Managing your workforce without data is like wearing a blindfold when you’re doing a jigsaw puzzle.
It’s not that you can’t fit the pieces together correctly - it’s just much harder, and requires a healthy dose of luck.
Data provides essential visibility for leaders navigating constantly changing conditions. From fluctuating consumer demand to productivity issues, the right analytics will help make faster, bolder and more effective decisions.
But understanding the value of data and actually integrating it into your workforce management system are two very different things.
So what are the challenges organisations face with staffing data - and how can they overcome them?
Three challenges for staffing data
1. Managing complexity
Employee performance stats, consumer demand projections, employee timesheets - staffing data is a broad category, and that makes managing it all very complex. Add questions around data accuracy to the mix, and you have the perfect cocktail for a very stressed staffing manager.
Some experts estimate that organisations spend between 10-30% of their revenue handling data quality issues, and inaccurate data leads the average company to lose 12% of its revenue. Organisations therefore need to ensure their data is streamlined, accurate and easily shareable.
2. Avoiding ‘tech debt’
The volume and power of staffing data has accelerated considerably in the last few years, as digital systems and apps have made collecting data far easier. Leaders have been understandably quick to act, but rushing to adopt data-driven approaches risks what experts term ‘tech debt’.
Organisations need robust data architecture to make data usable, but this process is often accelerated - pushing their tech systems beyond their limit. McKinsey describes the results as: “poor data quality, rising costs, inconsistencies in data access, and an inability to enrich data with external sources”.
3. Building the right analytics
Data is only as valuable as your ability to produce insights from it. Collecting vast datasets without a strategic plan or effective analytics is more likely to distract or confuse your staffing managers.
What leaders want is the outputs from data analytics. Instead of wrangling data or worrying about accuracy, they should be free to focus on the big questions - like how to evolve their workforce and produce the best possible results.
The solution is using pre-built staffing analytics
ROTA’s workforce management platform is not simply a tool to streamline and improve the staffing process - it is also designed to augment decision making using rich data analytics. The platform already captures vast quantities of vital staffing data - putting it to use just seems an obvious extension of central mission.
Staffing managers can use the outputs to make critical decisions, make strategic plans and gain insight into their workforce’s performance. But workers also benefit, as the platform helps leaders better nurture them and allocate resources to create an optimal experience on each shift.
A few examples include:
1. Demand forecasting
The average UK business is either 30% over-staffed or 16% under-staffed at any point in time. That’s not only wasteful - it’s unpleasant for the poor souls working overtime to keep the ship afloat.
Predictive analytics help leaders match the number of workers on a shift to the likely requirements, to improve efficiency and reduce stress for employees.
2. Performance management
Most performance reviews rely on managers’ subjective ‘read’ of an employee’s performance. While they might use data to supplement their intuition, their assessments are almost certainly shaped by some form of bias.
Staffing data can provide real-time analysis of individual workers’ performance, helping them catch problems before they worsen and reward employees more frequently.
3. Budget allocation
With staffing budgets stretched tight in most sectors, data provides some much-needed release. The right analytics enable managers to locate inefficiencies, optimise spend and create plans that actually correlate with reality.
As a result, employers are less likely to waste money or be spread too thin - and employees are more likely to be given reliable shifts.
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