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Forecasting Techniques

There are many forecasting techniques that Scrum Teams can use as complementary practices to Scrum, and they all have their pros and cons. However, their real value comes from the Scrum Team using them to drive conversation internally and with others.

Burn-down and Burn-up Charts

A burn-down or a burn-up chart can be used to create transparency on the progress that a Scrum Team is making over time toward the completion of a given amount of work.

The difference between the two is that a burn-down chart shows the work that is still remaining at a point in time, while a burn-up shows the amount of work completed toward a target. “Work” could be expressed as the number of Product Backlog items, story points or some other measure. Both charts allow the Scrum Team to make transparent actual progress of completed work over time. Based on the progress trends, they can project completion of all work, or how much work might be delivered by a certain date. Uncertainty of forecasts can be captured by projecting an optimistic projected trend line and a pessimistic projected trend line, creating what is called “the cone of uncertainty”. The result is a range of when the work might be delivered. The further ahead a Scrum Team looks, the wider the cone, capturing the fact that forecasting is less certain the further that we look into the future.

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Burndown chart

 

Burn-down and burn-up charts have the advantage of being relatively simple to create and they are fairly intuitive to understand. However, they give no indication if value is actually being delivered. As such, they are used for tracking progress in the form of outputs instead of outcomes, and it is easy for Scrum Teams and their stakeholders to focus on completing the originally forecasted work as the target rather than monitoring progress toward fulfilling their Product Goal. Also, in the case of burn-down charts, they give limited transparency of what is actually happening. For example, consider a Scrum Team who gets nothing done in a Sprint and one that gets lots done but adds the same amount of work back to the Product Backlog. In the same Sprint, those two teams will have similar looking burn-down charts.

Probabilistic Forecasts

A probabilistic forecast is a calculation that forecasts when a certain item will be completed. For example, based on the following calendar, the forecast could take a form such as: there is a 85% chance that it will be completed by February 11, 2018, but only a 50% that it will be completed by February 3, 2018.

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calendar

Probabilistic forecasts can be used for the completion of single items, whole Product Backlogs, or how much of a Product Backlog might be done by a certain date. They are commonly created using Monte Carlo simulations and are based on a Scrum Team’s historical performance.

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Probabilistic forecast 2


 Probabilistic forecasts help to communicate uncertainties since the language of probabilities is one that most people can understand. However, these types of forecasts are not trivial to create and can be flawed as the quality of the simulation is only as good as the input data. 

 


Resources:

Video
This video explains Monte Carlo Simulation. Monte Carlo Simulations can be used to make probabilistic forecasts. This video explains how it can be used in the context of product delivery.
4.8 from 16 ratings
Blog Post
In this article, we discuss how forecasting in VUCA has always been problematic and the questions that should be asked instead.
4.9 from 8 ratings
Blog Post
The most important question to stakeholders is often “When can it be done?” There is a lot that goes into answering that seemingly simple question. What is involved in the work?
5 from 7 ratings

 

 

Video
In this Scrum Tapas video, PST Martin Hinshelwood talks about how to use probabilistic forecasting with a Monte Carlo simulation and how to determine if you have enough work refined for a specific period of time. (3:23 Minutes)
4.5 from 1 rating

 

 


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Scrum Team can use forecasting and release planning as a guide for delivering a product through small incremental and frequent releases rather than big bang product launches.