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By Chris Gray

Regardless of what improvement program or acronym you’re currently involved with - ERP, supply chain management, Lean Manufacturing, Six Sigma, reengineering - some things never change.

For example, Wight’s 35th Law, When you change five things at once and things get better, credit will be given to the most complex thing you changed, when the improvements actually resulted from the simplest thing, is as true today as it ever was.

Today, no one argues much about the need for accurate and timely data. Any modern resource planning and scheduling system -including every supply chain management alternative - depends on accurate inventory records, accurate distribution networks and source of supply definitions, accurate transportation data, sensible lot sizing and lead time data, reasonable safety stock guidelines, up to date in transit inventory records, etc. Without this kind of data, the system won’t work. Regardless of the size of your investment in software, computers, and communication, results fall far short of expectations.

But data quality doesn’t get much attention in most companies. Yes, there are a few very well managed companies that know that accurate data isn’t an accident. They have in place proper accountability, defined objectives, performance measurements, and feedback.

Unfortunately, in most companies, there’s an assumption that the data is, or will be, good enough. People are focused on "more important things", like the new MINTS, MARKS, or RANDOM scheduling systems "with the hot new constraint based scheduling logic. After all, we’ll let the stockroom people and planners clean up the data". And, when and if things get better, what gets the credit? Why MINTS, MARKS, and RANDOM of course. Not the threefold improvement in inventory accuracy or the step-function improvement in transportation data. Or the new controls on safety stock levels. Or the item data cleanup. Or any of the other data without which the "new system" would never have worked.

Should you implement new supply chain planning systems? New systems may be required to improve your performance: if your existing systems lack the fundamental logic to match resources with demands, and communicate what is really needed and when, then they are probably due for an upgrade. But it may be that your systems are adequate and that you’ll get better results by focusing on basic data rather than a complete systems replacement.

Do you have an active and on-going process for monitoring the basic data upon which your supply chain planning system depends? Do you really know how accurate your data is? Or even which elements to measure?

There’s no time like the present to find out. In the chart, you can see some of the specific areas you should be monitoring, along with the minimum acceptable level of accuracy needed to operate a modern resource planning and scheduling system.

 

If your data is already accurate, great! You’re ready to move on to other problems. But if it isn’t, fix it now. It may be the simplest thing you can do to generate the results you want.