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About ERP Systems

Big Data

- Wednesday, December 12, 2012

In the early part of his career as an aviation engineer with GE, John Bosch pioneered the standardization of gauges on aircraft, solving the problem of too much visual diversity with instrumentation in the cockpit. The way Bosch explains it, all military and commercial engine instrumentation was procured from different manufacturers who built both the transducers and indicators. What the pilot saw in the cockpit were very different displays with needles pointing in all different directions, and these different appearances made it hard at a glance to see the situation of the airplane. Working with the chief pilot of Pan Am, the customer, Bosch basically simplified the complex, creating a system of displays that all spoke the same language. So finally, the customer could see the situation at a glance.

Sound familiar? Isn't that what happens in a manufacturing operation that relies on different data sets?

Wikipedia, now ranked the #5 website in the world, defines the information technology term of Big Data as “a collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools”.  These data sets are important for companies to analyze and understand if they want to make decisions based on the best -- and most accurate -- analysis. Fortunately, a number of toolsets exist to extract and perform data analysis that helps organizations -- small, medium and large -- make quality decisions when dealing with future management issues.

But here's the catch. For the information to be useful, the data sets must be accurate, and after nearly three decades of assisting small and mid-sized manufacturing and distribution organizations, I've learned that basic and vital company data are, very often, NOT CORRECT. Usually it's not a matter of someone making mistakes, it's more a matter of different systems -- like Bosch's system of displays -- that don't speak the same language and the information just doesn't compute, as they say.

Programs that clean-up data are usually a starting point for performing information improvement projects. A recent article in IndustryWeek discusses some of these issues. The article identifies integration issues, accessibility issues, and the inability to analyze meaningful data.  The article also stresses that data analysis needs not be restricted to the Information Technology group but pushed down to the proper user.

Our consultants see the same issues and more often than not, there are bigger issues with data accuracy. Part Number units of measure problems, inaccurate sales order delivery dates, incorrect plant throughput values, Bill-of-Material quantity per values and sometimes, inaccurate “Ship-To” addresses are the source of these errors.  These data must be accurate to be able to produce information that the organization can trust to assist with making proper decision about the future.

John Bosch and the engineers who worked with him simplified the complex in a way that probably has saved lives. I believe that organizations who understand how to improve their Big Data will have a tool that help save their bottom lines. We have written a number of articles that suggest methods to address the basic system data errors.  One article, The Future Ain’t What It Used To Be, recommends data analysis as a useful tool to address company and customer concerns in a proactive manner. Another article discusses how your ERP System can create the Key Performance Indicators to measure employee and department conformance to company goals.  Using KPI in Your Business has had a large readership and references one of first uses of KPIs at Ford Motor Company. Henry Ford was a stickler for measuring, and used measurements to understand whether process were in control or out of control. Like Bosch, he figured out how to simplify an otherwise complex production process.  

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