What an average doesn't tell you

Recently, I had a hunch that the average age of males was lower than the average age of females. My logic was that women tend to live longer than men and that slightly more male babies are born than female babies. I wondered if my reasoning was correct so I downloaded the demographic statistics for NSW from the Australian Bureau of Statistics and I found the following:

• There were 4.3% more males than females under 31 years of age
• There were equal numbers of males and females aged 31 years of age
• There were 6.3% more females than males over 31 years of age
• 41.2% of the population were less than 31 years old while 57.4% were more than 31 years old

When I crunched the figures I found that the average male is 1 year 8 months younger than the average female. So my hunch was correct. But the question is: what does this tell us about any given person?

The answer is: nothing!

Averages are about populations not about individuals. So if you were to see a statistic such as "Males are on average 1 year 8 months younger than females", you aren't being given an answer so much as a provocation to ask "Why would this be the case? What does it mean?"

When you are surprised at an average then it may help you to surface your assumptions about whatever it was that was being measured.

For instance, if I were to ask you what the average height for a human being was, the chances are that you would say something like 5'2" or thereabouts. So it would surprise you if I were to tell you that the true figure is under 5'. I will explain this claim in a moment, but first would it surprise you to learn that short people often have lower literacy levels than taller people? Yes?

Well interestingly the reason for both of these statistics is the same: children are human beings too!

Most children are under 5' tall and most childen have lower literacy levels than adults and these two facts result in the given statistics. So if you were surprised at the claims I made, it would be because you assumed that we weren't counting children in the averages. Even if we weren't aware of it, we implicitly assumed that we were talking about adult humans.

This can be true of almost any average. The question we always need to ask is: what is the true population that is being averaged? What assumptions are we making about this population? Are there groups we are excluding which we should be including? Does it make sense to use a single average when you are dealing with a 'mixed' population (e.g. adults vs children, males vs females). Does comparing separately calculated averages lead us to ask new questions about the reasons for any differences? Are the reasons obvious or do we need to dig deeper?

The other question is whether we are comparing the right averages.

In Australia, a serious issue is that average Aboriginal life expectancy is significantly lower than that of other Australians. However is this the right comparison? If we were to segment the two populations by socio-economic level would we find that the issue isn't race but poverty i.e. that people in lower socio-economic groups have much lower life expectancies than those in higher socio-economic groups? In other words, the underlying reason may not be racial but economic. Whatever the answer may be, it determines what sort of strategy you use to approach the issue: do we directly target health services to Aboriginal people or do we adopt a broader strategy of reducing poverty across the board?

I don't know what the answer is, but I raise this issue as just one example where the populations you choose for comparing averages can make a significant difference to what strategy you use to investigate the causes of any differences and the consequential strategies you adopt to deal with such causes.

Averages are one of the simplest statistics to calculate and this is one of the reasons that they are so frequently used. However they may conceal differences and assumptions that need to be surfaced if you truly want to understand what is actually going on.

Legacy processes - Don't let past solutions undermine future performance

Two stories to ponder:

Story #1:

A young girl is watching her mother prepare a ham for Thanksgiving. Before she puts the ham into the pan, her mother cuts about six inches off of the end of it, and throws it away. The girl asks her mother why she cuts the end off the ham. Her mother replies "I'm not sure, but that is how my mother did it". So she approaches her grandmother and her why she cut the end off the ham, before preparing it. Her grandmother replies "I'm not sure, but that was how my mother did it." In one final attempt, she approaches her great grandmother and asks why she cut the end of the ham, before cooking it. Her great grandmother replies "We only had one pan to cook with in our day. I had to cut the ham, so it would fit in the only pan we had."

Story #2:

The random wanderings of a calf formed a crooked trail through the countryside. Because this rough trail was slightly easier, people started to use it and it became a dirt track, then the main street of a small village, the main road of a small town and eventually three hundred years later it had become the crooked meandering thoroughfare of a city (For a more poetic account see the poem Cow Path )

What do these stories have in common? In one case a temporary limitation and in the other a random unthinking act determined the future actions and pathway of those who subsequently followed, who followed without thinking about why they were following that path.

A less than ideal decision made years before by a manager or programmer, perhaps determined by a set of circumstances that was either misunderstood at the time or which has long ceased to obtain may result in below average performance by the organisation and its employees for years to come. It may also be the sub-structure for future decisions that end up locking it in place.

This is why at times processes may need to be completely re-engineered from the ground up since the assumptions underlying the current process may be fatally and irretrievably flawed.

There may be barriers to doing this however.

A process wich has been around for a long time has the comfort of familiarity and an air of rightness about it since it may be all that those performing it have ever known. Even if it will make their lives easier, people may well resist a change that seems to go against everything that they have been taught about the right way to do something.

We can see some examples of this in sports:

• the 4 minute mile was broken only because someone wouldn't believe the accepted wisdom that a human being couldn't run a mile in under 4 minutes.
• high jump records were broken when the Fosbury Flop was introduced , challenging the accepted wisdom that the right way to go over the bar was forwards.
• until 1844, the fastest European swimmers used the breaststroke. But in that year two Native American swimmers outclassed them in a competition in London using what eventually developed into and became known as the Australian Crawl ( Surrounded by Geniuses Dr. Alan Gregerman)

In each of these cases, the sports community concerned believed that they had achieved the best that was possible. And in a sense this was true: the best that was possible doing things the way they had always been done and assuming what had always been assumed. And yet it was possible to do better by questioning these assumptions and trying something different.

Dr. Gregerman asks:

What if there are more brilliant ways to do things? And if those more brilliant ways are all around us simply waiting for us to discover them?

One of the difficulties in making these discoveries is that nothing is more invisible than what we take for granted and the things we need to change may be almost impossible to see since they form the very background against which everything else is decided.

What this means is that sometimes we need to take a step back and seriously ask ourselves whether we would have designed a process this way if we were starting from scratch. We need to ask ourselves whether the basis for a process is grounded in the reality of what is required or if it it only what we have unquestioningly assumed was required.

Sometimes this may require new eyes, the eyes of someone who hasn't done the work before. Questions asked by someone being trained in a job may yield unexpected gold because when they ask "Why do we do that?" in relation to part of a process, it may be the very question that should have been asked long before.

So if you ask soemone why do we do this and the answer is "I don't know" or "It's the way we've always done it" or "It's the way I was trained to do it", alarm bells should go off since none of these answers justify continuing to do it.

In an article in Bloomberg Business Week Rick Wartzman put it this way:

Many times, managers become preoccupied with how they are doing things. But what's equally important—maybe even more important—is what they are doing in the first place. As Drucker noted: "There is surely nothing quite so useless as doing with great efficiency what should not be done at all."

And I guess this is my main point. We need to look at how our processes square with the demands of current reality and ensure that we are doing the most effective thing given those demands.