Knowing your data is better than believing it

“You’re sure, or you know?”
-Stanley Tucci in the BBC movie “Conspiracy“

As developers, DBA’s, and analysts, we’ve all been asked this question in some form at one time or another.  We know the feeling of queasy uncertainty that comes with responding, “I’m sure.”  We know the sturdy confidence that comes with responding, “I know.”  So why would we ever opt to answer anything but, “I know”?

There are advantages to being sure about our work:

• We get more work done in the same amount of time.
• We deliver work with low risk of error.
• We develop a reputation for delivering work faster or ahead of schedule.

But consider the consequences:

• Our work is more likely to need revision, so the perceived time savings is an illusion.
• Business costs increase because of decisions made on our errant data.

And most importantly…

• We develop a reputation as producing unreliable output.

Don’t say we didn’t warn you

In a mission-critial environment, this last bullet point is really all that matters.  As soon as your company can count on not counting on you, you’re doomed.  Your career path there consists of two feet of sidewalk and a large brick wall guarded by a mean dog.

Fortunately, if you haven’t done incalculable damage to your reputation or your company, here are three things you can start doing immediately to remedy the situation.

1. Ask questions until you know the question being asked

There’s a process many of us have been through that goes something like this:

(client sketches dataset -> you query -> you report -> client asks why it doesn’t look right -> missing parameter discovered)

The answers are right but the question is wrong.  We can spend several hours looping through the diagram above, or loop through step 5 (missing parameter discovered) and arrive at the coda in several minutes.  Which would you rather do? (Don’t answer that.)

Once you’ve arrived at all the parameters, show your client the list of parameters and the expected look of the output.  If they agree it looks right, congratulations.  You’ve saved everyone involved a lot of time by understanding the question up front.

2. Check your work

No, I mean really check it.  Yes, it will take more time.  Tell your boss you’re going to need a little more time to verify or test your work.  In a mission-critical environment, no rational manager will trade consistently that little extra time in return for increased skepticism of your work, your reputation and theirs.

3. Admit your errors quickly to all concerned

Everyone screws up once in a while.  As important as it is to get it right the first time, it’s equally important to react with urgency when you don’t get it right.  I once sent out bad data to twenty-two department administrators.  As soon as I realized the mistake, I sent e-mail to each of them explaining the mistake, apologizing, and telling them when to expect corrected data.  Then I went down the phone list and called each one to make sure they’d seen my e-mail.  While I lost some credibility for providing the bad data in the first place, many of the admins expressed appreciation for my efforts to inform them of the error.  As a result, those admins know that when my data doesn’t have integrity, at least I will.

While we can’t promise perfection to the people who depend on our data, we can at least give them the trust that comes with saying, “I know.”