5 ways to make the most of project data

The world is awash with data. But how good are we at turning all that data into information we can actually use? Without applying the right analytical skills, data can be worse than useless; it can become noise that at best obscures the truth and at worst leads us astray.

But with the right approach, project data can tell us where we are performing well, where we are not, and why. It can help us understand what has already happened, predict what is likely to happen and understand how to take corrective action in a timely manner when things go awry. So, here are five ways how to maximise the utility of your data as a project professional.

1. Strategically define data needs

What do you need to know? The more distinct your project aims, milestones and performance criteria, the simpler it becomes to pinpoint the data you need. It is essential to recognise the pivotal decisions that will influence the project’s outcome, the operational processes that they affect and the key performance indicators (KPIs) they are tied to.

For projects undertaken on behalf of a client, scrutinising and interpreting the contractual requirements is critical. You don’t need to tie yourself up in endless, exhaustive discussions with the entire project team, but clarifying the specific data needs of key stakeholders and fully understanding their expectations and intended use of data will take you a long way towards identifying the necessary information for success.

Think about what drives performance in the project and what data and information support the effectiveness of those drivers. KPIs are valuable but they tend to be backward‑looking and to describe delivery against a baseline rather than illuminating how the current project status has been arrived at and the implications for future project management.

The more integrated your data, the deeper the insights it can provide. It is worth establishing links with key frameworks such as the Work Breakdown Structure as early as possible in the project setup to enable the categorisation of your data into appropriate ‘buckets’, facilitating integrated, clear and focused insights that support performance management at various levels.

The next step is to verify the availability of the required data. Collaborate with the project team and experts to methodically address your information requirements. Assess who will provide what data. You will often find that data availability hinges not just on systems but also on the maturity of processes and the capabilities of your project team. Begin by aligning your information needs with project processes, the owners of these processes and the corresponding systems or tools.

Identify any gaps in these areas and rank your needs based on their importance to the project’s success and its timeline. Collaborating with your team to bridge any gaps is vital, ensuring all necessary data is accessible. While setting up operations early in the project is beneficial, adjustments can still be made during the project’s lifespan. But bear in mind that later changes may be more challenging due to the team’s entrenched habits and the inertia of established processes and systems.

2. Establish data processes and assure data

Processes should prioritise critical data elements, such as project timelines, budgets and KPIs, and implement standardised methods for data collection and entry, utilising systems, templates or forms to ensure uniformity and minimise errors. Establishing regular routines, such as weekly checks to verify data accuracy and completeness, will maintain the integrity of your project’s information.

The establishment of a data governance framework tailored to your project is also critical. This involves creating transparent, straightforward rules for privacy and ethical data handling and assigning clear responsibilities for data‑related tasks to specific individuals. It is essential that project related data of all types is available from a single, accessible and secure location to ensure everyone is consistently working with the most up‑to‑date information.

These data systems should be linked to your project data structures by utilising columns or systems fields to tag the information to the right structure. Shared cloud storage solutions, ideally with customised access controls, can accommodate different levels of data sensitivity and ensure that data is available to those who need it while being protected from unauthorised access.

3. Roll out data processes

Begin with a kick‑off meeting to establish key data needs, assign roles, introduce the tools and define ownership of the processes, data and data structures. Clear guidance on the templates and checklists for data collection and quality assurance will deliver better results.

Everyone must understand their responsibilities and the quality checks required within their teams. Establishing an easy mechanism for team members to report issues or suggest improvements is critical, especially since data owners are often subject matter experts whose insights are invaluable.

4. Tailor reporting for effective outcomes

Automating report processes increases efficiency, saves time and maximises data effectiveness. On one of our major civil engineering projects, for example, we have over 60,000 deliverables. To automate the live update of this data we tagged key milestone activities in the programme and aligned each deliverable to the relevant section of the programme and also to the document control team sending out the deliverables to the client.

The result is a dashboard that automatically tells the project teams exactly where each deliverable is in the review cycle and also when they need to get the next version of the deliverable to the client. This report has greatly reduced the need for trackers at design‑team level, and this data can also be rolled up into specific reports that help the project executive understand the status of deliverables and review trends.

5. Continuously improve

Once the reporting has been set up and the data is being used effectively, it is key to be agile as the context and critical success factors of the project change. There needs to be regular reviews of the reports being utilised by the data owners and the relevant representatives from the project organisation to ensure continued relevance.

It is also important to establish feedback loops that enable report users to raise questions or comments regarding the content of the reports. The key to data‑led decision making is ensuring the data is relevant, correct and presented in a digestible format that leads to insights on project performance.