Posts categorized "Metrics"

June 05, 2007

Surveillance and diligence

As I mentioned in a previous post I recently heard Atul Gawande talk about his book "BETTER: A Surgeon’s Notes on Performance".  He made observations about why some teams have much better results (in terms of patient medical outcomes) than others.

He highlighted two traits that seemed to be central to that success: "surveillance" and "diligence".  These traits are incredibly important in the software world as well, for much the same reasons as touched on by Atul.

I am not sure that "surveillance" is the best possible phrase to use, I prefer to think in terms of "active observation."  Whatever the label the concept is critical.  Here are some points to keep in mind when practicing active observation:

  • Don't depend solely on your own observations, enlist the broader team to take part in the process and listen carefully when they share what they are seeing.
     
  • Don't accept everything you hear at face value, question and probe, search for validating or contradictory data points.
     
  • Make sure you have a good consistent data set that lets you make comparisons over time and comparisons between different people and different projects.  When there is variation in that data set probe into it, even if the variation seems small.
     
  • Take advantage of your insights into well known patterns of misleading reports.  Some folks are modest and pessimistic and consistently make things sound worse than they are.  Others may tend towards self-justification.  In any case you need to look for these patterns and take them into account as you get new reports from the same source.
     
  • As you form conclusions based on these observations, test that conclusion, make predictions based on that conclusion and go look at the relevant data.  If your new data points don't support your prediction, than your conclusions are probably wrong.

Atul makes some key points regarding "diligence":

  • Diligence can be defined as "the constant and earnest effort to accomplish what is undertaken."
     
  • "People underestimate the importance of diligence as a virtue" perhaps because on the surface it sounds mundane and simplistic.
       
  • However, diligence is a "prerequisite of great accomplishment" and "one of the most difficult challenges facing any group of people who take on tasks of risk and consequence"

I agree wholeheartedly with these points and would add just a couple more regarding the practice of diligence. 

  • It is unreasonable to expect diligence from someone who does not understand why their tasks matter in the bigger scheme of things.
       
  • Having relevant and easy to understand metrics that are shared with the entire team, encourages diligence and continuous improvement.
       
  • Developing team practices that enable folks to get into a good rhythm and spend most of their time "in the zone" is critical to encouraging diligence.  There are lots of things (too many meetings, unproductive meetings, inconsistent goals/feedback, constantly switching assignments, etc.) that will pull folks out of the productive zone and discourage them from trying.
     
  • An out-of-context or irrelevant response to anxiety or social tension is called a displacement behavior.   I believe this term was originally from animal behavior studies, but it certainly applies to humans as well.  For example you may feel anxious about a deadline, doing the relevant work just reminds you of how hard it will be to make the deadline, which makes you even more anxious, so you find yourself reading Slashdot or reorganizing the source tree instead of actually working on the relevant implementation.  Team leaders need to give folks an open door and when they express anxiety or point out tension, leaders need to help them work-around those issues so they can pursue the tasks that matter instead of getting sucked into an eddy.   

Here is Atul's description of a Doctor who has mastered the arts of surveillance and diligence.  This describes an examination of a Cystic Fibrosis patient (Janelle) by her Doctor (Warwick).  Even though the specifics of this situation are far from the specifics of a software project, the mindset and basic skills shown here are extremely relevant.

Warwick pulled out her latest lung-function measurements. There’d been a slight dip, ... Three months earlier, Janelle had been at a hundred and nine per cent (she was actually doing better than normal); now she was at around ninety per cent. Ninety per cent was still pretty good, and some ups and downs in the numbers are to be expected. But this was not the way Warwick saw the results.

He knitted his eyebrows. “Why did they go down?” he asked.

Janelle shrugged.

Any cough lately? No. Colds? No. Fevers? No. Was she sure she’d been taking her treatments regularly? Yes, of course. Every day? Yes. Did she ever miss treatments? Sure. Everyone does once in a while. How often is once in a while?

Then, slowly, Warwick got a different story out of her: in the past few months, it turned out, she’d barely been taking her treatments at all.

