Cooking Up Automation Discovery: Hell’s Kitchen or Master Chef ?

Facing heightened customer expectations, rising competition from digital disruptors, and the trial by fire of the Covid-19 lockdown economy, enterprises are looking to accelerate their digital transformation programs. As they do so, choosing which processes to automate is a burning priority.

Most organizations can choose between hundreds or even thousands of automations, and prioritizing the right ones can accelerate the time to achieving a return on investment. The traditional, manual ways of doing this are not only complex, time intensive and expensive, but also lead to incomplete and subjective answers. An example of such an approach is to get the stakeholders together to gather ideas, then observe how employees work, interview experts and gather supporting data from the business operations team. This approach can potentially hamper speed-to-market with new process automations.

Another methodology is to ask expert users to record themselves executing a business process. This approach is of limited value because it does not capture the variations in how different employees carry out a process, neither does it offer insight into work carried out across other business processes.

With apologies to Gordon Ramsay, I suggest that there are two better approaches to automation discovery that I will call ‘Hell’s Kitchen’ and ‘MasterChef’. Both approaches are valid, but each business should decide which is best suited for its needs as well as what it required to successfully use each technology. Let’s take a closer look.

Desktop Process Discovery – Hell’s Kitchen

Desktop process discovery is the Hell’s Kitchen approach. It uses a discovery technology to collect data on how users interact with applications and applies artificial intelligence (AI) to analyze the data and suggest automation opportunities. This approach has the virtue of simplicity. It doesn’t require previous analysis or rely on external dependencies.

Process Mining – MasterChef

Process mining – the MasterChef approach – aims to answer a straightforward question: How can we best prepare a specific dish? An organization analyzes the end-to-end execution of a specific business process and identifies the possible improvements. Just as MasterChef requires one to select the dish in advance and prepare the ingredients, process mining requires selecting a business process and collecting event log files from the relevant 3^rd party enterprise applications.

Use cases for each approach

Process mining includes the process discovery step, which discovers a model for a process based on its execution paths in the event logs. Desktop process discovery is a newer technology that uses AI to discover automation opportunities across the entire employee workday and requires no guidance or previous knowledge.

Both approaches are valid. Let’s consider suitable use cases for each of them:

• Desktop process discovery is a powerful tool for identifying actionable attended and unattended automation opportunities. It can analyze a user’s work across all applications without needing log files from third party applications. It isn’t restricted to analyzing a specific predefined process.
• Process mining is best used when an organization wants to identify bottlenecks in a specific business process. An example is slow and inefficient processing of incoming invoices. Process mining uses log files from relevant applications to provide a high level, end-to-end view of the process and the opportunities for improvement. These findings will not necessarily be geared towards robotic process automation opportunities.

There is great value to be found in combining the two approaches. We will elaborate on this in our next blog. Until then, you can read about the NiCE Automation Finder to find out how our AI and analytics-driven approach can help you identify business processes that are ripe for automation.