Making Your Customers Pay for Your Shortcomings

This one is a straight-up rant. Because this announcement incenses me.

AT&T Set to Roll Out Nationwide 3G MicroCell Availability Beginning Next Month
AT&T to begin nationwide rollout of 3G MicroCell in mid-April

Here is the letter that should accompany this announcement in next month's mailer to all AT&T customers:

Dear consumer:

We know our coverage is severely lacking. We've put a great deal of money into running ads to spin the facts and make it look like we have coverage comparable to our competitors. But that isn't helping because, well, our crappy coverage is a fact, not an opinion.

So now we have a new plan that we think you will really like. Rather than investing in our network to provide you the coverage you rightfully expect, we will instead take more of your money in exchange for which we will provide a device that allows you to use somebody else's network. We will, however, continue to charge you for these calls because you are using the micro device you purchased from us. Worry not, we've devised a month to month plan where you can pay us one flat monthly fee to use the device you purchased to make up for the crappy coverage we provided you in the first place.

This is what we call a win-win situation. You pay us more money and we give you effectively nothing in exchange for it.

Thank you for your continued patronage and bags of money.



Harmonic Mean is a Bitch

The Theory of the Weakest Link

A chain is no stronger than its weakest link, and life is after all a chain. - William James
A chain is no stronger than its weakest link. Metaphorically, this applies to teams. But in actuality, this is simply not the case. Humans have not only tenacity, but the ability to countervail one another. This is a quality that inanimate objects simply do not possess. We can and will compensate for one another for the good of the team. Links in a chain are incapable of sharing their strength. No other link can compensate for the weakest.

The key is knowing how to compensate.

Applying Averages

Quantifying Ability
So perhaps the weakest link theory does not apply. But you can't argue with math, right? Quantify each team members ability, average them together, and you get the normalized ability of the team.

On a scale of 1 to 10 in some arbitrary (but extremely meaningful and accurate) quantitive skill measurement:
Name   Ability
Alex       7
Casey      3
Chris     10
Jessie     4
Leslie     8
Logan      2
Pat        8

The Arithmetic Mean (Average) for the team is 6. Assume our scale is congruent with percentiles where 5 is average. We have a team that contains a clear prodigy and three above average individuals, yet the team's ability is barely above average.
Quantifying Delivery
I don't have a lot of respect for talent. Talent is genetic. It's what you do with it that counts. - Martin Ritt
This scale means nothing to us. Average ability? How does that map to work completed? Making it happen is where it's at, baby.

Let's assume for a second that our ability scale conveniently transfers to points per week completed.
Name   Points/Week
Alex       7
Casey      3
Chris     10
Jessie     4
Leslie     8
Logan      2
Pat        8

Again, the Arithmetic Mean for the team is 6. Nothing changed. What's your point, Doc?

Fair enough. There is no difference. But wait, there's more!

Accounting for Counter-vailing

We discussed earlier in the theory of the weakest link that man is capable of compensating for one another, thereby raising the strength of the weakest point in the group. Something a chain can never do. And this is a beautiful characteristic. But is it enough? And how does it work?

To be fair, we should assume that in covering for someone else, we diminish our own performance. If I assist you in completing a point, I sacrifice some of my own delivery rate. While I can certainly work a few extra hours to make it up, that pace is not sustainable.

We adjust the points per week. Our top performer is now our team lead. The top performer contributes two points to the others and our other high performers provide one each. The new scale looks like this:
Name   Points/Week
Alex       6
Casey      5
Chris      8
Jessie     5
Leslie     7
Logan      4
Pat        7

And our average for the team is still 6.

This sure would be swell, Wally. But their just ain't no way. I think something is wrong with the Beaver....

If we are pairing people up and one of the members has to effectively carry the other, there has to be some loss of velocity. If, however, we don't pair, we end up with a lot of re-work and lower performers stay lower performers for much longer. If you are in the camp who believes pairing is a bad practice, you will likely find significant ammunition in this article. I, however, do believe pairing is a fantastic practice. The dividends of pairing are significant and outside the scope of this article.

Getting the math right

Each developer is capable of completing a single point in some period of time. We can extrapolate that to points per week. When two developers share the work, we average the rates together. But now we have an interesting twist. We are trying to determine how long it will take these two developers to complete a single point, assuming they evenly share the load of that point between the two of them. This average is not determined by Arithmetic Mean, but by Harmonic Mean.
Digression into Harmonic Mean
Let me see if I can explain this.

You drive from your home to the store, which is exactly one mile, in exactly 4 minutes.
1 mile in 4 minutes is .25 miles per minute, which is 15 miles per hour.
You drove to the store at 15 miles per hour.

You return from the store along the exact same route, but this time it takes exactly 3 minutes.
1 mile in 3 minutes is .333 miles per minute, which is 20 miles per hour.
You drove back home at 20 miles per hour.

For the complete round trip, you drove 2 miles in 7 minutes.
2 miles in 7 minutes is .2857 miles per minute, which is 17.143 miles per hour.

Your average speed is not 17.5 miles/hour, but 17.143 miles/hour.

Back to our developers
This applies similarly to our developers.

Chris delivers one point in .5 days, which is 10 points/week.
Logan delivers one point in 2.5 days, which is 2 points/week.
Together, they complete 2 points in 3 days, which is 3.33 points/week.

As long as Chris and Logan are paired with Chris compensating for Logan as opposed to each of them augmenting the other, their average rate is 3.33 points/week. So we drop one of them from the Arithmetic Mean calculation.

