Turnover in the UK isn’t just a line item on a balance sheet—it’s a real, pressing problem. Recent research pegs the cost of replacing an employee at roughly £25,000, factoring in lost productivity and recruitment expenses. But the financial impact doesn’t stop there. High attrition ripples across teams, draining morale and creating a cycle where disengagement fuels further departures.
And that’s before we even consider the macro challenges. Post-Brexit, many industries are grappling with a labour market squeezed by skills shortages. Layer on the growing demand for flexible work policies and the contrasting needs of a multi-generational workforce, and the picture becomes even more complex. Yet, retention is where organisations have the power to win—or lose—their competitive edge. Holding onto talent is a cornerstone of organisational stability.
Key takeaways:
- Predictive analytics uses data to forecast and prevent issues like turnover and disengagement.
- Retention in the UK is shaped by skills shortages, generational differences, and demand for flexible work.
- Predictive analytics helps organisations identify drivers of retention, spot disengagement early, and address cultural gaps.
- Start by auditing workforce data, choosing a platform, and setting measurable benchmarks.
- Retention reflects organisational health and requires action based on clear, honest insights.
What is predictive analytics?
Predictive analytics transforms raw data into foresight. It is a specialised branch of people analytics that focuses on forecasting future outcomes using historical and current data. It uses algorithms, statistical models, and historical patterns to forecast future outcomes.
Predictive analytics connects the dots in ways traditional people analytics methods can’t. Where people analytics paints the current picture—engagement scores, demographics, and performance data—predictive analytics forecasts the storm clouds ahead. It anticipates what could happen next and provides data-driven insights to prevent problems like turnover or declining morale. Organisations to act before challenges spiral out of control.
What predictive analytics can do for retention
Retention is a measurable outcome. Using data like sentiment analysis, pulse survey responses, and engagement scores, organisations can track warning signs of attrition. If a team is showing a steady decline in satisfaction metrics, analytics can pinpoint whether the cause is leadership, workload, or a lack of career development opportunities.
The value lies in what happens next. Predictive analytics allows organisations to act before an employee’s resignation letter lands on a desk. Whether it’s tweaking a policy or addressing a specific workplace issue, the insights lead to real interventions that make employees want to stay.
The UK context: unique factors influencing retention
Retention challenges in the UK are shaped by a distinct mix of economic pressures, cultural expectations, and regulatory demands. From the aftermath of Brexit to the shift toward hybrid work, organisations face evolving employee expectations that can make workforce management a moving target. Predictive analytics offers a way to stay ahead by identifying the factors most relevant to retention in this context.
Flexibility expectations
The demand for flexible work in the UK has surged. A 2023 survey by CIPD revealed that 78% of employees now view flexible working as essential when considering a job offer. This is a redefinition of workplace norms. Employees no longer negotiate for hybrid options—they assume them.
Predictive analytics helps organisations navigate this shift by analysing how flexibility impacts engagement and retention. For example, it can show whether employees with fully remote roles report higher job satisfaction or whether hybrid arrangements lead to higher productivity. By examining these patterns, organisations can refine policies to match their workforce’s preferences, ensuring they stay competitive in attracting and retaining talent.
Generational differences
The UK workforce spans four distinct generations, each with unique priorities. Younger employees often seek rapid career progression, mentorship, and purpose-driven work, while older generations prioritise stability, benefits, and work-life balance. This diversity makes retention a challenge: What appeals to one group may alienate another.
Predictive analytics bridges this gap by identifying trends within generational groups. For example, data may reveal that Millennials are more likely to leave due to stagnant career paths, while Baby Boomers value strong healthcare benefits. With these insights, organisations can tailor retention strategies to specific demographics, addressing their priorities without alienating others.
Compliance and fairness
In the UK, equal pay and diversity laws are more than just guidelines—they’re enforceable requirements. The Equality Act 2010, along with gender pay gap reporting regulations, holds organisations accountable for workplace equity. But compliance is only part of the equation. Employees want more than legal adherence—they expect fairness and transparency.
Predictive analytics ensures organisations meet these requirements, by highlighting disparities in pay, promotions, and leadership opportunities in order to close gaps before they become liabilities.
How UK organisations can apply predictive analytics today
Retention starts with clarity. What makes employees stay? What drives them away? Predictive analytics doesn’t deal in guesswork—it identifies patterns in the data to answer these questions. It gives organisations the tools to take deliberate action, whether it’s addressing engagement issues, improving workplace culture, or focusing on the factors that matter most to their people.
