Continuous Partial Attention

Jul 22, 2010 by Phil Simon in Data Quality

A few months ago on this site, I ran a series about some of the causes of data quality problems in many organizations. To shamelessly plug my own work, the three pieces are:

• What Clients Don’t Tell Each Other
• What Consultants Don’t Tell Clients
• What Clients Don’t Tell Consultants

While each post addressed a separate topic, there was an underlying theme to the series: DQ problems on data migration projects stem from the differing agendas and priorities of different groups. What’s more, sometimes DQ is overlooked altogether. The question tends to be less about whether DQ suffers, but to what extent.

Beyond Data Migration Projects

Well, surely not all DQ problems emanate from data migration projects. What about DQ issues caused by the daily grind? Yes, we’re talking about DQ problems as a function of the status quo.

I was thinking about this very topic while reading Maggie Jackson’s excellent book, Distracted: The Erosion of Attention and the Coming Dark Age. Jackson describes a term originally coined by writer and consultant Linda Stone in 1998: Continuous Partial Attention (CPA). From its Wikipedia page:

Continuous partial attention describes how many of us use our attention today. It is different from multi-tasking. The two are differentiated by the impulse that motivates them. When we multi-task, we are motivated by a desire to be more productive and more efficient. We’re often doing things that are automatic, that require very little cognitive processing. We give the same priority to much of what we do when we multi-task—we file and copy papers, talk on the phone, eat lunch—we get as many things done at one time as we possibly can in order to make more time for ourselves and in order to be more efficient and more productive. To pay continuous partial attention is to pay partial attention—CONTINUOUSLY. It is motivated by a desire to be a LIVE node on the network. Another way of saying this is that we want to connect and be connected. We want to effectively scan for opportunity and optimize for the best opportunities, activities, and contacts, in any given moment. To be busy, to be connected, is to be alive, to be recognized, and to matter.

Now, it’s bunk to believe that CPA only causes DQ problems in the workplace. For more on the far-reaching consequences of our increasingly schizophrenic life, Jackson’s book (as well as Nick Carr’s controversial tome The Shallows) are well worth your time.

In my years as a consultant, I have seen firsthand how people enter incorrect time records, financial transactions, invoices, or other data into enterprise systems because they were distracted. Perhaps they were checking a newly arrived email, answering the phone, or talking with a cubemate while attempting to concentrate on the task at hand.

Nor am I taking the high road here. I certainly am guilty of occasionally losing focus. CPA-oriented DQ problems can stem from those with the best of intentions. For example, I recently played golf and needed four (yes, four) shots to get out of a greenside bunker, sullying an otherwise more than respectable back nine. While putting a painful eight on my scorecard, I had a hard time remembering just how many of my bunker shots failed before I put that stupid ball on the green.

Simon Says

Look, no one is perfect, nor are the systems into which we enter data. Yes, warnings, “friendly” reminders, and soft edits can minimize the damage that CPA does to DQ. To improve DQ in your organization, ask yourself the following questions:

• Does your culture emphasize rapid responses over accurate ones.
• Is management setting unrealistic expectations for its employees?
• Have cutbacks resulted in too few employees for too much work?
• Do you not have time to audit your data?

Hey, if any of these maladies affects your organization, there might not be anything that you can do about it: times are tight. Just don’t believe the information that comes out of your glorious systems.

Feedback

What do you think? Or are you too distracted to answer?

Tags: Data Quality, quality culture