What DMN And Improved Decision Logic Mean For Process Automation


DMN is a notation system that specifically aids in decision making, and while it’s written out in a way that seems very much helpful to humans, this type of notation is relatively new compared to other systematic notations — partly because DMN (short for Decision Model and Notation) is a tool used to inform machine-led decisions, rather than human ones.

The basis for this is what’s called a “rules engine”, and it’s what makes it possible for machines to act in predictable ways according to various input data. When a customer order, an employee’s input, or even the results of another process come into the picture, there is always a defined response, nailed out by the decision tables used in DMN.

If you’re looking to inform decisions for your automated workers like RPA bots, as well as automated microservices and the like, then you’ll need to know how DMN benefits this relationship with your machines, and how it enables you to guide their actions the way you would conduct business.

How Does DMN Work?

DMN decision tables allow you to set specific outputs for each type of input data that will come along within a task or process. You can see it at work specifically when any sort of “if, then” statement is executed, represented by the DMN system in the form of columns. Ignoring annotations, which are for the user, the rightmost column is the output that will be delivered by the computer that’s referencing your decision table.

The columns to the left of this are the input: there can be as few as one, but in many cases, there are multiple conditional inputs that create a context for the decision-making process that your machines will undergo. This way, you don’t rely on anything but pure logic to make many of the decisions that you can choose to automate within your process.

What DMN Means For Process Automation

DMN is something that creates ease of burden, in a sense. If you are using process automation, chances are the bots aren’t smart in the sense that some software is, but instead rely on preset conditions for them to do the work assigned to each one. This is because process automation generally consists of (and really only requires) rules-based execution, wherein certain inputs generate certain outputs.

DMN makes this a palpable thing, notating these rules as the basis for tasks without the need for coding or reprogramming of the bots themselves. Instead, the machines in your employ can act as needed on each new workload given the rules that are pre-established in a one-time setting. By creating a DMN decision table, you’re avoiding providing the rules to each application each time they need it, and you also avoid having to enter extraneous commands and information into each order, thereby asking less of your customer as you employ this method.

A process that runs the same way until certain conditions are met is the main goal: there is always a control of some sort, whether it’s the default service you offer or an empty cart. However, once the cart fills, or the service changes by request, the actions that are taken within your automated workflow are determined and changed accordingly, making processes that much more precise and predictable for customers, and even creating the sense of consistent communication and consistent quality of product.

Another thing that DMN changes for process automation is that you can see, first-hand, what your rules engine looks like on the inside. When you find you need to change something after looking at the way your rules are set up for automation, you can also make these changes faster than ever before. Where automation once needed to be fully reprogrammed to make different decisions or to change conditional behaviors, that same need is somewhat eliminated, as much of the changes you can make to a process automation system are right there within that decision table.

The next thing that DMN can change for a process is the overall quality of decision logic. While processes can sometimes suffer when decision logic is written out in the programming of a software, with DMN tables you have a built-in way to verify your conditions and your outputs — making the determination of your rules crystal clear when in execution.

What Improved Decision Logic Achieves

Improving the decision logic doesn’t only mean improving the quality of these decisions and the decision-making process. It also means that speed is a factor when pivoting for a special order, remediation of a process issue, or even a new set of automations within the process. Whatever you have to prep and pivot for, you’ll be able to do so thanks to a decision logic that’s been improved in not just its implementation, but in its clarity.

Decision logic is also what affects the way you approach business in certain cases. Since every business process starts with decisions (like which product to buy, which one to stock up on, and so on), the streamlining of the rules that make up your process gives your business the chance to internalize what’s happening during said process: what’s not being ordered, what conditions are never met, and what decisions aren’t attractive to customers are all great considerations when looking at how your decision logic will ultimately affect your process automation and your business as a whole.


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