How to automate decisions using rules

A business decision makers’ ability to combine answers to “what” they should automate with the “when” will differentiate a successful and unsuccessful deployment of automation.

In order to answer the question of “what”, think about those day-to-day, repeatable decisions that run the business such as:

• Location-specific decisions – such as eligibility verification, market sizing.
• Customer-specific decisions – such as credit authorizations, contract management.
• Product-specific decisions – such as design, configuration and availability.
• Process-specific decisions – such as process and request approvals, commands to perform an activity.

Now, to answer “when” – if any of your decisions fall in any of the broad categories listed above, or if you have decisions which are routine and repeatable, this is a great starting point.

It’s also worth noting that most companies find it useful to automate decisions that are time and resource intensive operationally. These are those decisions that are subject to human error and can be accelerated with automated process improvements achievable through machines and technology.

If automating business processes increases accuracy, reduces risks and error rates, improves business productivity and enables consistency in making the right decision at the right time – that’s fantastic.

Let’s look at how to automate decisions within a purchase order request.

Purchase requests are an example of a common process in many organizations. The process is usually standard: The requesting team fills out a form and sends it to the purchasing team. The purchasing manager examines the request and may either approve or reject the request depending on the information in the request. In case of an approval, a purchase order is created and copies are sent to the supplier and the inventory team.

Take the example of Alexandria Transit Company, who decided to automate decisions in their purchasing by digitizing approvals as well as processes for their end users so as to complete approvals in minutes and increase purchasing compliance.

Before automating their purchase request process, most of their decisions including purchase requisition, receiving report and invoice payment and purchase order change order required paper forms for directors to sign. Additionally, the processes were not well documented or understood. As a result, they were not consistently followed. You could read about the details of this story here.

In addition to the mentioned benefits, automation could also enable you avoid issues such as delayed purchase order, errors in the purchase order, incomplete records and errors while taking supplies delivery among others.

Business process automation helps improve accountability, transparency, and enable accurate data recording, which can be accessed by relevant stakeholders when necessary. It will also retain all process-related communication within the workflow to make execution easier and faster.

Drivers of decision automation in businesses

There are two main drivers of business decisions in organizations. These are business rules knowledge and data and information knowledge. The rule-based driven decisions and data-driven decisions techniques, in an advanced case – should work alongside each other in order to automate a decision. Let’s get deeper with the differences between the two below.

Rule-based Decision Automation

Before we get into how rule-based decision automation work, let’s dive deep into how workflow management software can enable you create such rules. Workflow management software is used to define, automate, and improve an organization’s business processes. Managing your organization’s workflow therefore means documenting, automating, and improving the way work gets done.

Moreover, the global market size of workflow management system has been experiencing remarkable growth with a $9.87 billion market size by 2021 from $3.5 billion (back from 2016). Companies often make sure tasks are completed and business goals are reached by using a wide range of different workflows.

Tallyfy is an example of an awesome platform that that transforms your tasks and approvals into automated decisions by using rule-based decision techniques.

So, how does rule-based decision automation work? The answer is simple, it’s based on rules. For example, take a scenario where you have different client on-boarding processes depending on the client company size. A rule in the form of if-this-then-that statements would be more suited to complete the task as shown in the GIF below.

As seen above, predefined human-made rules outline triggers and the actions that should follow. ‘IF’ outlines the trigger, ‘THEN’ specifies the action to complete. These rules are applied to automate decisions by making deductions and choices, imitating human intelligence.

Another slight variation to rule-based systems is the Robotic Process Automation (RPA) which could be thought as a software robot that mimics human actions. While other automation products would need modification to applications, or systems in order to carry out processes and tasks, RPA still utilizes the same interfaces a person does to interact with systems and applications.

Data driven Decision Automation

On the other hand, organizations with some maturity in process automation decide to leverage data and analytics to take the value of their process automation tools to the next level. Why is applying data and analytics to process automation useful? In most cases, the main motivation is to understand performance and measure the effectiveness of digital processes.

For companies that generate huge volumes of data and need to have a single view of operations and/or performance, converging data and analytics, automation of business processes and people up skill is necessary.

In this context, decisions are based on how a case in a certain situation is developing, and if there is uncertainty surrounding how it may behave. For instance, let’s look at an example where there is always uncertainty about how risky a driver may be in a car insurance policy case.

Here, a predictive model is best suited for automating decisions. One could even go further and combine it with rule-based decision automation to address any ambiguity in the decision-making process.

Automating decisions using rules

We’ve looked at rule-based driven decisions and data-driven decisions techniques as the main drivers of business decisions in companies. We’ll now go back to the main focus of this article which is how to automate decisions using rules and tasks in Tallyfy.

There are three main types of rules you could use to automate decisions and they include:

1. Trigger on task completion rule.
2. Trigger on form field response rule.
3. Trigger on approve/reject response rule.

We’ll begin with the trigger on task completion rule.

Let’s go through a cash collection process. Any credit officer would agree with me how painful the process of going back and forth with clients to resolve invoice disputes is at this point. An option to automate decisions in credit would then be a no-brainer, yes?

In the GIF below, we see how this process is automated and communication streamlined with your client. Credit team will only be able to carry out step two to confirm whether payment has been received only after the first payment reminder was sent to the client.

For more on how task completion rules work on Tallyfy, check here.

Second is the trigger on the form field response rule.

As in the client on-boarding scenario above, you would want to ensure that the client receives the right on-boarding experience based on whether the client company size is <100 or >100.

In this case, the first step in the template is to fill in the client’s information about their company size then create a rule for step two to only show or hide based on the form field value selected in step one. The form filed option >100 was chosen which subsequently triggered step two ‘Company Size Over 100’

For more on how rules work on a form field on Tallyfy, check here.

Lastly – there’s the trigger on approve or reject response rule – which automates rules from what happens if a response is an approval or rejection.

Another great scenario where rules could be used to automate decisions is in a vacation request procedure. Upon submitting your leave request, as shown in the GIF below – your department manager will either approve or reject your request which would subsequently trigger an email response from HR of either leave request approved or leave request rejected.

For more on how approve/reject response rules work on Tallyfy, see this support article.

Isn’t automating decisions awesome?

To wrap it up – rule-based systems offer great potential to companies looking to automate decisions in their processes. By simply following rules laid out by people, they are incredibly useful and make your processes easy to run. Automating your decisions saves a huge amount of time and money, and of course – mistakes are prevented.

We looked at scenarios when and why businesses need to automate decisions as well as where decision automation would be useful. Moreover, we also examined the three types of rules (task completion rule, form field response rule and approve/reject response rule) you could create with Tallyfy, how to automate various use cases including the benefits of automating these decisions.

If you’re interested in automating decisions – continue by signing up to Tallyfy for a free trial, or if you have questions – please schedule a call.