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tax residency, social security, immigration rules, local labour laws and payroll reporting. Every request can have implications. When nothing is being tracked, the picture becomes unclear and decisions become harder. Measurement changes that. When you have data, you have clarity. Leaders feel more confident that flexibility is being managed responsibly. Teams can point to evidence rather than instinct. And a policy becomes something which can evolve, rather than something that sits in a drawer. What happens when there’s no monitoring in place? Across the WFA roundtables we’ve participated in, the same pattern shows up. Some organisations still have no formal policy and rely on ad hoc decisions. Others have a policy but struggle with consistency. And many have the structure in place but still cannot describe the actual outcomes of their programme. Even among the most advanced teams, measurement is the missing piece. It’s the gap which turns a promising idea into a guessing game. It’s also the gap payroll and reward teams are best placed to close. Cross-border work moves quickly. Tax exposure, social security obligations, immigration limits and payroll reporting requirements can all shift faster than people expect. When no one’s monitoring what’s happening, confidence drops. Approvals become inconsistent. Leaders grow cautious. Not because WFA is the wrong idea, but because no one can see what’s happening. The moment organisations start to track even the basics, the tone shifts. It becomes easier to explain decisions. Easier to reassure leaders. Easier to adjust policies as patterns emerge. The data gap: a normal starting point Most organisations want to measure WFA but are unsure where to begin. Data may be scattered across systems. People struggle to identify what metrics to even measure. Ownership can feel unclear. As a result, even simple things are overlooked: time spent processing requests, changes in advisory spend, shifts in retention among WFA users and whether offering flexibility helps attract stronger candidates. These aren’t advanced analytics. They’re simple starting points. And payroll and reward teams already understand cost, complexity and operational impact better
than anyone else. They know which small pieces of data reveal the biggest insights.
or surveys. Test job posts with and without a WFA policy to see the number of candidates applying for each. Consider trying a pilot group in a smaller business unit or department before scaling. We cover this and other key performance indicator suggestions in our WFA return on investment (ROI) guide 3 , which caters to all types of organisations, no matter where they sit on their WFA maturity journey. Once the basics are in place, everything else becomes easier. The exciting pieces start to come together once you start to look at your data in more detail. Breaking it down by business unit, role type or geography, for example, can reveal trends which support better decision-making. Some also compare engagement or promotion patterns between WFA participants and non-participants. Technology can help, but it isn’t essential at the start. Automated tax and immigration tools, collaboration analytics and simple ROI models can all strengthen the process, but the foundation is always policy clarity first, tools second. A final thought for payroll and reward You don’t need perfect data. You only need a starting point. Once teams begin tracking even a handful of indicators, the conversation immediately becomes clearer and more grounded. Global payroll sits at the centre of accuracy, compliance and reporting, which makes the team a natural home for WFA measurement. When payroll leads the way, organisations shift from assumptions to evidence. WFA is becoming a long-term feature of modern work. The organisations that measure it will be the ones shaping how flexibility evolves. The most important step is simply to begin. P.S. Did you know Work From Anywhere won the CIPP award in October 2025 for Software Innovation Product of the Year? You can find out more on our blog 4 . Links corner 1. Spotify’s ‘Work From Anywhere’ Policy: Lessons Learned: https://ow.ly/ jP5050XRQY2 2. AI meets WFA in Mercado Libre: Using AI in rewards to reduce attrition from 14% to 4: https://ow.ly/LnGp50XRR2v 3. Work From Anywhere ROI: https:// ow.ly/5BMZ50XRR6G 4. Work From Anywhere Wins CIPP Software Innovation Product of the Year 2025: https://ow.ly/3Heo50XRRaR.
A practical way to start measuring WFA You don’t need a dashboard or a full data strategy. Most organisations begin by noticing a few basic signals. One is cost. External advice and / or internal time spent processing WFA requests can add up quickly. Once teams start tracking requests, they often realise they’ve reduced advisory spending simply by building internal clarity. Does your organisation track WFA requests in the first place? Another metric is time. Manual assessments, manager back-and-forth and document reviews can take days. Once you know how long it really takes, it becomes easier to improve the process or to introduce automation. Retention is another clear indicator. We’ve seen strong examples of this. Spotify 1 saw a 15% drop in attrition after increasing flexibility. Mercer’s Talent Trends Report 2 mentioned how Mercado Libre saw voluntary attrition fall from 14% to 4% for employees using its programme. When flexibility keeps people from leaving, the financial impact is significant. Beyond retention, from a talent acquisition perspective, hiring outcomes also shift. Offering WFA can widen the talent pool, increasing your total available market or ‘TAM’, and improve the quality of candidates. None of these metrics are complex. Yet, together, they create a clearer picture. Getting started without making it complicated The best approach is often the simplest. Create a basic request form if you don’t have one already. Track requests in one place. Make sure you measure whether your WFA policy (or lack thereof) is a driver of talent leaving in exit interviews “Shockingly, most organisations introduce a ‘Work From Anywhere’ policy without any way of knowing whether it actually works”
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