He pressed on. “Why aren’t you taking your treatments?” He appeared neither surprised nor angry. He seemed genuinely curious, as if he’d never run across this interesting situation before.

“I don’t know.”

He kept pushing. “What keeps you from doing your treatments?”

“I don’t know.”

“Up here”—he pointed at his own head—“what’s going on?”

I dont know,” she said.

He paused for a moment. And then he began speaking to me, taking a new tack. “The thing about patients with CF is that they’re good scientists,” he said. “They always experiment. We have to help them interpret what they experience as they experiment. So they stop doing their treatments. And what happens? They don’t get sick. Therefore, they conclude, Dr. Warwick is nuts.”

“Let’s look at the numbers,” he said to me, ignoring Janelle. He went to a little blackboard he had on the wall. It appeared to be well used. “A person’s daily risk of getting a bad lung illness with CF is 0.5 per cent.” He wrote the number down. Janelle rolled her eyes. She began tapping her foot. “The daily risk of getting a bad lung illness with CF plus treatment is 0.05 per cent,” he went on, and he wrote that number down. “So when you experiment you’re looking at the difference between a 99.95-per-cent chance of staying well and a 99.5-per-cent chance of staying well. Seems hardly any difference, right? On any given day, you have basically a one-hundred-per-cent chance of being well. But”—he paused and took a step toward me—“it is a big difference.” He chalked out the calculations. “Sum it up over a year, and it is the difference between an eighty-three-per-cent chance of making it through 2004 without getting sick and only a sixteen-per-cent chance.”

He turned to Janelle. “How do you stay well all your life? How do you become a geriatric patient?” he asked her. Her foot finally stopped tapping. “I can’t promise you anything. I can only tell you the odds.”

In this short speech was the core of Warwick’s world view. He believed that excellence came from seeing, on a daily basis, the difference between being 99.5-per-cent successful and being 99.95-per-cent successful. Many activities are like that, of course: catching fly balls, manufacturing microchips, delivering overnight packages. Medicine’s only distinction is that lives are lost in those slim margins.

And so he went to work on finding that margin for Janelle. Eventually, he figured out that she had a new boyfriend. She had a new job, too, and was working nights. The boyfriend had his own apartment, and she was either there or at a friend’s house most of the time, so she rarely made it home to take her treatments. At school, new rules required her to go to the school nurse for each dose of medicine during the day. So she skipped going. “It’s such a pain,” she said. He learned that there were some medicines she took and some she didn’t. One she took because it was the only thing that she felt actually made a difference. She took her vitamins, too. (“Why your vitamins?” “Because they’re cool.”) The rest she ignored.

Warwick proposed a deal. Janelle would go home for a breathing treatment every day after school, and get her best friend to hold her to it. She’d also keep key medications in her bag or her pocket at school and take them on her own. (“The nurse won’t let me.” “Don’t tell her,” he said, and deftly turned taking care of herself into an act of rebellion.) So far, Janelle was O.K. with this. But there was one other thing, he said: she’d have to come to the hospital for a few days of therapy to recover the lost ground. She stared at him.

“Today?”

“Yes, today.”

“How about tomorrow?”

“We’ve failed, Janelle,” he said. “It’s important to acknowledge when we’ve failed.”

With that, she began to cry.

Warwick’s combination of focus, aggressiveness, and inventiveness is what makes him extraordinary. He thinks hard about his patients, he pushes them, and he does not hesitate to improvise.

I particularly appreciate the comment "... combination of focus, aggressiveness, and inventiveness is what makes him extraordinary"  That certainly applies to the software world as well.

                                                                               copyright 2007 Kerry Champion

February 28, 2007

Rationalizing Creatures

Good post by Justine Davies titled Talk To Me In Numbers on data driven management.  One comment that struck me was "A person can provide any number of reasons, incredibly well argued, as to why their sales performance is off."  It is true people are rationalizing creatures by their nature. 

Here is an interesting paper that touches on the neuroscience behind why we take so naturally to rationalization.

