Is Your Data Actionable?

The idea of actionable data came from one of the founders of the quality of movement, W. Edwards Deming, when he created the PDCA (plan–do–check–act) process. In this cycle of improvement, ACT is the last step before returning to planning.
Of course, the only way to act is to have actionable data, but the obvious question is what is actionable data and how is it different from other data.
Many companies gather data. One example of data that I will talk about more in the next blog is plate remakes. Any time an offset printing plate has to be made again it is referred as a plate remake and considered a good measure of prepress mistakes. There are a host of different reasons why printing plates have to be remade. At the highest level we could divide them into pressroom and prepress mistakes.
If we dive deeper, we could separate pressroom errors into: plates going blind, bent or scratched, out of register, or processor errors. In the prepress area we could categorize mistakes: as missing or wrong marks, missing or wrong copy, or missing or wrong color bar / target.
Gathering and monitoring data is not acting on it. While many people gather data, few companies make a change based on the data. In this example, we would likely identify the root cause, find the most common reason and train staff to handle it differently.
Leadership is not Measurement. It is Change.
When we identify the common denominator of leading companies, we find that leaders:

  • Choose better measurements (not simply production per hour)
  • Measure mistakes in more depth (such as the categories above)
  • Benchmark their performance against other companies
  • When they fare poorly, take action to increase their performance by acting on the data (find the root cause and change)

Ironically, many believe that simply measuring, gathering and compiling data is the best practice, but that is untrue. For example, one common measure of productivity are clicks from digital printing devices. Unfortunately, clicks do not provide actionable data to help make decisions to improve productivity.
For example, what if the same 12 jobs printed every month were printed incorrectly resulting in 30,000 sheets that had to be reprinted. Simply looking at click counts,  you could conclude the productivity was high. But if you compared total sheets printed to total sheets sold you might discover that there was 15% rework, which is unproductive.
The best practice is choosing measurements that reliably account for productivity and waste and then monitoring and comparing productivity / waste to similar companies. More importantly, when productivity or waste is below par, making a change and monitoring to determine if you helped or hurt your productivity (bottlenecks, errors, cycle time, maintenance, etc.)

Howie Fenton is the Vice President of Consulting Services for IMG. He helps in-plant and commercial printers measure, identify and overcome operational issues. To learn more about measuring performance, benchmarking to leaders, increasing productivity, and improving your value, e-mail

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