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Contributed on September 8, 2017

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Decision Management Drives Disruption

As processes, apps and resources get smarter, the way in which we make decisions, and manage decision-making, becomes ever more important. This is especially true of industries where the fundamental processes change relatively little, yet business policies and regulations that affect those processes change much more rapidly. The need for greater agility has led to a resurgence in the search for methods that help businesses first visualise, and then execute, their ideas. In parallel, the standards related to business processes have taken a big step forward with the Decision Management Notation (DMN), which has wide implications for the new era of business automation. There’s a battle shaping up between established incumbents and this new execution era enabled by the DMN standard and its underlying expression language.

Top takeaways

Managing decisions, from visualisation to execution

Decision modelling, and the relatively new decision modelling standard DMN, have the potential to drive radical change in how you visualise, manage, control and automate aspects of your business.

With decision modelling, you now have way of visualising the future – using models to express strategies, goals, processes, policies, rules and constraints – and then driving those visualisations all the way to execution. As we will see, this is already happening. However, there are significant challenges ahead.

DMN’s impact is potentially very significant, but FEEL is key

The DMN standard sets out to enable business people with a way of interacting with, and describing the rules and constraints that they want in the world of systems implementation. It also enables the rapid development of reusable components for that world.

What’s fundamentally different about the DMN standard is that the standardisation and accessibility of the notation is enabling a new wave of innovation; a wave that has managed to overcome many of the limitations of previous attempts to move toward model-driven applications.

However, that promise only comes to reality with full support for FEEL level 3 compliance. An open source execution engine for Level 3 compliance is available as a part of Red Hat’s implementation for DMN. While FEEL support may appear challenging to implement, it is certainly possible with a few months of programmer time.

Vendors are squaring up for a decision management battle

As with all standards, there are different interpretations of the way ahead. Incumbent vendors want to shape the narrative around the standard to favour their strategies – to disadvantage key competitors, or block the opportunities for new disruptive products to emerge. Each organisation looks at the opportunity (and threat) posed by the DMN standard through its own perspective.

The potential to drive radical change

Decision modelling, and the relatively new decision modelling standard DMN, have the potential to drive radical change in how you visualise, manage, control and automate aspects of your business. This change may take many forms including:

• Decision modelling that shapes strategic thinking, for example:
  • As an engagement framework to align digital transformation efforts.
  • To create optimisation frameworks that resolve intractable/wicked problems.
  • To clarify, integrate and complement government regulations.
  • To help shape governance practices within the firm.
  • Shaping business analytics, metrics and the structure of business dashboards.
• Decisions-as-a-Service (DaaS) that:
  • Package knowledge for sale, and on the fly analysis of data.
  • Animate “what if” scenarios against partial sets of input data.
• Decision Services, as an enabling component of automated process execution, that deliver:
  • Rapid reconfiguration of outcomes in line with changing policies and regulations.
  • More effective and efficient use of process automation and RPA technology.
  • Optimisation using analytics and the definition of constraints, leading to more effective Next Best Action and Prescriptive Analytics.
  • Intelligent monitoring of IoT device data, leading to better predictive maintenance; even shaping how IoT devices generate and communicate that data.
• Support for software bots and AI/ML technologies by:
  • Providing frameworks that help create training/learning mechanisms.
  • Defining constraints within which these environments operate.
  • Creating after-the-fact explanations for opaque AI recommendations/decisions.

Business now has way of visualising the future – using models to express strategies, goals, processes, policies, rules and constraints – and then driving those visualisations all the way to execution. As we will see, this is already happening. However, there are significant challenges ahead. In the end, advances in decision management means dramatic changes to:

• How the business develops its strategies and tactics.
• The vision for digital transformation and the design of appropriate systems architectures.
• The roles and responsibilities of organisational governance.
• The process architecture used to drive work, and “How things get done around here.”
• How applications and systems are developed and maintained; indeed, the role of IT.

The reality is that many organisations are ill prepared to handle these changes.

A brief introduction to decision modelling and DMN

There’s nothing especially new about the desire, when designing systems, to separate processes from decision logic, data management and user interface definitions. Savvy application designers have always sought to reduce the amount of coding required. We’ve long understood the need for this separation of concerns – the difference is that we can now separately manage the lifecycles of these distinct types of artefacts.

Driven by the maturation of process modelling notations such as BPMN, vendors and consultants came together under the auspices of the Object Management Group to create a standard decision-modelling notation. The “Decision Model and Notation” (DMN) was published by in September 2015, with the current version DMN 1.1 released in June 2016. Most importantly, the standard incorporates compliance levels to facilitate interoperation and transport of definitions between products. Work is currently ongoing to finalise version 1.2, with several vendors already talking of support.

The DMN standard builds on a wide body of research and experience in building effective business rules environments. It emerged from a collaboration of key vendors and consultants active in the space – particularly FICO, Decision Management Systems, Trisotech and Sapiens DECISION.

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