- Pick a problem that is of the right size
- Pick a problem that is worth solving
- Pick a problem that can be solved and in finite time
- Pick a problem that can be quantified
- Pick a problem that impacts lives

Ask these questions because people will only change if they see you solving their problems. They know that some problems are too big and cannot be solved here and now. They also know that there are problems that can be solved and solved in near future. If they see the proposed change as something that will solve the later problems, they will be willing.

For me the success or failure of a change initiative rests on choosing the right problem to solve. Too often organisations set change initiatives to solve problems that are too big or too vague. These problems are either not understood by an average employee or are at too higher level to impact the life of any average employee. Let me explain this with an example

‘To sustain in the current market place we need to adopt a culture of innovation’

That actually means nothing. If you test this problem against all the conditions that I stated at the start of this post, you will realise that this one fails on almost every test. Can I change the culture in short term? Is the problem of right size? Can the problem be quantified? Can the problem be solved in finite time? Answer to all of these questions is ‘No’ and that is why usually such big statements do not get enough engagement and reaction.

We need to break these big statements into smaller pieces. Each of these pieces needs to pass all the tests that I mentioned at the start of the post. Let’s relook at our statement again.

Here is how I can look at the same problem in pieces

**‘To generate at least 100 innovators and 1000 viable ideas from within the organisation’**

Now that is a problem that can be solved and is worth solving. It is also a problem that can be measured and benefits can be felt. Employees can get excited about this problem and the impact can be felt. Will this lead to the desired culture change? The probability is good. People can rally behind such problems as these are much more tangible than the vague statements of vision.

Give the concept a chance. Take a look at how you have defined your ‘change problem’. Check your definition against the tests I mentioned. If it fails then maybe it is worth redefining your problem. After all if your problem cannot be measured, solved in finite time and cannot impact lives directly, why bother?

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