Tips for getting started with “digitization” – Blog Post #2: Getting an empirical baseline

by | Feb 13, 2023 | Blog, News

Written by Paul Hogendoorn, MEE Cluster Digital Transformation Consultant

In the first column in this “tips for digitization” series, the focus was on making sure the company leadership was on board with the digitization initiative, and that the company’s business objectives and vision for the future were aligned with the digitization initiative; in other words, making sure that you weren’t undertaking a digitization project for the sake of completing a digitization project. Equipping the staff and company with new and improved tools helps the company achieve its objectives, and digitization should be seen as just that – providing better tools for the people within the company to do their jobs.

The next step is to establish empirical baselines of where the company is. At this point, you are not looking to discern good and bad, you are just looking to know where you are at now, so you can measure your progress in your journey going forward. There are only 3 important things to be aware of at this baselining stage: 1) the information needs to be “empirical”, 2) it needs to be collected in real time, and 3) it needs to be directly related to your business’s normal day-to-day performance. 

An expression I’ve often used is “anecdotal information leads to anecdotal improvement”. You want real improvement, so you need real measurements. Anything recorded or entered manually after the fact is anecdotal.

What you measure for your baselining is equally important. Too often I see companies using indirect or more sophisticated metrics when simple uptime, downtime, start time, end time and machine cycles is all that’s needed to establish an accurate baseline.  A commonly accepted key performance indicator (“KPI”) such as “OEE” may or may not be a valid metric for the company to adopt, but you won’t know until after you establish your baseline and review what your true improvement objectives really are along with all the stakeholders in the processes. My guidance to manufacturers is to come up with KPIs that matter to everyone, not KPIs that are only meaningful to a few, and the best time to do this is after you’ve collected some good baseline data.

So, how do you collect good baseline data? It is easier than you may think. With the emergence of “IIoT” (Industrial Internet of Things) technologies, any machine, regardless of type, brand, or age can be quickly, and cost effectively connected to a data collection system to record uptime, downtime, cycles, and other information such as when the machine started operating and when it stopped. More sophisticated (and expensive) solutions are available that can connect directly with some of the more modern machine’s control systems, but none of the additional information that might be available that way is necessary to establish the all important initial baseline; in other words, you could be adding cost, time and complexity, and likely delaying the establishment of the all important initial baseline.

If this is the stage that you are at and you would like to know more about establishing your initial empirical digital baseline, send an email to and we will send you a quick questionnaire regarding your manufacturing machine processes.

A 14 to 30 day data collection period is often good enough to establish your initial baseline. The next step after that is to establish meaningful and effective KPIs, and that will be the subject in the next blog in this series.