Forget RAG charts and timelines, project managers are increasingly turning to big data for much-needed insights into large-scale jobs of work. In the second part of our seriesexamining the impact of data and data strategy in business, we look at how new technologies are impacting the project management profession.
Organisations have come to recognise the near-limitless power of data-driven decisions, a fact that has contributed to making data strategy the new linchpin of project management.
In agile environments, waterfall models, and hybrid frameworks, integrating a solid data strategy can ensure project outcomes are aligned with everything from client needs to organisational goals.
Those who wield data effectively enjoy a clear advantage over those who don’t. In the project management field, that equates to a track record of jobs completed to a high standard, on time, and to budget – music to any PM’s ears.
Conversely, without a comprehensive grip on the information that powers your business, project managers become blinkered to opportunities and threats, resource requirements, and timelines – which, it goes without saying, is a problem.
The Big Data Factor
Historically, without the benefit of big data, project managers relied on concrete, clear-cut plans, agreed timelines, and fine-tuned resource allocation. That’s still true today, but with the introduction of dynamic data, modern projects are built on fluid strategies that can adapt to real-time insights.
Despite the obvious benefits, elsewhere in the economy, emphasis on data skills is patchy.
A study conducted by Harvard Business Review Analytic Services, in partnership with ThoughtSpot, found that just seven per cent of organisations are effectively equipping their teams with the analytics tools and resources required to enable autonomous decision-making.
By contrast, a growing number of project management job postings now list data proficiency as a top requirement, reflecting the increasing demand for data-savvy professionals.
“Now, more than ever, we’re seeing a need for organisations to be able to adapt, evolve and pivot at pace in order to meet changing business demands,” says Sudheesh Nair, CEO of ThoughtSpot.
No surprise then, that organisations are spending big on skills to ensure they stay in the game. According to research by GlobeNewswire and Analytics Insight, the Big Data market is projected to grow from $162.2 billion in 2021 to $273.4 billion by 2026, with a compound annual growth rate (CAGR) of 11%.
It’s an upward trend, not just limited to tech-heavy industries but spanning across sectors such as healthcare, retail, and manufacturing.
Recruiting data-savvy project managers, or upskilling current employees, will be the name of the game now and in years to come, says Cyril de Avellar, Learning & Development Manager at Ingka Group, owners of the Ikea brand. He comments:
"Learning is no longer an afterthought – it now informs how we solve business challenges, strategise, and approach new projects".
By leveraging predictive analytics, project managers can foresee bottlenecks, optimise resource allocation, and adjust timelines. This is particularly crucial in industries such as construction, engineering, and IT, where projects are routinely delayed because of unforeseen – yet often predictable – factors.
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What are the Benefits of Big Data?
For project managers, whose job it is to ensure that often competing factors work together in symphony, data insights provide a suite of benefits.
Improved resource allocation is one, with project managers tracking resources and sprinkling them across tasks in real-time. Another is better risk management, with predictive analytics helping to identify, modify, and mitigate hitherto unseen pitfalls.
According to a report by McKinsey, “…dynamic and integrated risk management, which includes the ability to detect risks, determine appetite, and decide on the action in real-time, is growing ever more critical”.
Even stakeholder communication gets a boost: Data helps project managers present clear and measurable metrics to the team, keeping everyone aligned on project progress.
By integrating real-time dashboards and reporting tools, stakeholders are continuously updated with key performance indicators (KPIs), improving transparency and trust. A win-win situation.
Then there’s the perennial problem of cost overrun, which data helps reduce by finding and filleting unnecessary expenses. By analysing past project data, managers can predict cost overruns and implement strategies to mitigate them.
In a study by data consultancy BARC, organisations able to quantify their gains from analysing big data reported an average 8% increase in revenues and a 10% reduction in costs.
How Should Companies Adapt to Use Big Data?
While the technology underpinning the data-driven world is moving at a quick clip, organisations are advised to move at their own pace, acknowledging and responding to the need for more data skills, but not panicking.
The Association for Project Management (APM) refers to a 2022 study by Warwick University revealing several barriers to the implementation of project data analytics. In response, it advises adopting an “incremental approach where organisations learn as they deploy these capabilities”.
To make the changes, it recommends the following five-point plan:
Step 1 – Develop an understanding of how data analytics can help your organisational and project goals. Consider your organisation’s current level of maturity in this area.
Step 2 – Review the skills that align most closely with your goals or your team’s goals. This may include skills related to data collection and analysis, gaining deeper insights, communicating effectively, or making more objective decisions.
Step 3 – Identify the profiles of the team members you want to assess and consider their current skills, challenges, and goals for improving their data analysis skills. The personas within the framework can help identify common areas to focus on.
Step 4 – Use the indicators provided within the framework to understand the skills that you and your team already have and any skills gaps that need to be addressed. Develop a targeted plan to close these gaps and enhance your team’s data analysis capabilities.
Step 5 – Project data analytics is constantly evolving, so regularly review and update your development plan.
Regardless of your approach to project management, the formulas you follow, or the methodologies you swear by, data is the secret sauce that will forever define the success or failure of projects, programmes, and portfolios.
By carefully collecting appropriate pockets of information, sifting them into understandable groups, and incorporating insights into action, organisations can improve their chances of success by understanding each new project well before they break ground.
