Establishing Anything but Average

It is well-known that there are three essential elements on which you judge a service or product: Its price, the speed of delivery, and the quality.  There is also a well-known axiom, that you can only have the best from two out of three.

Since data is the foundation of our understanding of problems that we are trying to solve and how we identify the value of our proposed solutions. The collection, management and use of data in transport policy issues and infrastructure development have, for too long, focused on price and speedy delivery at the high expense of quality.

We are spending billions of dollars, supposedly to improve the efficiency and living standards of our communities, based on a barely average approach to ensuring that we start on the right foot with useful data.

The private industries now have many good examples of how they have perused detailed and accurate data to improve their profitability.  Government’s must learn from this in order to achieve long-term community benefits.

Sadly, there are three ways in which Government data, and how we use it, can be considered only “average” at best.

Report Card: Must Put In More Effort 

Our data is “average” in the sense of being ordinary or mediocre.

It starts at the beginning when we define the things we want to measure. Too often it is to fit preconceived ideas or a simplistic measurement of a small part of a complicated issue.  

We then haggle to get the lowest price without considering what this does to the quality.

Once the numbers are in, we often just take them at face value, ignoring (or certainly not paying for) the time and effort necessary to ensure transparent and credible results. Concerned professionals have told me that up to half the data collected by governments is worthless, or even worse, it is totally misleading.

The situation is even worse in how we compile, store and make data available. In many cases, we just file the data away or also hide it within organisations.  

Good data will not come from just good intentions or project management that shouts harder in order to get an impossible mix of price, timing and cost. It will only come from an informed and resourced approach that respects the value of doing it right in the first place.

The advent of big data has erroneously led to a belief that an extensive collection of numbers (which are then averaged) will lead to an accurate and complete understanding of issues and therefore the solutions we should adopt.

The large databases problem may obscure the real issues which can be activities at the extremities. For example:

1. they can hide false readings
2. they might be measuring something different to what you think
3. they may not be recording a representative sample and an average figure  

Big data can be a kilometre wide but only a millimetre thick: it can have a massive number of records of one aspect of an issue which fails to measure the diversity and complexity of a problem.  Even if the numbers do cover a range of activities, we then average them which blurs the diversity and the extremes.

Average “Analysis”