When outcomes aren't guaranteed, data becomes essential

I was intrigued by something I saw Sandeep Shrivastava post on LinkedIn.

Are there such things as guaranteed outcomes?

If I eat fewer calories than I need every day, I will lose weight.

If I practice piano every day, I will get better at playing the piano.

If I help one person every day, I will feel more fulfilled.

If I play the lotto every week, I will be $20 poorer every week.

OK, that last one is not guaranteed, but it sure feels like it sometimes!

I can see that these “guaranteed outcomes” will likely have diminishing returns. I might start losing weight at a faster rate and that rate might slow over time. There might even be points where there is no return. No matter how much I practice the piano, I may reach a point where I am not going to get better.

Absolutes and continuums

Are we now leaning towards the view that there is no such thing as a guaranteed outcome?

Or is it because these outcomes are on a continuum? If an outcome has an absolute (as all good outcomes should), can we create a chain of events that guarantees delivery of the absolute?

A good outcome should not be guaranteed

If we can guarantee delivery of an outcome because we’ve defined it as an absolute, I would argue that it is not an outcome.

An outcome should be a stretch. If the achievement can be guaranteed, I would argue that it is not a stretch. And if it’s not a stretch, it’s not an outcome.

Thinking back to our definition of an outcome, an outcome should also be SMART, with the A being Achievable. Achievable = able to be achieved. That’s not the same as guaranteed to be achieved.

There should be no such thing as a guaranteed outcome.

So that brings us back to experimentation

If an outcome is not guaranteed and is a stretch, there is an element of the hypothetical about the work to deliver an outcome. We hypothesise that the work will generate the outcome. It’s only by doing the work, we are able to validate if our hypothesis is correct.

Things brings us to another really important point. Because outcomes cannot be guaranteed, because any work to deliver an outcome is based on an hypothesis, outcomes must be measurable. There is no way of validating the hypothesis if we don’t have a way of measuring the result towards the outcome from the work we do.

It is really important that our outcomes have measurable data and that the data is easy to collect, inspected and considered frequently. This is the best way to improve the likelihood of delivering on your outcomes.

And now, we’re right back at the start. There is no such thing as a guaranteed outcome. To learn more about outcomes, sign up for my free email article series on outcomes.