analysis capabilities

The benefits are tangible and have fundamental effects on the business, including:

  • 20-50% shorter projects (with most issues discovered early on during business logic articulation)
  • 400-1,000% faster time to market for new products, services and updates
  • 10-70% more reuse of Business Logic
  • Significant reduction in production issues (e.g. fewer compliance fines, risk allocations, etc.)
  • Less time and resources needed to handle production incidents, support issues and compliance inquiries
  • More business processes get automated (less de-scoping)
  • Reduced cost of operations

The Decision Model, included in the Sapiens DECISION offering, provides support for the Decision Model and Notation (DMN) specification recently adopted by the Object Management Group, an industry standards consortium.

Read more about our business decision management solutions.

“It’s about decisions and data…the decisions we have to make quickly and accurately and accessing the data to do so.”
Head of Transformation – Top 10 US FSS Company