The Data Collection Continuum
By: Ray Zignato
About Ray: Ray Ziganto has over 30 years of hands-on experience and expertise in strategy, technology, operations and business development for domestic and international manufacturing companies
The Problem with Data
It’s no secret in the manufacturing world that operational inefficiency is costly. Unplanned down time, capacity underutilization, constrained labor availability, and quality drive up costs and threaten competitive advantage. The industrial internet of things (IIOT) helps creates transparency though real time data that can be translated into actionable insights in order to maximize operational efficiency. If you're just getting started on your IIOT journey, your fastest path to ROI is typically in OEE improvement.
Data Collection Continuum
In its most basic form, Overall Equipment Effectiveness (OEE) is Availability x Performance x Quality. However, in our experience, OEE is a metric that many companies believe they have a 'feel' for, but they rarely have reliable data to verify their assumptions. The depth of data transparency within an individual organization can be summarized into four primary groups along the Data Collection Continuum:
A “No Clue” company is on the minimal end of the spectrum when it comes to systems and tools used to collect data. There is no ERP system, no transparency into performance or accountability, but instead simply a mentality of “everybody here sure is working hard.” The lack on transparency is detrimental to an organization’s ability to even understand OEE, let along work to improve it. As IIOT uptake will drive increasing levels of transparency, “no clue” companies will find themselves unable to compete.
A company that has a “hunch” would try to back into their OEE measure by working backwards from the monthly P&L. The mentality with “hunch” companies is “if there’s money in the checkbook, we must be doing something right”. “Hunch” companies will soon find themselves in a similar situation as “no clue” companies; they will soon be outpaced by manufacturers who have operational visibility and can effectively leverage it.
“Pretty Sure” manufacturers have an ERP system in place yet resort to manual data collection on the floor. While the resources are in place to optimize efficiency, “pretty sure” companies don’t know how to effectively leverage them to accurately determine OEE, nor to effectively allocate resources. “Pretty sure” companies are often at a good starting place, but an emphasis on digital transformation must quickly become a top competitive priority in order to effectively adapt to the rapidly changing manufacturing industry. A push for further transparency on operational processes and outputs must come from the top down in order to keep pace with industry leaders.
Last but not least, we have “chaos” companies on the entire opposite end of the spectrum. “Chaos” companies have an imbalance in priorities. In short, there is too much data without enough direction. Often times, “chaos” companies were the among the first movers in digital transformation but are currently unable to effectively harness the capabilities the digital transformation brings to their business. Instead, real time data collection, alerts, and excessive reporting overwhelm manufacturers that are unprepared to strategically leverage the opportunities greater transparency can bring. Essentially, “chaos” companies operate in data pandemonium, resulting in few (or no) strategic insights to derive from the data. Strategic priorities become less clear, processes, roles, and responsibilities are subsequently muddled, and fewer truly strategically aligned decisions are made, ultimately undermining the efficacy of the implementation and providing little to no further clarity on a company’s actual OEE in the process.
While each company is unique in its approach to data collection and utilization, all have key opportunities for improvement. Where does your company fit?
That’s all for now! In my next article, I’ll focus on the common pitfalls in successful IIOT implementation. For questions, comments, or more information on how your company can effectively address data collection challenges, please feel free to reach out at email@example.com.