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Join Elisabeth Hendrickson and me for our Developing Agile Teams workshop in Mountain View, California on March 1 and 2, 2007:

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Also check out the articles by the other presenters, and the AYE wiki that hosts an ongoing conversation for AYE enthusiasts.

I once defined information as “that which informs.” I was unsatisfied with this definition, because I didn’t have a good definition for “inform”. The dictionary definitions didn’t help (e.g. “to impart information” or “to impart facts”), so I turned to the web to seek other people’s ideas.

The definition I found most useful is Claude Shannon’s: Information is that which reduces uncertainty. I’ve refined Shannon’s definition by replacing the fuzzy word “that” with the sharper word “data,” which I define as descriptions of events or conditions.

For a while I was worried that this definition, focused so specifically on reducing uncertainty, was too limiting. Why uncertainty? And why reducing uncertainty? What about data that increases uncertainty? Suppose I discover a datum that invalidates a key “fact” that I thought I knew, and therefore leaves me uncertain about many other “facts.” It seems to me that that would be information, too.

I was tempted to substitute the more general word “alters,” and to find some variable more general than “uncertainty” as the central variable that is altered by information. But I’ve found that the limitation—the intense focus on reducing uncertainty—turns out to be helpful when I’m seeking information. In most cases where I’m gathering information my goal is to reduce my uncertainty. Of course, I may end up being informed by data I wasn’t seeking, and I may be informed in ways that increase my uncertainty. But when I’m seeking information, I’m almost always trying to reduce my uncertainty about something. This definition reminds me to ask myself which uncertainties are most important to me, and which I’m most uncertain about. Then I can focus more productively on gathering the data that may reduce my uncertainty.

I’ve made good use of this definition in a number of contexts. I’ve found it especially helpful in talking about testing, because a central purpose of testing is to deliver information, specifically information that reduces stakeholders’ uncertainty about quality.

The definition also helps me when I’m estimating. It invites me to assess my uncertainty about the variables that affect the thing I’m estimating. That assessment helps me to focus my search for data.

Another definition I like is Peter Drucker’s: Information is data endowed with relevance or purpose. Drucker’s definition emphasizes purpose and the relevance of data to our purposes. I’ve seen numerous metrics programs flounder because they started by collecting data rather than by clarifying their purpose for measuring. The end up collecting lots of data, and then not knowing how to make sense of it.

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I don’t think we need more research about the ill effects of multitasking. It doesn’t surprise anyone to learn that multitasking is at best ineffective and at worst dysfunctional. Everybody knows it already. I think everybody has known it all along.

If everybody already knows that multitasking slows the work, and if study after study merely confirms what everybody already knows, why do people keep multitasking?

Suppose I’m working on six different tasks that I’ve committed to six different people. If I want to complete all of the tasks as soon as possible, I will prioritize them and do them one at a time in priority order. Then I can tell Andy, whose task I’m working on first, that I’ll finish his task today. And I’ll finish it today. Andy will be very happy.

But what will I tell Bonnie, whose task I have given second priority? I’ll have to tell her that I haven’t made progress on her task yet. I’ll have to tell her that I won’t even start her task until tomorrow. Bonnie won’t like that. And I won’t like that Bonnie won’t like that.

And what about Francis, whose task I have prioritized sixth and won’t start until some time next week? Francis will be very unhappy. Francis will be furious. And Francis knows ways to make me very unhappy. This will not do.

So what’s a harried worker to do? Multitask! If I split my time among all six tasks, I get to tell all six people every day that I’m making progress on their important tasks. And I get to be sincere about that. And I get to avoid Bonnie’s unhappiness and Francis’s fury. Never mind that nobody will be satisfied until late next week. I’ll deal with that next week. For now, multitasking gives me a way to placate all of the people who are making demands of me. Multitasking delays the day of reckoning.

This explains how multitasking can remain so popular even though everybody knows it slows the work. The real purpose of multitasking is not to finish work faster. The real purpose of multitasking is to avoid conflict.

And that’s a tragedy, because multitasking does a lousy job of avoiding conflict. For one thing, our expectation of conflict is probably overblown. People are often more reasonable than we fear, as long as we keep them apprised of our priorities and plans. We reach for multitasking to solve a problem that often doesn’t need solving. For another thing, multitasking doesn’t avoid conflict but at best merely delays it. And by delaying everyone’s satisfaction, multitasking often exacerbates conflict rather than reducing it.

If conflict is the problem, multitasking is a poor solution. A better solution would be twofold. First, improve your skill in negotiating expectations and commitments. This reduces the likelihood of conflict. Second, improve your skill in resolving conflicts. This reduces the cost of the conflicts you can’t avoid. These are both enormous topics. But even a little improvement in these skills pays off far more than the ineffective and dysfunctional practice of multitasking.

This encouraged people to come to me with even more problems. Eventually they posed problems—not only about programming but also about other sticky issues—that I couldn’t solve off the top of my head. In order to understand the problem better so that I could solve it, I’d ask questions to get more information. Simple questions such as What have you tried so far? and What happened? and What else did you try? I noticed that often as people were answering my questions they would suddenly say, “Ah, I’ve got it!” It turned out that I didn’t need even to understand the problem, much less to solve it.

I began to enjoy helping people with those problems most of all, the problems that I had no idea how to solve. I learned to notice what puzzled me and to ask questions about my puzzles. Not leading questions with embedded advice (”Have you tried regrafting the Johnson rods?”), but questions simply to help me understand more clearly what was happening. And in answering the questions, people became more clear themselves about what was happening. I was surprised and delighted to learn that as people understood their problems better, they were usually able to come up with great advice of their own, advice that was far more useful than anything I might have offered.

Over time I’ve added other questions to my repertoire, questions not only about understanding the problem per se, but about understanding how the person is going about trying to solve the problem. Those “meta-problem” questions, such as the ones I asked Paul, the dream-home builder, seem to have great power to help people create their own advice. And they help people learn to examine their own problem-solving process, to jiggle themselves loose when they’re stuck so they can better solve their own problems.

One day Sriram poked his head into my cube, raised a finger, and said, “Dale, I— No, I got it.” And off he went.

Later I asked him what that was all about. He said, “On my way to your office, I was asking myself, ‘What questions would Dale ask me?’ I answered those questions, and I came up with the answer myself!”

I’d helped Sriram without even being there! That’s the moment I knew I could be a great coach. If only I could find a way to get paid for stuff like that.