Manufacturing Execution System • June 22, 2021

Are You Having a Good Day?

How do you know if you are having a good day?

While this may be an easy question to respond to when asked by a friend or significant other, it can often be quite difficult in other contexts, such as an operations supervisor responsible for optimizing Overall Equipment Efficiency (OEE) or another factory shop floor metric. The sad truth is this information or data is not always readily available. I know. I have been in situations where it was up to a week before I understood how my day went – even if it was five days ago. 

How Modern Are Your Manufacturing Intelligence Systems?

Despite all the investment in new technology and Industry 4.0 strategies, deployment has not always focused on the collection, standardization, and sharing of manufacturing intelligence. As a result, many a supervisor remains challenged when responding to the question of whether they had a productive, high-performance day. If you are not able to translate the vast amount of data now available into meaningful intelligence that can be acted upon quickly, then perhaps much of the potential value from this investment has not been captured.

The Work Around MES

So, what’s the problem? The sad truth is, that many manufacturers are still creating their reports and managing their factories using another type of “Manufacturing Execution System” – a Microsoft Excel Spreadsheet. It’s what they’ve used for years and now depend on. The problem is that in today’s fast-paced world where decisions need to be made quickly, it is no longer enough. Cutting and pasting data from different programs, assembling reports by hand based on yesterday’s information, and manually trying to keep track of the complexities of manufacturing operations just don’t work anymore.

Let’s start with the basics. People make mistakes, and the typical spreadsheet is likely to contain errors. In one highly publicized case shared on BBC News, a simple mistake while exporting an Excel file caused 16,000 COVID-19 patients to be dropped off England’s contact tracing list. Good people doing important work and taking great care will still make mistakes. In my experience, 90 percent of the spreadsheets I have worked with have some sort of errors – be it in a formula, data entry, filtering, or something else. If you are still using a spreadsheet to do any sort of reporting or data transfer, chances are there is an error somewhere. 

The Impact of Reporting Variability

Any time you have different managers in different locations create their reports by manually extracting operations data into an Excel sheet, there is no standardized process. How do you know if one plant is doing better than another if they’re combining data and creating reports in different ways? You don’t. This means the reports that come out of this type of process really can’t be counted on to derive meaningful information about business performance.

The Time Investment

This is often a hidden cost. Teams can spend hours and hours manually compiling data for reports, formatting the information, and then presenting it to their managers. Some organizations have dedicated resources just tasked with generating these reports, explaining variances, and managing this process. By the time final reports are ready, days have passed. The result is that operations managers have no idea if they had a good day.

Processing data manually without a standard procedure leads to mistakes. Worse case, it can expose a business to making wrong decisions or data security vulnerabilities. For example, a decades-old method of cyberattacks is to search a company’s database for Excel files titled “passwords,” or “PW,” in an attempt to seize a company’s sensitive information. Sadly, this approach still succeeds all too often.

Did you have a good day today? I hope so. As I have just shared, this is a question that’s a lot harder to answer than it seems. In a slow-paced business environment, manufacturers had the time to do manual processes and use Excel sheets. Today, it isn’t a viable strategy. 

In my next post, I’ll explore what manufacturers can do about addressing this problem.

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