"many times we give 'rational' explanations to our "irrational behaviors', even knowing that we are betraying ourselves"

"In a well-known experiment, a group of women have to chose some nylon tights.  Once they were asked about their elections, they gave detailed, careful, and sensible explanations related to the differences in color, texture, or the quality of the material, without taking into account that the tights were identical.  The reasons for choosing them in fact were rationalized explanations built to explain an emotional behavior, that has no rational explanation"

The paper discuss that this tendency to rationalize may be driven by the division of labor between the two hemispheres of the brain.  The logical half of the brain gets in the habit of unconsciously building verbal explanations to explain the impulsive, reactive, emotional behavior of the other half.  That sounds plausible to me.  But as a practical matter how to effectively deal with this behavior is more important than the biological basis for it.

My experience is that from day-one you need to build a culture and set of practices that is data-driven and that is prepared to deal with harsh truths when the become apparent. 

Justin's post seemed aimed more at sales results, but of course this tendency to rationalize away what you are seeing comes up in other customer interactions as well, and gets in the way of really hearing the customer.

                                                                                 copyright 2007 Kerry Champion

February 27, 2007

Gates to spending

Another great post from Scott Maxwell, this time on common ways that startups burn money without creating value.  All his points are right on the mark.

Beyond Scott's points, I strongly recommend using crisply defined "gates" as a way to pace your burn.

Ventures typically define their spending based on the calendar:

  • hire the CMO in June
  • have first 4 support engineers in place by September
  • execute marketing launch and advertising campaign in October
  • hire first sales rep for Atlanta office by August
  • etc. etc.

I have found it works a lot better to schedule you spending not based on a date but based on an observable event, preferably an externally measurable event.

  • hire 1st support engineer after we have XXX customers installed, hire 2nd after YYY customers installed, hire 3rd after ZZZ customers installed
  • execute marketing launch after you have 3 reference users in place who are willing to talk publicly about their experience
  • hire the VP of Marketing after your Dir of PM and Dir of Corp Mktg, are clearly maxed out and no longer able to get the near term job done on their own
  • hire first sales rep for Atlanta office after at least 2 of your 3 existing reps have hit their full quotas for at least one quarter

Obviously the definition of the right gates will vary tremendously depending on the nature of your business, but the basic idea of using gates is applicable across all software ventures.

Taking this approach can seem like the harder path: 

  • You have to think hard about what are the right metrics to justify taking each step in your business plan.
  • You have to be constantly tracking your metrics to know when you should pull the trigger on each next step.
  • If progress is not tracking to plan you can not hide behind a veneer of bustling activity and feel good reports.
  • Sometimes you will find yourself beyond the curve on your hiring which  puts stress on the existing  team.

However while it may sometimes feel like the harder path, it is clearly the healthier path:

  • You don't waste money (and dilute equity) by spending too early in the cycle
  • Measuring metrics becomes are more integral part of how you manage the business
  • You are encouraged to have a more open honest conversation with your employees and your board.  Which builds credibility with both.
  • You avoid the stress that comes from over-staffing.  People want to contribute to the effort, if they are hired too early and there is not a productive way for them to contribute than they will rationalize themselves into doing "something" that makes them look useful.  That "something" is often counter-productive.

                                                                                 copyright 2007 Kerry Champion

What you want to see and what you need to see.

Scott Maxwell does an excellent job explaining the 10 best ways to lie with metrics.

Seth Godin recently posted on the disconnect between common metrics and what really matters.

Our previous post on how market definitions can be used to reaffirm existing biases is getting to a similar point.

Behind these cautionary tales the real issue is selectively using data to reinforce what you want to see.  Instead of using data to discover what you need to see.

Sometimes what you want to see is a specific conclusion, such as "yes it makes sense to inject another $10m into our current product focus, no changes needed there".

Sometimes what you want to see is a high degree of action and precision regardless of the conclusion:  "Look at all the metrics, look at the precise numbers, this is one organization that is really on top of things ... well no, we are not sure yet what action plan makes sense given these numbers ...".

In both cases you are missing the real goal: having a open minded data-driven process that sometimes leads you to surprising conclusions, but always leads you to decisive action.

                                                                                 copyright 2007 Kerry Champion


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