uniform. Prices can vary drastically between neighbourhoods of the same city. This summer, a one- bedroom property in an upmarket area of London, like Kensington and Chelsea, would cost approximately £2,650 per month. Meanwhile, fifteen minutes away by train in the London Borough of Ealing, you would typically expect to pay around £1,700 per month. Without accurate data, it is
almost impossible to capture the full spread of possible rental prices. And remember rental prices are inconsequential if there’s not enough property stock to secure a property in that location. Some areas can be so competitive – with up to 10–20 potential tenants offering on every available property – that securing a property turns into a game of chance. Setting blanket rental allowances
across an entire city without considering these nuances could lead to mismatches between expectations and reality. It might mean assignees only have the budget to search in areas with low stock levels or an allowance that unintentionally accommodates a life of luxury at their employer’s expense. With such variable prices and stock levels, how can modern GM teams utilise data to set their budgets?
DEPLOYING DATA The first stage is to identify key areas. All relocation providers should, at the very least, be aware of locations favoured by assignees. It is worth highlighting that a relocation provider that completes the entire home search process in-house is more likely to have a comprehensive and consolidated understanding of key areas for each client than one who outsources. In any case, rental allowances
that could make or break an assignee’s relocation shouldn’t be based on anecdotal evidence, as comprehensive as it might seem. GM teams need solid insights to make informed decisions. In the modern, data-driven world, subjective knowledge isn’t enough anymore. We need numbers, maps and graphs. By harnessing real data over
circumstantial storytelling, GM teams can use genuine, actionable insights to inform their decisions.
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There is a wealth of information not currently captured by so many relocation providers. This includes where assignees are looking for homes – not just the area, but also the exact geolocation – when they’re looking, what they’re viewing and where they end up living. Mapping out this data captures
hundreds of stories in a single image, telling us where assignees want to live, where they have been successful and where – importantly – they haven’t. It’s only the GM teams harnessing this level of data that can truly and confidently pinpoint what and where they need to be basing their budgets on. Armed with this information,
GM teams can then tap into rental market data to establish average rents for each property size in each desired location. They can also see the stock levels – whether it’s feasible to search there – and any trends. If assignees are showing interest in a popular area, but there are consistently no rentals within their budget, it’s a clear signal to adjust either expectations or allowances. This is just one example out of
hundreds of how data can improve the accuracy and efficiency of GM tasks. It could, theoretically, be used for everything. By looking at the average number of days it takes to secure a property, HR teams can ensure they offer the right amount of support. Comparing the typical number of days in temporary accommodation to what they provide allows them to adjust as required. And so on. The truth is, data and technology are no longer optional – they are a necessity. Without the right data, GM teams can easily miscalculate, leaving assignees struggling to find a home that fits within their allowance. Companies that leverage the
power of data to set budgets, adjust policies and improve compliance are the ones that will deliver the best results for both their assignees and their organisations. Those that don’t, risk being left behind. In the end, technology and data- driven decision making aren’t just a game-changer for global mobility – they’re a lifeline. And in an industry where the stakes are high, it’s one no company can afford to ignore.
Data mapping Kensington and Chelsea’s rental market
GLOBAL MOBILITY
2 0 TH ANNIVERSARY
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