Mastering Decision Centric Orchestration

Balancing Human Insight and AI Automation for Justifiable, Context-Aware Business Choices

Presented By
Denis Gagne CEO & CTO Trisotech.
Description

In today’s dynamic business landscape, decision-centric orchestration is pivotal for organizational success. This presentation delves into the diverse spectrum of decisions within an organization, ranging from those that are purely human to those that are fully automated. We will explore how various types of artificial intelligence (AI) support decision automation, with a particular emphasis on the crucial role of context in making informed business choices. Attendees will gain a comprehensive understanding of how context-aware AI can enhance decision-making processes, ensuring that outcomes are not only efficient but also relevant to specific business needs.

Highlighting the necessity of explainable and justifiable decisions, we will discuss the imperative of maintaining human oversight in all business processes. The presentation will address the challenges and opportunities associated with integrating AI into decision-making frameworks, focusing on the balance between human intuition and AI-driven efficiency. Attendees will learn strategies for achieving a harmonious integration of these elements, ensuring that their organization’s decision-making is robust, transparent, and aligned with ethical standards. Ultimately, this session aims to equip business leaders with the knowledge and tools to leverage both human insight and AI automation for superior organizational performance.

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Mastering Decision Centric Orchestration

Balancing Human Insight and AI Automation for Justifiable, Context-Aware Business Choices

Presented By
Denis Gagne CEO & CTO Trisotech.
Description

In today’s dynamic business landscape, decision-centric orchestration is pivotal for organizational success. This presentation delves into the diverse spectrum of decisions within an organization, ranging from those that are purely human to those that are fully automated. We will explore how various types of artificial intelligence (AI) support decision automation, with a particular emphasis on the crucial role of context in making informed business choices. Attendees will gain a comprehensive understanding of how context-aware AI can enhance decision-making processes, ensuring that outcomes are not only efficient but also relevant to specific business needs.

Highlighting the necessity of explainable and justifiable decisions, we will discuss the imperative of maintaining human oversight in all business processes. The presentation will address the challenges and opportunities associated with integrating AI into decision-making frameworks, focusing on the balance between human intuition and AI-driven efficiency. Attendees will learn strategies for achieving a harmonious integration of these elements, ensuring that their organization’s decision-making is robust, transparent, and aligned with ethical standards. Ultimately, this session aims to equip business leaders with the knowledge and tools to leverage both human insight and AI automation for superior organizational performance.

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Bruce Silver's blog post - What Is a Decision Service?
Bruce Silver
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What Is a Decision Service?

By Bruce Silver

Read Time: 5 Minutes

Beginning DMN modelers might describe a decision service as that rounded rectangle shape in a DRD that behaves similarly to a BKM. That’s true, but it is a special case. Fundamentally, a decision service is the unit of execution of DMN logic, whether that is invoked by a decision in the DRD, a business rule task in BPMN, a decision task in CMMN, or an API call in any external client application or process. Whenever you execute DMN, whether in production or simply testing in the modeling environment, you are executing a decision service.

In Trisotech Decision Modeler, that is the case even if you never created such a service yourself. That’s because the tool has created one for you automatically, the Whole Model Decision Service, and used it by default in model testing. In fact, a single decision model is typically the source for multiple decision services, some created automatically by the tool and some you define manually, and you can select any one of them for testing or deployment. In this post we’ll see how that works.

Service Inputs, Outputs, and Encapsulated Decisions

As with any service, the interface to a decision service is defined by its inputs and outputs. The DMN model also defines the internal logic of the decision service, the logic that computes the service’s output values from its input values. Unlike a BKM, where the internal logic is a single boxed expression, the internal logic of a decision service is defined by a DRD.

When the service is invoked by a decision in a DMN model, typically it has been defined in another DMN model and imported to the invoking model, such as by dragging from the Digital Enterprise Graph. But otherwise, the service definition is a fragment of a larger decision model, including possibly the entire DRD, and is defined in that model.

Within that fragment, certain decisions represent the service outputs, other decisions and input data represent the inputs, and decisions in between the outputs and inputs are defined as “encapsulated”, meaning they are used in the service logic but their values are not returned in the service output. When you execute a decision service, you supply values to the service inputs and the service returns the values of its outputs.

