How can we solve messy real-world problems?


What do we do when we have a situation – perhaps something has gone wrong?

We probably rely on experience – either fix things ourselves or get an expert in to solve the problem.

Most solvable problems like this tend to be hard problems, in the sense that they have clean edges.

For example, the tap is broken, a flood has disrupted shipments and we need an alternative or the printer is jammed and we have to get this proposal to the couriers in the next fifty minutes.

Many other problems are less well defined – how do we reduce our environmental impact while still growing the business, how can we develop people’s skills, what information systems do we need to invest in or what changes do we need to make now to stay relevant?

As a species, we have been phenomenally successful at solving hard problems.

For example, many of us live safer, longer and healthier lives as a result of the medical and technological breakthroughs of the last couple of centuries.

This success has been accompanied by an unexpected problem.

Many people are concerned about the growth in population as we head towards 8 billion people.

They point out that it’s unsustainable and we’ll run out of food to feed everyone and really it would be much better if everyone in all these developing countries stopped making so many babies.

But is the cause of population growth really more babies?

It’s not, reallyit’s not that we breed like rabbits – it’s just that we’ve stopped dying like flies.

The real solution to population growth might be somewhere else.

It turns out that richer people have fewer children.

So, if we want to manage population, a better way might be to help everyone get richer – so instead of aid should we focus on trade?

We normally think that charities or the UN handle big problems like that but maybe it’s business that will solve it in the end.

The thing is that we don’t know. And with many real-world problems we don’t know what solution is going to work – or for that matter what the real problem is.

That’s where a learning cycle comes in.

Hard problem solvers like to say give me your requirements, I’ll build a system and you’ll be happy.

That works sometimes – but all too often it doesn’t.

That’s because most real-world problems are context specific – they depend on the ideas and assumptions of the people involved as well as the situation and environment.

So, instead of solving a problem we may need to work our way to a solution.

In a learning cycle, we have a theory about what might work and that leads to ideas we can put into practice.

We can learn from the results and that leads to modifying our theory and ideas.

It’s not rocket science – but it’s easy to fall into the trap of thinking a new system or platform will solve our problems.

Real-world problems, however, are usually solved after going round the learning cycle loop several times.

Reference: Information, Systems and Information Systems – Peter Checkland and Sue Holwell

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