Data vs. Facts, Illustrated
There are two expressions that get used often in the lean world, one from Dr. W. Edwards Deming and one from Toyota's Taiichi Ohno. Dr. Deming was quoted as saying (even if he didn't originate it):
“In God we trust, all others bring data.”
“Data is of course important in manufacturing, but I place the greatest emphasis on facts.”
Ohno emphasized not relying on reports, but instead going to the “gemba” – a Japanese term that means “workplace” or “the actual place.”
Thanks to one of my favorite funny blogs, Failblog.org, I found a picture that illustrates it perfectly:
Here's a sign that's clearly wrong, given the snow on the ground. Is there a risk in our organizations, whether a factory or a hospital, that the data (in the form of a report or an electronic system) that we rely in data that's inadvertently incorrect? What if someone was making a decision based on a “management dashboard” that said it was 119 degrees outside?
In John Shook's class yesterday, he talked about facts – what do you know and how do you know it? So you think it's 119 degrees outside in January? How do you know that? From a report? Hmmm, not good enough. Go to the gemba. Do you feel the temperature first hand?
This is an old story from the 1995-1996 time frame, but it's one of my favorite GM war stories – how the plant production superintendent was fooled by perpetually faked data. I wrote about it 2007 in “GM Got Gamed.” The superintendent never went to the gemba in a meaningful way, he never saw the “fact” that production rarely hit a consistent 60 engine blocks per hour the way the faked data showed.
Do things like this happen in your organization?
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I agree about the crucial difference between data and facts. But that leads me to ask…
– How are facts stored in an organization?
– How are facts made available to others?
It can’t be the case that every fact must be confirmed by personal observation or we’d spend all our time in the observation stage. I think that data quality and reliability are essential to any organization (lean or not). This is the unfortunate Achilles heal of many organizations and leads to decision-making based on a fuzzy collection of subjective assessments rather than on facts.
One often-missed benefit of a lean implementation is discovery of how good the data is in an organization and especially the data that’s been the basis of business decision-making all along. I’ve worked with a lot of companies who were pretty uncomfortable with what they discovered when they compared their electronic data to reality.
Data is a huge issue. Thanks for bringing this one up.
Very good point! But, you know, data is usually incorrect either because we entered it incorrectly or we managed it badly.
We are responsible for our data (especially the one we create) and there are no machines and/or systems (yet) that can manage it for us. Data integration tools are very important and can help a lot, but we’re the ones building and configuring them.
At the onset of their lean journey, people often feel overwhelmed by the breadth and depth of the various lean principles, systems and tools (I know that I did). I tell them that they will develop in their understanding as they study, see and do, but perhaps the single most important thing that they can bring (along with intellectual curiosity, passion, respect, humility, etc.) is common sense. Most people think they have that! Common sense, “native good judgment,” is typically unvarnished and unsophisticated. There’s nothing as unsophisticated or powerful as going to the gemba and observing the reality or facts before you. So, here’s to common sense and facts.
.-= Mark R Hamel ´s last blog ..The Kaizen Promotion Office Does What? =-.
your mistake, though, is to confuse data with information. In the above example, the display showing 119 degrees is a source of information. Data for that day, from NOAA for example, would give us the correct temperature and expose the misinformation.
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