Why Your Delivery Predictions Will Always Be Wrong if You Keep Mapping Story Points to Hours
When it comes to making delivery commitments, mapping story points to hours to estimate your work is a terrible piece of advice. In fact, there is a very simple exercise that can be used to reveal this paradox.
Bar Vaccin (Haute Cookure) is a small cozy place in Oostmalle, Flanders, here in Belgium. For those of you who have stuck around for a while, you already know that apart from heavyweight boxing, I’m also addicted to French cuisine. Bar Vaccin is a wonderful Michelin star restaurant and even if it wasn’t located only 10 km away from our house, I’d still always go back for our birthdays, anniversaries, and any other special occasions we celebrate. Over time, it also has become my favorite place to meet with potential customers who are looking to adopt Nave within their organization.
The last time I went there was a few months ago, just before pandemic precautions required the place to close, and I met with the technical director of a big media company. With a glass of Vaccin’s famous namesake cocktail, we were talking about their main problem – lack of predictability.
There was something that she said which particularly struck me: “When we meet with the teams and they say this story is 2 story points, I do the math in my mind (1 point is approx. 3 days) and I know right away it will take 6 days. If they say, the story is 8 points, that would translate to about 3 weeks. However, I don’t understand why this approach always ends up wrong!”.
Well, let’s dig deeper into it!
Compare Story Points of Completed Stories With Their Cycle Time
Before we begin, let’s clarify that when we talk about cycle time, we are talking about the amount of elapsed time between the moment a work item starts and when it finishes.
Let’s do an exercise. Let’s build a scatterplot with story points on the X-axis and cycle time on the Y-axis. We’ll define 1, 2, 3, 5, and 8 points on the X-axis (you can adjust these values based on your own context). Now, let’s plot how many days have taken for a story assigned with 3 story points to be completed. In this example, that story needed 12 days to be finished. Now, let’s map story points to hours for the last 20 to 30 completed stories. For each work item, add the story points to column B in the “Story points to hours correlation” spreadsheet and then add the actual cycle time it has taken to complete the item to column C.
Moving on, we would expect that items with 1 story point will be relatively quick to complete and as the story point value goes up, the time that an item has taken will slightly increase.
This is what the correlation between story points and cycle times looks like for one of the media company development teams we talked about in bar Vaccin:If you look into the cycle times perspective, the items with 1 story point can range from anything between 1 day all the way up to 22 days. The same results are observed for items with 2 story points and 3 story points. The most surprising trend is that their 8 point stories are in the same date range as the items with 1 story point.
Use the “Story points to hours correlation” spreadsheet to map your own data and visualize whether or not there is a correlation between story points estimation and the actual time required to complete your work. The main purpose of the chart is to serve as evidence to prove that story points should not be mapped to hours. Doing this exercise is supposed to be a one-time effort, the results of which would hopefully call this vicious practice into question. Providing proof based on your historical performance is the best approach to communicating the fact that converting story points into hours will land you in hot water.
Are You Getting the Right Value From Story Points?
It’s obvious that mapping story points to hours is not a reliable approach to take when making delivery commitments. In fact, you should never resort to story point estimation again – there are far more effective alternatives, which will enable you to make accurate future predictions.
Now, the question is, are you getting the right value from story points?
When we talk about story points, the number itself shouldn’t be that important. The actual conversation behind what needs to be done and how you can do it are the most important things. In fact, probably the main benefit of story points is that they trigger this conversation.
There is a need to clearly differentiate the analysis process and the forecasting process. Think about how much time you’re spending arguing whether something is taking 5 points or 8 points. If you have a team of 10 people and you spend 1 hour per week on estimating your work using story points, that’s 10 hours per week that can be spent doing the actual work instead. Gaining an understanding of the problem you’re trying to solve is essential. Not the points themselves. If this all sounds familiar, it would be worth calling your current practice into question and looking for an alternative trigger for these conversations.
Last but definitely not least, talking about story points is the wrong way to communicate with your customers. Have you ever tried to explain to a customer what ‘8 story points’ mean? Story points estimation doesn’t speak their language. Your clients don’t think in terms of story points. They think in terms of elapsed time, they think in terms of “When will this be done?”.
In our Sustainable Predictability program, we dive deeper into the proven strategies that enable you to give a confident answer to the “When will this be done?” question and meet your customer’s expectations.
Mapping Story Points to Hours Is Terrible Advice
Even though plenty of management platforms provide the feature of mapping story points to hours, don’t fall into the trap of heading in this direction. It will only compromise your ability to make reliable delivery predictions.
Use story points to spark the conversation around the work that needs to be done, in order to come up with the most feasible solution that brings value to your customers. And always keep in mind that time spent actually doing the work is way more valuable than the time spent arguing about the number behind the work itself.
Meet the Author
Sonya Siderova is a passionate product manager and a driving force behind Nave, a Kanban analytics suite that helps teams improve their delivery speed through data-driven decision making. When she's not catering to her two little ones, you might find Sonya absorbed in a good heavyweight boxing match or behind a screen crafting a new blog post.