So what does this do?
Name   Points/Week
Alex       7
Casey      4
Chris   3.33
Jessie     4
Leslie     7

Pat        7

The average for the team is now 5.39

Harmonic Mean is a Bitch

Harmonic mean lessens the impact of higher outliers, while emphasizing the impact of the lower numbers, especially as compared to Arithmetic Mean. So Harmonic mean favors the lower numbers. If this is true, doesn't it make more sense to have one of our slightly above average developers help train Logan instead?

Let's ask Alex to do it.

Alex can complete 1 point in 1.4 days.
Logan can complete 1 point in 2.5 days.
Together they complete 2 points in 3.9 days.

They have an average of 2.56 points/week.

Name   Points/Week
Alex    2.56
Casey      4
Chris     10
Jessie     4
Leslie     7

Pat        7

The average for the team is now 5.76

It does make more sense to have Alex pair with Logan. Theoretically, we could improve even more if we ask Casey or Jessie to pair with Logan. But now we are pairing all of our lesser performers together. Probably not a good idea.

Work Together

While my explanation may be a bit complex, my point is simple. You get a better return when everyone on the team pitches in and helps out. And you get a better return if you focus on pulling up the bottom numbers without significantly dropping the top numbers.

I am not advocating that you should only hire "top performers". If you do not grow your team from within, you fail to establish a sense of connection and purpose. And you set yourself up for huge salaries, huge egos, and ultimately high turn-over.

I am not suggesting you should silo your top performers and do not allow anyone to "bother" them. Not only will you have ego issues, but you will have established a cast class for the developers that will be difficult to break out of.

Most organizations take the top performers and put them in leadership roles where they are able to mentor and guide others. A single performer is expected to assist the entire team. Inevitably, those who require the most assistance, get it. We see an improvement as we pull the bottom up, but it is not nearly as significant an improvement as when each level pulls the one beneath it.

Don't blindly put your top performer in charge of the team. Odds are, they will not enjoy the role and your return will be less than optimal. Have the team work together. Encourage pairs with low performance disparity. Make sure your best performers pair with the next level down and so on.

Caution: Metrics change behavior

Measuring and reporting are important

I've often heard said, "That which you cannot measure, you cannot improve." And while I do believe this is a general truth, I think it fails to tell the entire story. It is not just about what we can measure, but what we actually do measure that is significant; "That which is reported, will improve."

What is not measurable, make measurable. -- Galileo Galilei 1564-1642.

Measuring and reporting influence behavior

Metrics give us feedback. Metrics show a measure of progress toward our goals. Metrics remind us what is most important. Visible metrics, ala Big Visible Charts, help to focus the team on what is most important.

...if I have quick access to key metrics every day, my creativity stays within certain bounds – my ideas all center on how to achieve our goals. -- Paul B. Allen

Access to key metrics provides an individual or a team a quick means of assessing progress and focusing their minds on what is most important. These can be excellent tools for influencing a team toward a desired goal or level of performance.

But the outcome is not always what we intend.

The Hawthorne Effect

There is a now famous study that was done in the early 1900s. Hawthorne Works commissioned a study of the effects of ambient lighting on worker productivity. The results of the test were perplexing. Essentially, worker throughput seemed to increase despite the level of light. High, low, medium; with each change, throughput increased. Once the study was concluded, levels quickly fell back to "normal".

The are several criticisms of this particular study, but the phenomenon has been repeated under different circumstances since.

The conclusion; that which was measured, improved. Effectively, because people were aware their throughput was being measured, it increased. In similar studies, people's throughput increased when they were knowingly observed but received no guidance or feedback. So they assumed throughput was the objective.

Rock On! Where is my plotter?

So this is pretty awesome, huh? Just let people know you are watching them and their productivity will soar! Throw up a few charts and you've got yourself a high-functioning team.

You wish

So here's the rub. An increase in throughput is not necessarily a good thing.

Why Not?
Do you believe your employees are slackers?
Do you think they lollygag about all morning, marking time until lunch and then perhaps featherbed it to 5pm before they skedaddle out the door?

If you do, then you have a significant problem. A problem that a few charts and some good old fashioned micro-management probably won't solve. But, hey, it is worth a try....

Our employees suck less than that

Good. So you have a reliable, forthright, responsible team of people. If this is the case, then you might do well to be a bit leery of easy increases in throughput. I'm not saying it is a bad thing, but that extra throughput had to originate somewhere. Perhaps it is less time spent in needless meetings. Perhaps it is better attention to priority items. If so...

Huzzah for metrics!


You've been warned

That which you measure and report will improve.

If what you track and report is one-sided, your results will be one-sided.

When you are on an agile team and all of your metrics are about velocity, you send a clear message to the team.

Go Faster! quality ain't all that important and value don't matter

Goodhart's Law

Goodhart's Law is a principle first defined in 1975 in a paper by Charles Goodhart, chief economic advisor to the Bank of England. Goodhart's basic premise is that economic indicators made into targets for the purpose of conducting economic policy, thereby lose their ability to serve in the desired capacity.

More succinctly put - When a measure becomes a target, it ceases to be a good measure.

Goodhart's law is applicable to both economics and sociology. It is a proven fact (law) that when you take an indicator such as velocity and you make it a target, you thereby eliminate it as a valid indicator.

Good Metrics

Measure value, not throughput. How many of the high-value stories were delivered, regardless of points.

Focus on your customer's determination of value. How do your metrics tie directly to their single highest priority?

Study trends, not moments in time.

Use metrics as a diagnostic tool. When a problem is identified, devise one or two metrics that will help diagnose and monitor the health of the issue. When resolved, stop measuring.

Do not record or report metrics for reporting sake.

Do not set targets for your metrics.

If you must report velocity, report only team velocity.