Identify retention drivers
The first step is understanding what matters most to employees. Data can reveal if career progression, team dynamics, or benefits are driving engagement—or if they’re driving people away. Metrics like promotion frequency, workload balance, and even manager feedback scores tell the real story of why people stay or leave.
Target disengagement early
Waiting for exit interviews is like closing the stable door after the horse has bolted. Tools like Diversio’s Recommendation Engine™ spot disengagement long before it becomes a resignation. Whether it’s a sudden drop in engagement surveys or a spike in absenteeism, analytics flags issues in real time, allowing interventions when they matter most.
Refine workplace culture
A workplace can be a maze of unseen challenges. Predictive analytics shines a light on those hidden corners, uncovering inclusion gaps, pay inequities, and mismatched leadership. With this clarity, organisations can act decisively to build a culture where employees feel valued and heard.
Getting started with predictive analytics
1. Audit your current workforce data
Start with what you have. Are you tracking engagement surveys? Do you know turnover rates by department? Identifying gaps in your data is the first step to improving retention analytics. Do you break down this information by department, role, or demographic group? For example, understanding which teams have higher turnover rates or whether certain groups feel less engaged can highlight where to dig deeper.
Consider data sources beyond surveys, such as exit interview trends or performance reviews, to build a more complete picture. A thorough audit can help you uncover not only what you’re missing but also which metrics need more regular attention.
Diversio streamlines audits by consolidating data like engagement scores, turnover rates, and inclusion gaps into one platform. Its custom dashboards reveal trends by department, role, or demographic group, while tools like Inclusion Metrics™ highlight key areas for action, saving time and ensuring clarity in your retention strategy.
Pro tip: Create a data checklist that includes engagement surveys, turnover rates, absenteeism, and even qualitative feedback like comments from employee surveys. Regularly review this checklist to keep your data fresh and relevant.
2. Choose the right platform
Not all analytics tools are built the same, and choosing the wrong one can lead to frustration and wasted resources. Look for platforms that offer more than just raw data collection. For UK businesses, tools like Diversio’s Platform stand out by combining customisable surveys with real-time insights and dashboards designed to uncover actionable trends.
The right platform doesn’t just collect data—it should provide clarity. Can it help you pinpoint at-risk employees? Does it offer benchmarking tools to compare your organisation’s metrics to industry averages? Can it generate insights that guide action, like highlighting teams where engagement is dropping or leadership support is weak?
What to look for:
- Customisation: Tailor surveys and analytics to match your organisation’s structure and challenges.
- Integration: Ensure it connects with existing systems like your HRIS.
- Data security: Platforms must comply with GDPR and protect employee data.
3. Set clear benchmarks
Data only becomes powerful when it’s put into context. Before you start analysing, define what success looks like for your organisation. Are you aiming to reduce turnover by a specific percentage? Improve engagement scores in underperforming departments? Benchmarks give you a point of comparison and help track your progress over time.
For example, if your current turnover rate is 18%, setting a goal to bring that down to 14% within a year gives your team something concrete to work towards. Similarly, if engagement scores are consistently low for employees with less than two years of tenure, use that as a focus area for improvement.
Benchmarks should also be flexible and evolving. Reassess them quarterly or biannually to make sure they reflect current priorities and challenges.
How to set benchmarks:
- Start with a baseline: Gather your current metrics to understand where you are now.
- Align with business goals: Link retention and engagement goals to broader organisational objectives, such as productivity or growth targets.
- Be realistic: Ambitious goals are great, but they need to be achievable based on your resources and timeline.
Conclusion: Embracing the data-driven edge
Retention isn’t just a numbers game. Who stays and why tells a story about culture, leadership, and purpose. Are you offering more than just a paycheck? Do your values go beyond slogans on a website?
Predictive people analytics doesn’t provide easy answers, but it does reveal the patterns beneath the surface. It shows how trust erodes when pay is unfair, how leadership fails when inclusion feels performative, and how disengagement spreads like a quiet wildfire when employees don’t feel seen. It pushes organisations to confront the realities they might not want to see.
For UK businesses, the stakes are rising. Employees are making decisions based on a company’s culture as much as its job descriptions. The question isn’t whether retention matters—it’s whether your organisation has the courage to act on what the data is already telling you.
The organisations that thrive in the next decade will be the ones that embrace this challenge. Not just with tools and metrics but with action, honesty, and an openness to change. So, where does your organisation stand? Book a demo with Diversio today, and let’s find out.
