Of all the “inspirational” little vignettes that disfigure management literature and LinkedIn streams, few are as hackneyed as the tale of JFK touring NASA headquarters in 1961 and on asking a janitor what he did for NASA, receiving the reply “I’m helping to put a man on the moon”. So far, so Dilbert.

Yet clichés are clichés for a reason. At the very least, the failure of organisations where there is no commonly shared and understood goal is a commonplace, and the alienation of workers who see no connection between their activities and a meaningful end goal was articulated by Marx, if not Ecclesiastes.

The reason why we are so cynical about “higher purpose” mantras is that they often aren’t really true. Too often, the real higher purpose of organisations is about securing resources, profit, prestige or power. So what has interested me in my conversations with organisations that use data well both here and abroad is that all a) have a clearly defined higher purpose and b) staff within the organisations align their work to this without prompting. How has this happened?

My reflection is that these organisations plan and act explicitly to achieve the higher purpose. Typically, potential lines of work are tested against the higher purpose, and if they don’t advance it measurably they are dropped (however otherwise attractive the proposal). The success of a project is judged by how well it advances the goal, not how well the project milestones are ticked off.

As a thought experiment, I set myself the challenge of defining a higher purpose for the shift in use of data that I advocate and the changed behaviour, and from that, determining the types of actions that need to be taken.

Based on all I’ve been saying to date, the higher purpose for achieving a transformed use of data might be that, “By 2025, the New Zealand public sector sees data as a source of insight rather than a means of control”.

To achieve this, I’d argue we need to do five things:

  1. Stop arguing about the validity of individual data sets and precise definitions of indicators and instead use an agreed range of data, in rigorous ways based upon an agreed set of standards. It is critical for data owners to rigorously and consistently outline what the data set contains, and what it can and can’t be used to show.
  2. Within each public sector agree the “monitoring” measures and automate them in as close to real time as possible. Success here might be that no more than 30 per cent of analyst time within core ministries, crown entities and public bodies is taken up with tasks associated routine performance monitoring. 
  3. Open source the measures and methods. This builds confidence through transparency, replicability and comparability of method, and reduces time spent building from scratch. 
  4. Make decisions in line with the higher purpose. Only innovate with data if it is providing insight that we don’t currently have.
  5. Evaluate whether the higher purpose has been served by what we have done. What new insights have been generated? How has the world been changed as a result? Rigour and courage are required.

This last would, in my experience, be a challenging transformation. Accountability for public sectors has tended to be in terms of delivering agreed products (hence “deliverables”) rather than improving lives (or transforming working practice). This is largely because the former is straightforward to measure and the latter isn’t. Yet hard though it is, this type of measurement is implicit in, and far more consistent with, the Leadership Success Profile domains of strategic leadership, system leadership and delivery management.