Reference Class Forecasting is a method you can apply to ensure that you are as accurate as possible in your planning, from the perspectives of quality, budget, time and resources.

Most project teams come up with a forecast for how long the pilot will take based on the funding timeline of a grant or contract. They will also estimate the budget, the people needed, and any other resources required based on what they think they can raise. To avoid the common tendency to underestimate the time and resources you will require, Reference Class Forecasting can be used to improve the objectivity of your analysis.

The idea is to learn how similar projects have fared in the past and base your forecast on the actual performance of this ‘reference class’ of comparable projects, thereby avoiding both the optimism bias and the potential for misrepresentation. Even if you are working on an innovation and you cannot identify many similar projects, there are usually some that can help to guide you. To do this properly can take a lot of time and effort and expense. However, a quick method is possible.

The first area of reference is to identify projects that are similar in terms of type, and then find out how they did against their original plans. For example, if you are looking at building an information management system, there have been other such systems built before. If you have gone through a good Search process, you will have identified systems that may be similar. You can then try to interview people involved on those projects to get a sense of time, cost, resources required to deliver it.

The second area of reference is to identify projects in the context that you will be implementing your pilot. Speak to people running similar or analogous projects to understand whether contextual and environmental factors, such as security, logistical, weather patterns etc. created delays or extra costs. By developing a reference class of projects for the type of innovation, and a reference class of projects for the location, you can draw the lessons from both to design a much more feasible and robust pilot project design.