Hours or story points?

We can easily get bogged down in this age-old debate.

So, what if, instead, we consider an alternative perspective?

What if there is an approach that will enable you to make reliable sprint commitments and meet your sprint goals consistently?

Let’s jump into the details!

How to Determine If Counting Hours or Story Points Works Well for You

We’ll begin by asking the most crucial question, “Is your current sprint planning approach actually working for you?” How can you answer this question?

Let’s look into an example.

This is the Cycle Time Scatterplot of a cross-functional Scrum team consisting of 10 people, delivering batches of work every 14 days to their stakeholders.

Cycle Time Scatterplot by Nave | Example

The dotted horizontal lines stretching across the graph are called percentile lines. They indicate how long past tasks took to finish.

In the diagram above, the 50th percentile points to 10 days. This means that half of the work has been completed in less than 10 days. The other half though has taken up to 130 days to be finished. In 95% of the cases, the team needed up to 76 days to deliver the work they had started.

If you’re running 14-day sprints, these numbers are quite bad. If, in 50% of the cases, the work was finished within 10 days, this means that stories that started at the beginning of a sprint only had about a 50% chance of being completed within that same sprint.

This is not a predictable system. And if this is what your picture looks like, I’d strongly recommend exploring a different approach to planning your sprints.

How to Plan Your Next Sprint So You Actually Meet Your Commitments

The first step to making an objective decision on how much work your team can handle during the Sprint is to understand that effort time is just one part of the whole picture.

If we break down the elements that contribute to the time needed to deliver your work, at least 60% of it consists of waiting time in the system due to dependencies, bottlenecks, expedite requests, and plenty of other sources of inefficiency. This is a realm that you can’t predict by intuition.

Delivery Time Formula | Image

So, instead of planning your Sprint using hours or story point estimations, it’s better to assess the capacity of your team.

The capacity of your team is measured by the rate at which they deliver work. “Deliver” is the keyword here. We’re only interested in how much work they can complete within a given sprint.

So, to determine your capacity, what you want to do is look into your past performance data to evaluate how many items you have completed per sprint in the past 3 to 6 months.

This is where the Throughput Histogram comes into play.

Throughput Histogram by Nave | Example

The Throughput Histogram shows the number of items you completed in a certain period. To track the number of tasks delivered per sprint, we will group our data by 2 weeks and we will set the start date of the chart to match the start of a sprint.

Looking into the example above, we can see that in the past 6 months, there was 1 sprint in which this team managed to deliver 5 items, 2 sprints in which they finished 10 items, 1 sprint with 12 items, another 2 sprints with 14 items, and so forth. You can now use this analysis in your next Sprint Planning to better understand your capacity.

Here’s how to read the numbers:

This team can schedule at least 5 items in the next sprint. This is their absolute minimum. They guarantee they will deliver at least 5 items, and that commitment comes with a 98% certainty that they’ll hit that target.

Then, there is an 85% chance that they will deliver at least 10 items and a 70% chance that they will finish more than 12 items. The chance that they will complete 14 items drops down to about 50%.

Even though this team managed to finish 24 items in one of their previous sprints, it is unlikely that they will be able to deliver that much work consistently (the probability that comes with this commitment is less than 30%). If they commit to that number, it is very likely that some of the work will be rescheduled for the next iteration.

Use this information as a guide to determine the amount of product backlog items necessary to achieve your sprint goal.

And if your team commits to a number that comes with low confidence of that being achieved, put that commitment into question. The greatest benefit of performing analysis based on throughput is that it represents your actual capability to deliver.

How Much Risk Are You Willing to Live With?

Now, I can already hear you saying, “Sonya, this will only work if we have items of the same size!”

No, it won’t. And here’s why:

The question you now have to answer is no longer, “How much work can we deliver?” The charts already provide that answer for you. The question now is, “How much risk are you willing to take?”

That risk is quantified in terms of percentages. So, which percentiles will you choose when you make your commitment?

If the work is complex, there are lots of unknowns, and you expect obstacles along the way, then go with the 95th percentile to reduce the risk of failure. Schedule 5 items instead. You will probably deliver more, but not less than 5 items, and that promise comes with very high confidence that you’ll keep it.

If the work is easy, you’ve done this before, and the team is confident to take that work, then go with the 70th percentile and commit to delivering at least 12 items.

Just because you have 12 stories in your backlog, this doesn’t mean that these exact 12 stories will be delivered by the end of the sprint.

That’s not what the capacity analysis is telling you. What it is telling you is, “If you have 12 items, they will be done in less than 14 days, and there is 70% certainty that you’ll meet that goal.”

You now have 12 free slots to deliver on your commitment. It’s up to you to decide, in a continuous manner, how to best fill these slots to meet your sprint goal.

Here’s your action item: Introduce capacity analysis in your next Sprint Planning meeting. Use the Throughput Histogram to inform your decisions and set reliable data-driven goals. It’s free for 14 days, no CC required, so go ahead and explore your data

I hope this has been helpful. Make sure to share this article through your social media channels. I’d highly appreciate it if you spread the word.

I wish you a productive day ahead and I’m looking forward to seeing you next week, same time and place for more managerial insights!

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