The importance of data in project management is growing every day. Teams use data to drive decision making at every stage of the project lifecycle—to identify risks, control costs, uncover opportunities, and plan and execute nearly every other activity. As the volumes of information flowing through the business environment increase, your project team members become more reliant on data to carry out their responsibilities.
Project professionals aren’t the only ones interested in project data. Your stakeholders also expect greater access to information and the knowledge it holds. But delivering raw data, or even a limited analysis, often isn’t enough to provide sponsors and executives with a good understanding of what the data means. Maintaining good awareness across the entire project portfolio complicates the picture, as the amount of data presented increases and making sense of it all becomes more difficult. This is where context is valuable—it gives project information meaning and helps senior staff, end users, and other stakeholders comprehend how to translate project data into insight.
If your team wants to elevate the value of your project data and make it more meaningful for customers, supporters, and other collaborators, consider these strategies to add context to key information sets.
The right context enables the project team to put problems in perspective. Every project experiences some level of difficulty, though most issues are effectively addressed within the team and never rise to a level where they require the attention of the senior staff. Because the organization’s leadership usually has only limited visibility into the majority of project challenges, placing context around the problems that do cross their radar is vital to helping sponsors understand the potential scope and impact of issues that come before them. It’s particularly useful when an issue has the potential to spill from one project into others, for example, or to undermine financial expectations at an operational—rather than an individual project—level.
Providing contextual background gives the team a way to link problems to triggers. The right context helps in identifying relationships between project challenges that occur and the root causes behind them. If a problem is particularly complex, adding context may be the best way to define what’s happening and to understand why. Sharing this context with stakeholders empowers them with the perspective they need to accurately assess possible solutions and to conduct an effective cost-benefit analysis for those best fit the current problem.
Comprehensive context around project data helps your team to predict and avoid downstream problems. Reviewing challenges with a narrow focus often results in missed insights, such as a delay in a single activity that will create a cascade of timeline conflicts in other tasks. But using contextual information, you can build a much deeper understanding of the other issues your current challenge is likely to trigger. Are today’s budget overages related to new freight surcharges, and will that same fee structure snowball into even bigger funding problems as downstream activities begin? With context to make the data more meaningful, your team can adjust near-term expenditures or reallocate funds to avoid budget shortages later.
Adding context to performance metrics provides an additional level of insight to understand how well your team is delivering project results. Schedule delays can be analyzed with a more comprehensive view of surrounding factors that may have created or suffered from timeline shifts. One budget shortfall may hold a different significance when contextual data—trends, relation to other project spending, etc.—is included in the post-project review. Context is the piece that makes the puzzle complete and enables your team to improve performance over time.