Better school improvement through Problem-Driven Iterative Adaptation

Guest blog written by Harry Fletcher-Wood

What do these have in common?

  • Crossrail
  • The Edinburgh Tram
  • The NHS National Programme for IT

All three ran late and overbudget: Crossrail is 3 years late and £2 billion overbudget; the Edinburgh Tram was half-finished 3 years late and £231 million overbudget; the NHS IT programme was abandoned after 10 years and £6 billion. Most big projects exceed their budget – because when people make plans, they are usually optimistic, overconfident, and under pressure to promise success (Flyvbjerg et al., 2018, 11-12). Promising plans pose subsequent problems.

Which brings me to school improvement. How many things did we drop from the School Improvement Plan and professional development programme last year – because unanticipated challenges took precedence? This example is so extreme – so obvious – that it risks undermining my point. The same thing happens every year.  We finish our plan, and – almost immediately – new priorities arise, external pressures shift, colleagues move role. Much of the plan is never fulfilled.

I’ve come to view a long-term plan as a necessary fiction. It may all come off: if it does, I’ll believe in it. I don’t mean we shouldn’t plan or prepare. I mean we should recognise that our foresight is limited: unexpected events will make fulfilling the plan hard; new insights will make us change direction. Planning a series of steps (and expecting they’ll actually happen) prepares us poorly. In this post, I’ll explain why, and suggest a better way to plan school improvement, drawn from development economics.

The problem with big plans and best practice

Consider these events:

When we face a problem, our instinct is often to create a grand plan to solve it: in this case, a multi-million dollar, internationally-supported project. We emulate best practice: we want a world-class case management system. For some challenges – like building schools – this can work. But it doesn’t work for complicated challenges rooted in human behaviour, such as getting multiple judicial agencies to cooperate, or ensuring students experience a great education.

Big plans pursuing best practice make organisations look good (helping them survive). But they neither help them meet their goals, nor build capacity to meet those goals:

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