Chris ConwayChris Conway
Chief Architect, Quantiv

There’s an old marketing adage along the lines of “I know half my advertising budget is wasted, but I don’t know which half” (a quote often attributed to American merchant John Wanamaker).

While this might make for a wry summary of the subjective nature of marketing, I suspect the phrase itself is only half true.

In practice, seasoned marketeers almost certainly have a good idea of the approaches that work and those that are a bit left-field. Moreover, I imagine that while to an outsider those ideas might seem to be random or based on intuition, in reality they probably have a more rational basis, albeit one that is most likely specific and personal.

And these rules of thumb aren’t confined to marketing. They’re present in all aspects of an organisation’s operations. They come from hard-won experience of how a company’s processes work and the ways in which their success or failure can be judged, often at a detailed or specific level.

Think of it like the ‘old grey whistle test’, a phrase that dates to when new songs were played to the grey suit-clad doormen in New York’s ‘Tin Pan Alley’. If the doormen (the ‘old greys’) could remember and whistle a tune, the song passed the test.

See how processes are performing

But those general principles are rarely the stuff of formal accounting and compliance reports (although those are needed too). Instead, they’re the methods people in an organisation have developed to be able to see, quickly and reliably, that the processes are working or where there might be problems. For example:

  • The volume or value of goods returned (perhaps even from a single postcode)
  • The reaction to new products or services by certain groups of people
  • The number of visitors at a specific time of day

All the above could be indicators of an organisation’s health. However, they may only apply to that specific organisation based on its own circumstances. Moreover, these indicators are likely to be closely guarded because they can be the organisation’s differentiator.

Often the rules have ‘hard’ numbers associated with them. Their use depends not on feelings but on properties that can be measured. And this means their values can be compared with those observed previously.

What are operational metrics?

They might start as a random set of personal ‘sanity checks’, but over time those numbers effectively form an organisation’s ‘operational metrics’. And while they may have some formality…

  • They’re not as specific as financial accounts (although they should have the rigour associated with their collection and use).
  • They’re not necessarily intended to be distributed as widely as KPIs (key performance indicators) – but they should still be easily visible and their context clear.
  • And yet they’re not as ad hoc as business analytics, although they might have been identified from them.

Furthermore, those numbers aren’t just useful to people. Or rather, the fact they’re useful to people is a strong indicator they could be valuable more widely.

To be successful, process automation depends on having good input data from which decisions can be made. So, if a rule of thumb is a good way for a person to decide on whether action is needed, then it will also work for a computer system.

And for a machine to learn about good and bad outcomes, it needs a way to judge. Using metrics that have already proved their worth with human arbiters provides a solid basis for such decisions.

Operational metrics may not feel as if they have the gravitas of formal accounting and compliance reporting, or the dynamism (superficial attraction) of analytics results. But, if anything, they’re more important to the running of an organisation than either of those. Being able both to identify and then to capture operational metrics reliably and consistently is essential to the success of any organisation.

Turn data into useful information

To find out more about how to identify and capture operational metrics, call our team on 0161 927 4000 or email: info@quantiv.com