People Make Mistakes

NOTE: This originally appeared on this date at Quest Software's ToadWorld, on the expert blog "John Weathington's Quest for Compliance". The link to the actual ToadWorld article is at the bottom.

Everybody makes mistakes, even seasoned professionals. If you’ve ever tried to learn a computer language, I’m sure you can relate to what I’m talking about. Even if you have 20 years experience, it’s quite uncommon to just crank out code that works perfectly the first time. This doesn’t mean you don’t know how to program – it just means that even the best of us get it wrong sometimes.

I made a mistake myself, just today. I accidentally posted something to a forum board, in a place I wasn’t supposed to be posting. The rules are very clear, and I’ve been posting to this forum for a very long time, however today I wasn’t paying attention and stepped on the board moderator’s toes.

Whenever the human touch is involved, this is a risk we need to deal with. In Japanese, the term Poka-Yoke means “mistake-proofing”, and people in quality circles use this term to describe the actions taken to make sure errors are either avoided ( the ideal situation ), or made immediately apparent ( not as great, but still better than letting the error go unnoticed ).

When compliance is concerned, human error is a big issue. An inappropriate post in a forum board is pretty innocuous, but something like an “additional” zero in the wrong place can really wreak havoc. As data professionals, we need to be aware of how we can keep our business partners from making these kinds of mistakes.

An interesting architecture to consider is a “mistake database.” Now, nobody likes their mistakes thrown back in their face, but we’re all grown-ups here, and there’s a greater goal at stake other than protecting somebody’s ego. The idea of the mistake database is to capture all the mistakes people make, so we can analyze the data to make improvements for the future.

Records in the mistake database can be started with an automated process, however need to be finished by human intervention. For example, you could have an automated reconciliation control in place that would be upstream from your mistake database. Each time the control failed, a mistake would be recorded in the mistake database. In addition, people should be allowed to manually enter their mistakes as they are discovered.

At the time the mistake is discovered, at a minimum you should record:

• What the mistake is ( i.e. description of the mistake )
• Who made the mistake
• When the mistake was made ( date and time )
• What process was being performed when the mistake was made

The more additional information you collect about the mistake, the better. You will want to brainstorm on different factors surrounding the mistake, so you can identify possible patterns associated with the mistake. For example, capturing the department of the employee may give you the opportunity to highlight departments that have a high probability for making mistakes.

Shortly after the mistake is recorded, the following information needs to be collected by the person that made the mistake:

• What caused the mistake to be made
• What could prevent the mistake from happening in the future
• What will be done to correct the mistake

Although it seems somewhat like an issue tracking system, it is not. Do not make the mistake ( pun intended ) of mixing the two together. This system’s sole purpose, is for mistake analysis. That’s why we’re not concerned that the mistake was corrected, only in what is planned. This will give the analysis team insight into possible corrective and / or preventive measures to consider.

Periodically, a review should be done on this database by a Poka-Yoke team – a team responsible for error proofing the process or situation. This takes a combination of analysis and innovation skills. In practical terms, it is not required for these skills to be terribly acute. The data in most cases will speak for itself. If you see the same mistake being made, something needs to be done about it, and the best advice on correcting the problem will come straight from the people making the mistakes. There are occasions however, where either trends and / or causation are hard to spot, or you realize the trend but it’s hard to come up with a solution to the problem. In these cases, you may need to defer to the quality people ( e.g.  Six Sigma Black Belts ).

As long as humans are involved mistakes are going to be made. It’s your company’s option to allow the mistakes to continue, or to actively do something about preventing them. This article has given you some advice on how to assist your company in that direction. Start a simple mistake database today, and you’ll uncover obvious fixes in no time.

...read the article on ToadWorld