Operational Excellence practitioners deal in facts. These are the real facts of science, processes, measurements, and data, not “alternate facts” that show up from myriad unreliable sources and may have zero basis in reality. What happens when we get the facts wrong?
Major problems: from consumer perception…to death
It used to be that “all the news that’s fit to print” was published in newspapers after multiple sources verified accuracy. When Walter Cronkite signed off his news broadcasts saying “And that’s the way it is,” we trusted he was telling us the truth. Opinions stayed on the editorial page where they belonged. Satire showed up in cartoons.
Today the open structure of the internet means anyone can say just about anything. Other people—or bots—may repeat a story so much that it takes on the appearance of truth even if it comes from a basis that is totally fabricated.
Consumers yearn for honesty. They expect and deserve the organizations they deal with to be reputable and deal in facts. Once an organization loses credibility in the eyes of consumer, it’s difficult, if not impossible to regain. The organization and its workers can face serious consequences.
Let’s look at several cases related to organizational use or misuse of data:
Volkswagen cheated on emissions controls by installing devices that controlled emissions during lab testing but allowed unacceptable levels of harmful exhaust during actual road use. The company released data showing compliance with the Clean Air Act, but a West Virginia University lab proved that data falsely represented actual operations.
Volkswagen now has to deal with millions of “bad” cars and faces billions of dollars in settlement costs and possible criminal charges. The company even made consumers complicit in its sins. For years, environmentally conscious consumers wanting to comply with emissions controls were actually putting up to 40 times the U.S. limit of pollutants in the air. Will these consumers believe Volkswagen again? Will they ever buy Volkswagen cars in the future?
Tobacco Industry Research Council
In the tobacco industry, when medical studies began to indicate that smoking caused health problems, the major companies formed the Tobacco Industry Research Council, ostensibly to counter health concerns. In effect, their studies recommending “healthy” cigarette options (filtered and low-tar) allowed the companies to increase sales without eliminating health problems.
Many thousands of people have suffered and died from the effects of smoking and second-hand smoke. According to the American Cancer Society, smoking continues to cause 1 in 5 deaths in the U.S. Recently e-cigarettes and vaping have been introduced as “safer” smoking alternatives, especially for those who are trying to quit smoking. But young people are using these “safe” smoking devices at alarming rates. Are these choices safe in any way?
Inadequate testing of the wonder drug Thalidomide kept hidden the harmful impacts to a fetus, yet the drug was released aggressively and sold over the counter to prevent morning sickness among pregnant women. Worldwide in the early 1960s, thousands of moms who took the drug gave birth to babies with shortened limbs and other birth defects. After this catastrophe, the U.S. FDA implemented requirements for proof that drugs are safe and effective before they are marketed.
NASA's Challenger Launch
While limited data in the space shuttle program indicated some negative impact of cold temperature on O-ring performance, the 1986 Challenger launch proceeded on a day when temperatures were well below the testing range. The resulting failure killed the seven people on board and put the shuttle program on hold for nearly three years. One painful lesson learned is that conclusions should not be drawn beyond the range of data gathered.
In 1999, NASA lost a $125-million Mars climate orbiter because the two teams involved in the project used different units (metric vs. English). According to NASA: "The problem here was not the error, it was the failure of NASA's systems engineering, and the checks and balances in our processes to detect the error.”
These examples demonstrate a lack of data, misuse of data, or imperfect execution.
How to support fact-based improvement
Clearly organizational leadership has a key role in nurturing an ethical culture and providing the resources that will prevent problems like those above. OpEx too has important roles to support fact-based reality.
1. Use systems thinking.
Do risk assessments and “what-if” scenarios to consider possible outcomes (effects) before making or approving changes (causes). Look at operations as a flow rather than as individual silos. At a high level, a balanced scorecard helps to ensure important priorities are not forgotten with a focus only on the bottom line.
2. Create fact-based operations and communications.
Don’t rely on hearsay or assumptions. Help to ensure data points are good. Use appropriate methods in setting metrics and goals and use sound methods for data collection. Use statistical process control (SPC) to identify outliers and trends. Drive to reduce variability and build reliability. Electronic systems and tools can help track performance and quickly signal areas that are performing other than as expected so investigation can be done.
3. Use Lean to keep the workplace organized and efficient.
Remember that the “shine” element of 5S not only helps the area appear clean, but also provides quick visible signals when something happens to mess up that cleanliness.
4.Benchmark internally and externally.
Are good results real or do they have assignable causes? Often if something looks too good to be true, it is.
5. Drive for root cause and fix it.
Use problem analysis, potential problem analysis and other tools such as FMEA to truly understand issues. Never let a Band-Aid be used as a fix to a problem when solid investigation and correction of underlying issues is needed.
6. Be a change agent.
Help people to understand the importance of data completeness and accuracy. Workers are not being asked to collect data for the sake of filling out a form, but because they are providing critical information for the operations and ultimately for the customer. Make sure any data requested are truly needed, of course.
7. Drive out innumeracy.
Show people that data are not just numbers on a page but are actually meaningful and alive. Help people want to understand how to interpret the information they’re dealing with and give them the tools (e.g. basic quality training) to look at numbers visually and make sense of them. Encourage questions and investigation rather than blind acceptance.
8. Reinforce desired behaviors.
Tie data-related actions to strategy, vision, and values. Support not just the end results of positive outcomes, but also day-to-day diligence that provides information. Remember that a bad outcome is not a failure; it’s an opportunity to learn about what does not work.
9. Be a data watchdog.
Don’t let data be accidentally misinterpreted or maliciously misused. Remember the adage: “Figures don’t lie, but liars do figure.” Correct those who misunderstand the facts. Raise conscientious objections if people choose to misinterpret data. In the extreme, you might have to be a whistle blower and go outside the organization when ethics violations require action.
To paraphrase George Orwell’s writing in 1984: “He who controls the data controls the future.” Let’s make sure we use good data, real facts, honest intentions, and flawless execution to drive to a future of integrity and effectiveness.