How to Forecast Project Timelines?

How to Forecast Project Timelines?

Anyone who has had to deal with medium to high difficulty projects in a professional environment has experienced how projects can “go awry”. The problems may vary – deadlines not being observed, budgets being exceeded, the desired result not being delivered etc. Why is this? Of course, each project was carefully planned initially, and everything was honestly calculated and considered so that the desired result could be delivered, right on time and using the planned resources! The key to this problem is specifically hidden in the approach to the forecasting/planning of the project.

In 1979, Daniel Kahneman and Amos Tversky – mathematics, economics and psychology academics – formulated the Planning Fallacy Theory about how people are always rather optimistic about their individual forecasts about the future. According to this theory – we are unable to evaluate how much time will be necessary for the completion of a job/project, and most of the time, we underestimate how quickly we will be able to complete individual projects.

What is the most widely used approach to forecasting project timelines in our everyday work? Usually, it is based specifically on individual people’s (on experts with the corresponding previous experience) individual opinions about how much time will be necessary for the completion of an individual job or a whole project. Unfortunately, this type of approach falls within the trap of the Planning Fallacy Theory and the initial forecasts (irrespective of how professional they may be) are nearly always wrong.  

Luckily, both academics also later provided various solutions for the resolution of the Planning Fallacy Theory, of which one is connected with Reference Class Forecasting, for which Kahneman received the Nobel Prize. At the core of Reference Class Forecasting is the determination of reference values which can be understood and grasped by everyone; the forecasting of the future is based on a comparison of future scenarios against a determined reference value.

For example, in project planning, it is important to understand that a project consists of several separate jobs. Therefore, the completion of a project is linked to the completion of these separate jobs. It is best to determine an unchanging constant value, like for example, the complexity of a job as a reference point. The time for the job to be performed is a variable value, which can vary from situation to situation due to various external factors which are difficult to forecast; but the complexity of the job is constant and remains unchanged.

If a project team can agree on determining the complexity of one job as a reference value (let us call this Job X) – then the complexity of the other jobs can be evaluated relative to the reference job – by comparing them. The other jobs will, therefore, be either more, or less, or equally complex to reference Job X. Of course, complexity does not have a universal unit of measurement – therefore, we can choose any standard, like, for example, a point system: a more complex job has more points, while a simpler job – less points than reference Job X. In this way, it is possible to evaluate and quantify the overall complexity of a project.

But why is this necessary? The quantification of complexity will later provide us with empirical proof of the speed at which a team works. The speed of a team's activities can be formulated just like any other speed formula = distance (work completed and complexity)/time (the specific unit of time, such as an hour, a day, a week, or a month). Therefore, over time, it is possible for any project team to determine the average speed of its activities, or the degree of complexity of work that a team can resolve in a prescribed period of time.

As soon as we can find out a project’s overall, or remaining complexity (distance), the speed of a team's activity – we can simply calculate the time necessary for the performance of the project. In this way, project timelines can be forecast much more accurately, avoiding the mentioned biased optimism of the Planning Fallacy Theory, which is the main reason for the inaccurate planning of projects.

I will talk more about this approach in the interactive Planning Project Time course, which will be based on acquiring practical skills for the forecasting of project timelines in a much more accurate way – a popular approach, which is used widely on an everyday basis by Agile teams throughout the world.

Jānis Dirveiks, Agile practitioner and presenter

See the current courses presented by Jānis Dirveiks here: