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How can you create a reliable project forecast with limited data?

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Project forecasting is the process of estimating the time, cost, and quality of a project based on available data and assumptions. It helps you plan, monitor, and control your project, as well as communicate with stakeholders and manage risks. But what if you have limited data to work with? How can you create a reliable project forecast that reflects the uncertainty and complexity of your project?

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Chris Leman

Global Lead C&Q @ AstraZeneca | ISPE UK Affiliate Vice Chair, North West Regional Chair, UK C&Q COP Chair

1 Understand your project scope and objectives

The first step to create a reliable project forecast is to define your project scope and objectives clearly. This means identifying what you need to deliver, why, and how. You should also document your project constraints, assumptions, and dependencies, as well as your success criteria and key performance indicators. Having a clear project scope and objectives will help you align your forecast with your project vision and expectations, as well as avoid scope creep and unrealistic expectations.

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Chris Leman

Global Lead C&Q @ AstraZeneca | ISPE UK Affiliate Vice Chair, North West Regional Chair, UK C&Q COP Chair
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Identify stakeholders with historical experience and involve them in the planning phase. They have invaluable experience in how long things take to progress through local process and business systems providing a genuine reality check on your assumptions. If there is limited data then gain an understanding of specific deliverables associated with similar systems to your scope and the necessary predecessor and successor tasks associated with each deliverable. PMO is a good starting point for historical information. Resource load your program for all stakeholders involved in task completion. Rarely will project resources be able to give 100% of their working week to task execution. Understand the level of involvement on offer by others.

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2 Choose a suitable forecasting method and technique

The next step is to select a forecasting method and technique that suits your project type, size, and complexity. There are different methods and techniques you can use to forecast your project, such as top-down, bottom-up, parametric, analogical, or expert judgment. Each method and technique has its advantages and disadvantages, depending on the level of detail, accuracy, and reliability you need. You should also consider the availability and quality of your data, as well as the time and resources you have to create your forecast.

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3 Collect and analyze your data

The third step is to collect and analyze your data to support your forecast. You should use both historical and current data from similar projects, as well as data from your own project, such as the work breakdown structure, the project schedule, the resource plan, the risk register, and the change log. You should also validate and verify your data, as well as adjust it for any factors that may affect your forecast, such as inflation, exchange rates, or market conditions. You should also use tools and software that can help you organize, visualize, and manipulate your data, such as Excel, Project, or Power BI.

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4 Apply uncertainty and contingency factors

The fourth step is to apply uncertainty and contingency factors to your forecast to account for the variability and unpredictability of your project. Uncertainty factors are the ranges or probabilities that you assign to your forecast values, based on your confidence level and risk exposure. Contingency factors are the buffers or reserves that you add to your forecast values, based on your risk appetite and tolerance. Applying uncertainty and contingency factors will help you create a more realistic and flexible forecast that can accommodate changes and surprises.

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5 Review and update your forecast regularly

The fifth step is to review and update your forecast regularly throughout your project lifecycle. You should compare your forecast values with your actual values, as well as track any deviations and variances. You should also monitor any changes in your project scope, objectives, assumptions, dependencies, risks, or issues that may affect your forecast. You should also solicit feedback and input from your project team, stakeholders, and experts to improve your forecast accuracy and reliability. Reviewing and updating your forecast regularly will help you keep your project on track and on budget, as well as identify and address any problems or opportunities.

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6 Communicate and report your forecast clearly

The final step is to communicate and report your forecast clearly to your project team, stakeholders, and sponsors. You should use formats and methods that are easy to understand, such as charts, graphs, tables, or dashboards. You should also highlight the key information and insights from your forecast, such as the baseline, the actual, the variance, the uncertainty, the contingency, and the forecast at completion. You should also explain the assumptions, limitations, and risks behind your forecast, as well as the actions and recommendations you propose to achieve your project goals. Communicating and reporting your forecast clearly will help you build trust and credibility, as well as facilitate decision making and collaboration.

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7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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How can you create a reliable project forecast with limited data?

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1 Understand your project scope and objectives

2 Choose a suitable forecasting method and technique

3 Collect and analyze your data

4 Apply uncertainty and contingency factors

5 Review and update your forecast regularly

6 Communicate and report your forecast clearly

7 Here’s what else to consider

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