A friend of mine has a nifty parlour trick.
At educational conferences—where discussions about measuring learning outcomes can stretch endlessly—he suddenly stands up and asks: “What is the size of this elephant?” The room falls silent. Participants look around, confused. When someone inevitably asks, “Which elephant?”, he smiles and replies: “Precisely. When will we stop trying to measure the elephant before even bringing it in? Let us talk about measuring quality after we have done something to create it.”
His point unsettles many officials. For decades, leadership in education systems has been interpreted primarily as an administrative role—focused on monitoring rather than transforming learning. In such systems, measurement often becomes the centrepiece of discussion even when the deeper work of improving learning has barely begun.
Measurement is critical to improvement. It can point to the actions needed to strengthen capacity, support learning processes, provide feedback and redesign systems. Measurement helps test the assumptions behind policies and refine them in the light of evidence.
But measurement only has value when it is part of a coherent effort to improve practice. If programmes are implemented without careful attention to context, without a credible theory of change, and without a plan to build capacities or create feedback loops, the data collected becomes largely irrelevant. It sits in dusty cupboards or in terabytes of data on forgotten hard drives.
In such situations, measurement often serves a different function. It becomes an instrument for punishment or a tool to validate untested prejudices. Unsurprisingly, people begin to fear what it might be used for. Data collection, design and interpretation are quietly sabotaged, and over time widespread cynicism develops about official measurement processes and the information they produce.
This serves us ill as a nation. Without reliable information, systems are forced to fly blind into the accelerating storm of change we experience every day. In our own work, we often ask officials—who receive volumes of reports from their teams—what they can say with confidence about their programmes. Most often, the honest answer is: very little.
When data is used meaningfully, however, it transforms how systems learn. Numbers, graphs and visualisations can reveal progress, identify gaps in implementation, guide capacity-building efforts and inform policy action.
In our own programmes, we distinguish between process data and outcome data. The distinction is partly artificial—every process measure is itself an outcome measure. But a careful distinction here helps us construct a causal chain: understanding what must be done now to produce better results later. This clarity strengthens programme design and focuses attention on what is critical today.
Of course, at any point, some initiatives will be too young for meaningful measurement. For the time being, we describe them through stories, hoping that soon they too can be examined through a measurement lens.
At the same time, we remain mindful that many of the most important elements in education—trust, motivation, relationships, meaning—are not easily measured or quantified. These are often the very conditions that determine whether change takes root.
Measurement must illuminate learning, not distract us from these deeper foundations.
