Factors for Complexity of Implementing Automation

After completing this lesson, you will be able to:

After completing this lesson, you will be able to:

  • Outline the factors for complexity of implementing automation

Factors for Complexity of Implementing Automation


Each business process has unique goals, paths, and needs. There are four key factors that impact the complexity of mapping, running, and automating a business process. Those factors are:

  • Collaboration and access
  • Timing
  • Routes and logic
  • Data and metrics

Collaboration and Access Complexity

Collaboration and access is our first factor. For this, you need ask questions such as, how many participants are involved? With fewer participants you have more simplicity, and more participants increases the complexity. The same thinking applies to the number of departments involved.

Additionally, how do participants collaborate during the process? Are they communicating in a sequential order, one after the other, or is it in parallel? Who is involved? The simplest is a small team, harder is universal access across a company, and the most complex is a process involving external participants. Finally, when do participants need to access the process? During business hours is more straightforward, any time or on-the-go can be prone to problems.

Timing Complexity

When it comes to timing, lower complexity is attributed to processes that are infrequent, on demand, and short. If it only needs to happen a few times a month or year, the process is used as needed. If a process is frequent, meaning many times per day, on a recurring basis, and running for a long period of time, it is more complicated to automate.

Routes and Logic Complexity

The third factor that changes complexity is more pragmatic in nature. How many different routes are there in the process? How much logic is required to determine which route to take? What kind of decisions are being made during the process? One single route, with simple logic and no approvals is basic. If you can automate it, do. Many divergent routes, with multi-tiered logic and multiple high stakes decisions may have barriers. As a citizen developer, you want to avoid this.

Data and Metrics Complexity

The fourth aspect that makes automation more, or less, complicated, are data and metrics. What types of data are required to run the process? How many system integrations are required? How are metrics and reports being used? Who needs access to metrics and reports? The more straight forward processes are those that use standard data, where reporting is retroactive, and when only the process owners need to worry about monitoring. That is good territory for a citizen developer.

Alternatively, problematic process automations are those that require customized data, need multiple integrations or external integrations only, reporting should be predictive and external people need to access it. These types of processes may not be the best starting point for a citizen developer, however.

Summary: Stay Away from Complexity with Automation

Why did we spend so much time explaining to you, the aspiring citizen developer, about the factors of complexity for implementing automation? The reason is that we want you to succeed with the first applications and automations you build. The main point here is that you focus on the simplest processes first. Understand how to look at the work you are doing and the workflows you manage and map their level of complexity. Find the least complex processes because that is where you will have quicker wins, and an impact on your organization’s efficiency almost immediately. You’ll also feel more comfortable building your own software extensions.

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