In many assembly and fabrication businesses, one of the biggest challenges I’ve encountered is folks simply Not Knowing Where Stuff Is (NKWSI). They lack timely actionable intelligence about their business operations. This is especially problematic when the product is complex, takes multiple shifts to complete, and involves a lot of people.
"We were able to reduce the variation in the amount of product put into bottles across a 16-head machine. By bringing all the heads in alignment, we reduced average overpack by two grams. Two grams of our product means absolutely nothing to the consumer. But because of the volumes we run through here, we saved an enormous amount of money, and it all fell directly to the bottom line."
Announcing the release of my new eBook "Tripping Over Data - How too much data and not enough actionable intelligence can torpedo your business."
If you’re struggling to make sense of manufacturing big data, you’re not alone. According to research published last year by The Economist, only 42% of manufacturers have what they consider to be a well-defined data-management strategy. Even more striking, 86% report problems in managing the data they are now generating. According to David Line, Managing Editor, Economist Intelligence Unit, “Manufacturing has been at the forefront of data collection and its importance to quality and cost control is well recognised. But collecting too much data, or failing to analyse what you collect, can be counterproductive.”
Lean manufacturing is evolving towards increased incorporation of information technology into the Lean enterprise. How are you evolving your systems to support this move?
Did you know that manufacturers with visibility to real-time metrics in manufacturing have a higher average OEE (Overall Equipment Effectiveness) than those who don’t? According to the LNS Research Report: "Big Data - Driving Quality Intelligence at the Speed of Manufacturing", the difference is significant: 5 percentage points higher. You can request your copy of this reporthere.
I’m amazed by the number of organizations that still lack both the infrastructure and the ingrained, organizational core competency of turning knowledge into action. Why aren’t all organizations Excellence Addicts? Why are so many companies still stuck on the left side of the matrix? So the important question is how do we create a culture that has high measurement maturity? This may be one of the most important questions facing manufacturing today because according to Hofman’s report, “Companies with higher levels of measurement maturity have better overall performance.”
There is a lot of evidence that real-time closed loop quality data systems help manufacturers perform at higher levels. But many manufacturers are struggling. They're struggling because they have too much or too little data, or it takes way to much effort to get to their data, or they only get to the data too late to make any difference , or...
Once you've eliminated redundant and irrelevant testing, you can concentrate on breaking down the data silos so you can make better use of the data that matters. I can't tell you how many times I've seen these data silos in action. Data silos hide critical information and make it very difficult to make meaningful performance improvements.
Further, in the quality management arena, people are talking about Big Data—especially with more focus on finding correlations in real-time performance data. Many of today’s quality analytics solutions are designed to support the use of Big Data analytics, so manufacturers can cultivate and analyze massive amounts real-time data generated by SPC and other quality process data sources.
