Simon Garrity: How HR can provide leaders with better data to understand to plan, manage and adjust workload

Our own research shows that UK businesses are plagued by an overtime epidemic, impacting employee retention and business performance. The right data can help employers identify the root cause of overwork, ensure workloads are fairly distributed and take proactive measures to anticipate and manage heavy workloads.

Earlier this year, our research revealed that UK  employees work 19 million days unpaid overtime a month and this is having a negative impact on staff retention and business productivity.  Unrealistic workloads were found to be the main reason for employees working overtime, causing stress, anxiety and burnout for more than half of employees.  With nearly a third of employees routinely given unrealistic workloads.

Our research also found that this is not a problem employees can solve by themselves. Most employees try to actively manage their workload, informing their manager when they have more work than they can get through in the working day, asking for management help to prioritise workload, it is clear that when overwork is the norm in an organisation it requires cultural and systemic change to address.

Equally, it isn’t realistic to expect managers to be able to address the issue of overwork themselves. It is widely accepted that many managers today find themselves between a rock and hard place, trying to manage top-down performance targets and the consequences meeting these has on team workloads and individual team members.

Without manager support and clear boundaries in place, overwork is damaging business performance and employee engagement.  With 38% of workers saying they are less productive when overworked,  29% say the quality of their work suffers as does their relationship with their manager.

It’s not just productivity that suffers, employee wellbeing is also undermined by overwork with 53% of employees saying they experience increased stress and anxiety and 41% feel burnout as a result of heavy workloads.

If we accept that the current culture of excessive overtime is primarily an organisational not individual issue it becomes clear that an organisation unless is gathering data on time spent it won’t be able to quantify the size of the challenge or identify appropriate measure to address the root cause of the problem and address it.

With the introduction of new employment rights this is an issue that employers must address with urgency or worst-case scenario face tribunals for unfair distribution of workloads and expectations on individual employees.  With this in mind, it’s worth noting that hybrid workers are more vulnerable to overwork with 33% saying they are more likely to work additional unpaid hours if they are working out of the office.

HR can empower leaders with data-driven insight on workload management

HR has a unique opportunity to transform how leaders make workforce decisions by providing them with comprehensive, actionable data. The challenge lies not just in collecting data, but in translating it into insights that drive better workload planning and resource allocation decisions.

Many organisations still rely heavily on intuition and incomplete information when making staffing decisions. This approach often leads to suboptimal outcomes: teams struggling with burnout, declining productivity, and increased turnover. By leveraging our position at the intersection of people and data, HR departments can revolutionise how organisations approach workload management.

To effectively support leaders, HR needs to focus on three key metric categories: First, capacity metrics provide the foundation for understanding workload distribution. These include FTE allocation across projects, the ratio of available to allocated hours, and overtime patterns. By tracking these metrics, leaders can identify potential resource constraints before they impact team performance.

Second, productivity indicators offer insights into team efficiency and output quality. These encompass task completion rates, project milestone achievement, and time allocation across different work activities. Particularly important is the often-overlooked metric of meeting load and collaboration time, which can significantly impact actual productive hours.

Third, workforce health metrics help predict and prevent burnout. Employee engagement scores, absenteeism patterns, and work-life balance feedback provide early warning signs of potential issues. When combined with turnover rates and stress indicators from surveys, these metrics create a comprehensive picture of team wellbeing.

Building a robust data-driven picture of workload

Without the right tools it is almost impossible to collect and analyse workload data across the organisation. Spreadsheets are simply not up to the task.  For real-time insight, HR must lead the business case for implementing integrated systems that connect workforce management software with project management tools and platforms.

HR can also support the business in establishing consistent metrics across departments and implement regular data collection intervals. Without a standardised approach to the data, you collect and interrogate it’s hard to achieve meaningful analysis. Quality control measures ensure data accuracy, while standardised reporting templates will make insights accessible and actionable for leaders.

To maximise the impact of these systems, consider implementing self-service analytics dashboards. These tools empower leaders to access real-time data and make informed decisions independently while reducing the burden on HR teams for routine reporting.

From data to action

An organisation can collect the best data but it’s true value lies in its ability to interpret and apply the results. HR professionals should focus on creating context-rich reports that go beyond raw numbers. Include historical trends, industry benchmarks, and clear narratives explaining significant patterns. This context helps leaders understand not just what the data shows, but what it means for their teams.

Related to this point, explore how AI and predictive analytics can help take workload management to the next level. The ability to analyse historical patterns, enables HR to help leaders forecast future workload demands, identify potential bottlenecks, and predict burnout risks before they materialise. These insights enable proactive rather than reactive management strategies.

In our experience what moves data from interesting insight to a practical tool that supports decision making, is the inclusion of  clear, actionable recommendations for managers and leaders. Here HR can draw on job design expertise to suggest specific steps for workload rebalancing, timing for resource adjustments, and strategies for risk mitigation or help to facilitate this conversation between managers and their teams.

Implementation strategies for success

Drawing on our experience implementing workload management solutions across a wide variety of industry groups and clients, we suggest the following approach.  Start with pilot programs in select departments to refine your approach before scaling. Focus initially on collecting high-quality data for core metrics, then gradually expand both the metrics tracked and organisational coverage. This measured approach allows for learning and adjustment while building credibility with key stakeholders.

It’ll take time to build data literacy across the organisation. Invest in training leaders on data interpretation and provide ongoing support for data-related questions. Create user guides for data tools and dashboards to encourage independent exploration and analysis.

As you roll out the pilots, monitor the effectiveness of your data initiatives through adoption metrics, user feedback, and impact measurements. Track how frequently leaders access and use data tools, gather input on additional data needs, and measure improvements in workload-related outcomes. In addition, you’ll find it helpful to compare before and after metrics for key indicators like employee satisfaction, productivity, and efficiency. This evidence helps demonstrate the value of data-driven decision-making and builds support for continued investment in data capabilities.

The future of workload management lies in creating a data-driven culture where leaders routinely use insights to make better decisions. HR professionals, have a crucial role in building and maintaining the systems, processes, and capabilities that make this possible. By providing leaders with better data and helping them use it effectively, HR can contribute significantly to improved organisational performance and employee wellbeing.

If you’d like to know more about how Protime can support strategic workload management, contact simon.garrity@protimewfm.co.uk.