Knowledge work is notorious for its unpredictable nature. There will always be a vast array of different scenarios that could possibly happen in the future. Frankly, it is just impossible to eliminate the uncertain and unknown.

So, why do so many of us lean towards the illusion that coming up with a single certain delivery date is the best way to make our commitments?

We have to embrace the fact that uncertainty exists and, rather than ignoring it or trying to work our way around it, we have to find a way to manage that uncertainty effectively. We have to start thinking probabilistically.

We can’t just come up with a single delivery date stating that we’ll hit our target with 100% certainty. When we’re attempting to predict the future, there is no such thing as 100% certainty. Alas, no one has invented the magic crystal ball just yet.

Our commitments should always be presented as a range of delivery times, alongside the probabilities that come with each of them. Always remember that there are many possible scenarios that might happen. When making delivery predictions, thinking deterministically is simply not sufficient.

Why You Need to Think Outside the Box

In order to make a reliable commitment, predicting when a certain task will be delivered, you should produce a probabilistic forecast.

Probabilistic forecasts look like this: “We’ll be done in less than 31 days and there is an 85% chance that we will meet that goal”.

Are we saying that the effort time of the task is exactly 31 days? No, we aren’t.

Are we saying that we’ll deliver that task in exactly 31 days? No, we aren’t.

What we’re saying is that it will probably take less than 31 days to deliver the work, but it won’t take more than 31 days and there is an 85% probability of hitting that target.

That’s what probabilistic thinking looks like. That’s how we manage uncertainty effectively.

The Little-Known Fact You Should Know About

There are different approaches to producing a probabilistic forecast, however, the one that will help you shift your mindset from deterministic to probabilistic thinking the most is analyzing your cycle times in a histogram.

This is where the Cycle Time Histogram comes into play.

The Cycle Time Histogram shows the shape of the frequency distribution of your cycle time. The horizontal axis displays your cycle times and the vertical axis denotes how many tasks have been finished within the same cycle time.

Little-known fact about your cycle time - Histogram

For the selected period, this team has finished 29 items in 1 day, 11 items in 2 days, 3 items in 3 days and so forth.

And here’s one little-known fact about your cycle time that you should understand and embrace:

Cycle time is not a number, it is a shape.

Every time you think about your cycle time, think about it in terms of the shape of your frequency distribution. Think about your cycle time as the whole histogram. The cycle time of your process is not a single number. Rather, it is many numbers and each of them comes with a probability of its occurrence.

And the single best thing that you can do to come up with a reliable delivery commitment is to say: “Here are the chances of getting task X done in Y days”.

Looking back at the example above, this team can finish any work item, regardless of its nature, size or complexity in less than 31 days, and there is an 85% chance of it happening.

Always remember, your cycle time is a shape, it’s not a number. And that shape will dictate the accuracy of your delivery predictions. Thin-tailed distributions produce more accurate probabilistic forecasts.

And, if you’re not completely delighted by the numbers you see on your histogram, chances are you are maintaining a fat-tailed distribution. In layman’s terms, your workflow is not optimized for predictability.

If you want to explore our proven 7-step roadmap to building predictable workflows, improving your delivery times and hitting your targets consistently, I’d be thrilled to welcome you to our Sustainable Predictability program.

Here Is a Little Pro Tip

With this approach, you’re switching the gears from “When will this be done?” to “How much risk are you willing to take?”. You no longer need to evaluate the effort of your work, your data is already giving you the answer to that first question. Now, it is up to you to decide how much risk you want to live with.

Should you go with a high certainty of achieving your goals and use the 95th percentile instead? If the risk you are managing is high enough to justify this commitment, by all means, go for it.

As a little pro tip, never commit to a delivery time that comes with less than 50% certainty of hitting that target.

50% certainty is the same certainty that comes with flipping a coin. Committing to the 50th percentile essentially means that you’re just as likely to make it as you are not. And that’s certainly not what I’d advise you to do.

Always remember, you should never commit to a single certain delivery time. Your cycle time is not a number, it is a shape. Use your historical performance data to define that shape and strive to make it as thin as possible. That’s exactly what predictable workflows look like.



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