One Model, Many Services

In Trisotech’s Whole Model Decision Service, the inputs are all the input data elements in the model, the outputs are all “top-level” decisions – that is, decisions that are not information requirements for other decisions. All other decisions in the DRD are encapsulated. In addition to this service, Trisotech automatically creates a service for each DRD page in the model, named Diagram Page N. If there is only one DRD page in the model, it will be the same as the Whole Model Decision Service, but if your model has imported a decision service or defines one independently of the invoking DRD, an additional Diagram Page N service will reflect that one.

All that is just scratching the surface, because quite often you will want to define additional decision services besides those automatically created. For example, you might want your service to return one or more decisions that are defined as encapsulated in the Whole Model Decision Service. Or you might want some inputs to your service to be not input data elements but supporting decisions. In fact, this is very common in Trisotech Low-Code Business Automation models, where executable BPMN typically invoke a sequence of decision services, each a different fragment of a single DMN model. In BPMN, if you are invoking the Whole Model Decision Service it’s best to rename it, because the BPMN task that invokes it inherits the decision service name as the task name.

Defining a Decision Service

So how do you define a decision service? The DMN spec describes one way, but it is not the best way. The way described in the spec is as a separate DRD page containing an expanded decision service shape, a resizable rounded rectangle bisected by a horizontal line. The shape label is the service name. Decisions drawn above the line are output decisions, those below the line are encapsulated decisions. Service inputs – whether input data or decisions – are drawn outside the service shape, as are any BKMs invoked by decisions in the service. Information requirements and knowledge requirements are drawn normally.

The better way, at least in Trisotech Decision Modeler, is the decision service wizard.

In the wizard, you first select the output decisions from those defined in your model, and the wizard populates the service inputs with their direct information requirements. You can then promote selected inputs to encapsulated, and the wizard recalculates the needed inputs. You can keep doing that until all service inputs are input data, or you can stop anywhere along the way. The reason why this is better is that it ensures that all the logic needed to compute the output values from the inputs are properly captured in encapsulated decisions. You cannot guarantee that with the expanded decision service shape method.

Testing DMN Models

Trisotech’s Automation feature lets you test the logic of your DMN models, and I believe that is critically important. On the Execution ribbon, the Test button invites you first to select a particular decision service to test. If you forget to do this, the service it selects by default depends on the model page you have open at the time you click Test.

In Test, the service selector dropdown lists even more services than the automatically generated ones and those you created manually, which are listed above a gray line in the dropdown. Below the line is listed a separate service for every decision in the model, named with the decision name, with direct information requirements as the inputs. (For this reason, you should not name a decision service you create with the name of a decision, as this name conflicts with the generated service.) In addition, below the line is listed one more: Whole model, whose inputs are all the input data elements and outputs are all the decisions in the model. It’s important to note that these below-the-line services are available only for testing in Decision Modeler. If you want to deploy one of them, you need to manually create it, in which case it is listed above the line.

In Test, your choice of decision service from the dropdown determines the inputs expected by the tool. As an alternative to the normal html form, which is based on the datatypes you have assigned to the inputs, you can select an XML or json file with the proper datatype, or use a previously saved test case.

Invoking a Decision Service in DMN

Invoking a decision service in DMN works the same way as invoking a BKM. On the DRD containing the invocation, the decision service is shown as a collapsed decision service shape linked to the invoking decision with a knowledge requirement.

The invoking decision can use either a boxed invocation or literal invocation. In the former, service inputs are identified by name; in the latter, input names are not used. Arguments are passed in the order of the parameters in the service definition, so you may need to refer to the service definition to make sure you have that right.

Invoking a Decision Service in BPMN

In Business Automation models it is common to model almost any kind of business logic as a DMN decision service invoked by a business rule task, also called a decision task. In Trisotech Workflow Modeler, you need to link the task to a decision service in your workspace; it is not necessary to first Deploy the service. (Deployment is necessary to invoke the service from an external client.) As mentioned previously, the BPMN task inherits the name of the decision service. By default, the task inputs are the decision service inputs and the task outputs are the decision service outputs.

Data associations provide data mappings between process variables – BPMN data objects and data inputs – to the task inputs, and from task outputs to other process variables – BPMN data objects and data outputs. On the Trisotech platform, these data mappings are boxed expressions using FEEL, similar to those used in DMN.

The Bottom Line

The important takeaway is the a decision service is more than a fancy BKM that you will rarely use. If you are actually employing DMN in your work, you will use decision services all the time, both for logic testing and deployment, and for providing business logic in Business Automation models. The decision service wizard makes it easy.

If you want to find out more about how to define and use decision services, check out DMN Method and Style 3rd edition, with DMN Cookbook, or my DMN Method and Style training, which includes post-class certification.

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