Chris ConwayChris Conway
Chief Architect, Quantiv

The UK general election takes place in two weeks. For many, mention of this political event might provoke a heavy sigh, but for anyone fascinated by numbers, the nationwide ballot is heaven-sent.

In the run-up to the 4 July poll, every aspect is being put under the microscope, like the parties’ policies, opinion polls, and voter priorities and intentions. And that scrutiny usually involves at least some quantifying, even if some of the uses of these numbers are often unhelpful, misleading or just downright incomparable. For example:

  • “50% of this compared with two-thirds of that”
  • A “2% decrease” – or should that be a “decrease of the rate by 2%”
  • A (very) large amount that turns out to be a (very) small percentage

But even if voters do persist and manage to pick their way through the finer points of these metrics, the election itself then represents something of a paradox. Because for all the numbers used in the campaigning, the vote itself is remarkably simple.

Indeed, the final choice is almost one-dimensional. In each seat, the voters pick a candidate from a (very) short list.

In the UK, we do at least have multiple parties involved, so we’re not quite at the binary decision of systems like the U.S. presidential election. But we don’t use proportional representation, and instead elect local representatives and then use first-past-the-post to identify a party with a majority. And so the result can often come down to a straight fight between the two largest parties.

How do voters make their choice?

What’s remarkable is voters do manage to distil the almost infinite number of factors into a simple decision. Some of this will come down to non-numeric attributes like policy descriptions, track records and personalities (so there are still some things that can’t be quantified!).

But some will also come down to individual voters selecting particular metrics to help guide their decision. Some will prefer to consider tax rates, while others will think about spending. There are some who will need help now, while others will want support later. And everyone will have their preferred locations and projects.

The metrics used will vary from person to person, and given the number to choose from, it’s possible no two voters will use the same criteria. (You could argue it’s this variety that gives the system its strength.)

But what the selections will have in common is they provide each voter with their own personal way to compare the different candidates and parties. In effect, they’re using certain specific factors as indicators of their overall preference.

At first sight, this could seem to be a very hit-and-miss approach. For example, there’s no particular reason a party’s policy on health should be indicative of its approach to transport. However, voters seem to have become adept at knowing which factors are connected (so one aspect can be used as an indicator for another) and which are indeed separate (so both are needed).

Human intelligence, or at least experience, is usually good at making these distinctions, and not only in elections but in other circumstances too. Those summer sporting events will almost certainly show similar traits, with results predicted based on only a small number of critical factors. And organisational performance can often be checked using only a small number of critical metrics.

Navigating the election data

In effect, although there can be vast amounts of data associated with each system – such as an election, sporting event or organisational operation – it’s actually only necessary to use a small amount of this data to understand how the system will behave. So, rather than worry about the ‘big data’, it’s more important to worry about the ‘good information’.

However, big data isn’t unnecessary, because it’s still very helpful in identifying patterns over long periods of time. But when the patterns are known – sometimes instinctively or sometimes through that detailed analysis – not only is it wasteful to collect unnecessary data, it’s also distracting, or ‘noisy’.

Helping you identify and define your ‘good information’

At Quantiv, we understand this distinction because it’s at the core of what we do. Our NumberWorks method makes identifying and defining ‘good information’ easy, while our NumberCloud platform includes robust mechanisms to collect and expose contextual information about significant organisational activities and events.

In short, we know the numbers that count. But it still doesn’t make deciding on a vote any easier!

Get in touch

To find out more, contact our team today on 0161 927 4000 or email: