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Best Practices

Avoid top mistakes companies do with process mining

mistake

At Minit, we had a chance to observe how companies leverage Process Mining software to make decisions. During the past year, we noticed a number of trends and approaches to that are ineffective and result in wasted opportunity. So how do you mine your data to drive insights that actually make a difference to your bottom line?

Mistake #1: Starting Analysis Without a Goal

Companies have understood the importance of data and are starting to invest in analytical capabilities. But all too often, while there is an intense focus on analyzing processes, companies lack any strategic direction for the initiative. We had customers provide us with event log data from their corporate system, without any clue about the story. With no clear point of view, no defined questions, we are left chasing a moving target.

How Minit analyzes data behind your operations

You need to start with a specific question to answer or investigate. A lot of times, people will extract data from a particular process and then say, ‘How's it doing?’ Rather than saying, ‘Our goal is to convert more customers, or we want to speed up claims underwriting.‘

Michal Rosik, CPO, Minit

You need a clear and agreed-upon goal and the key metric that's going to determine success. That is the key to useful application of Process Mining - to stipulate what you’re trying to accomplish and how you’ll define success. The best practice is to have the goals written down before analysis gets started.

Putting your goal down on paper is also the best way to resist the tendency to shift gears as you go. We are not saying you should turn a blind eye to other insights that surface in your data, but keep your focus on what you’ve set out to accomplish.

What is your number one priority for the quarter? Do you have a clear, definable metric around it?

Michal Rosik, CPO, Minit

Mistake #2: “First we need a Dedicated Data Scientist”

Don't think that your organization’s analysis needs to come in the form of a dedicated employee with a “data scientist” title. Try to think in a broader context. Data science requires statistical and programming skills. But you also need to understand the market and how your business functions to ask the right questions and meaningfully answer them. Companies often hire for the technical skills and place the employee in a silo without access to business knowledge. Mostly they don’t have the time or opportunity to interact with people who could give it to them and without context no matter how good an analyst, they can’t be successful.

Isolation blinds the data scientist to the realities of how the company is operating, and this makes their results and recommendations theoretical and often irrelevant. They don't know what to look for, or which are the right questions.

Consider the skills a data scientist needs; you might already have someone like that on board. Look into your team, for a combination of analytical mind, technical skills, and business acumen — and support those employees. It might be easier to combine capabilities of your in-house experts and make them come together on analysis than to look for one unicorn who can do all of those things.

[FREE CHECKLIST] Business Process Analysis

Mistake #3: Chasing After the Ultimate Tool

New tools emerge all the time. But at the end of the day, they can’t make your analytics foolproof or perfect.

If you put garbage in, garbage is all that will come out. A tool can absorb whatever event logs you import, but it’s you that has to define what those events are and what they mean.

Michal Rosik, CPO, Minit

Adoption of the right mindset is much more important than the adoption of any single tool. There’s no substitute for clarity and consistency, nor a tool that can replicate a clear point of view. Adopt a central dashboard for measuring process metrics and KPIs.

When you know what your key metrics are and you put them on a dashboard, no one else can change it. It can be as simple a locked Google Doc. The point is to have a canonical source of truth for what you’re doing, as well as a resource that you can push out to the rest of the organization on a regular basis.

Michal Rosik, CPO, Minit

Simona Parnicka Marketing Manager at Minit

31. 10. 2017