The Problem With Quality

1. Meeting the spec[ification]
2. Documented adherence to established [process] norms
3. The product's effects are primarily positive (for example, it tastes good and doesn't make me ill)
4. I'll know it when I see it

Multiple choice: which of the above (choose only one) is the definition you want applied to your new car?

Does the answer change if we apply the definition to your morning cup of coffee?

Last question: which definition do you apply to the next example of "business intelligence" that comes before you?

I have two points in mind. First, defining quality is not an exact science even within a specific context. Second, #4 may be the deciding factor regardless of #s 1-3. In the end, the consumer/customer merely has to say, "That's not what I was looking for" to relegate a product to the trash heap. We all know that it does no good to say, "This is what you asked for" (meeting the spec) or "I did it just like you told me" (followed established procedure) or "One won't hurt you" (tastes good and not sick--yet).

So what is quality and especially, what is data quality? How we obtain data quality is completely dependent on the answer to this question.

I'd like to suggest that we divide the question in order to produce at least one useful answer. If we examine data quality from the perspective of a computer and its logic, we can come up with an answer that will allow us to progress. The second perspective is obviously the consumer/customer or the human perspective.

Recently I received an email with what at first glance seemed like an innocuous statement full of typographic and/or spelling errors, but when I actually looked at it, it was a nearly perfect illustration of a principle I have been talking about for years.

Teh hmuan mnid is cpalbae of miankg snese of amslot atynhnig taht ftis smoe bisac ptratnes.

This is the principle that draws the line between computer logic and human "logic". It is also what makes programmers (an outmoded term, I know, but best suited to the point I'm making) so vitally important. There is only one role in the continuum of roles involved in producing an information system product that must bear the full weight of responsibility for the integrity of the data quality at the boundary between computer and human. That role is best thought of as programmer.

Unless you earn your living as a programmer, some alarms may be going off. In fact, if you are a programmer, some alarms should be going off. I earned a degree in computer science and made a living as a programmer. From there I moved into data modeling, data administration and database administration. Now I'm involved in data quality and governance. In all of that time, I have never come into contact with any training, education, book or even a job description that addressed my accountability for preserving data quality at the man/machine interface.

This may be a poor forum for this, but my intention is to change this situation right here. My next few posts will present some background on how a programmer might live up to this responsibility and some of the forces that will need to be fended off in order to make it a reality.

Next: Programmer as Data Quality Champion