We need to speak the same language when it comes to EDI data in FM

In my last blog, I talked about how facilities management measures everything… except people.

But let’s move that on a step.

Because even when we do collect EDI data, there’s a bigger issue sitting underneath it. We’re not speaking the same language.

Across FM, there’s definitely progress happening. More organisations are starting to collect workforce EDI data, asking better questions, and taking EDI more seriously. On the surface, it looks like we’re moving in the right direction.

But when you look a bit closer, it becomes clear why this still isn’t translating into meaningful change. Everyone is doing it slightly differently.

One organisation defines roles one way, another structures them differently. Ethnicity categories vary. Disability data is captured inconsistently. Very few people collect socioeconomic background data. Some collect detailed information, others keep it high-level. Even the way grades, pay bands or job levels are described can differ significantly. And if we drill down deeper into how the data is gathered, there’s yet more variability.  

Individually, none of that feels like a big issue. Collectively, it creates a real problem.

Because the moment you try to step back and look across contracts, clients, suppliers or competitors… it doesn’t line up.

And that matters more than people think.

If we go back to the reality of the FM workforce, we already know it is not straightforward. ONS Census of Population data tells us we are dealing with a sector that is ageing faster than the national average, with high levels of disability and poor health, a heavy concentration of routine roles, and a workforce that is often fragmented across multiple employers, contracts and locations.

It’s a complex environment.

And complexity without consistency creates risk.

Because if everyone is measuring things in different ways, you lose the ability to see what’s really going on. You can’t confidently compare one contract to another. You can’t easily spot where something is improving or where it’s starting to go wrong. And when a client asks you how you’re performing, the answer is often based more on interpretation than evidence.

If you think about it, we would never accept this in any other part of FM.

Imagine if every contract measured SLAs differently. If response times meant different things depending on the site. If suppliers reported performance in completely different formats.

We wouldn’t tolerate it for a second.

It would be impossible to manage, impossible to compare, and impossible to improve.

And yet, when it comes to EDI data, that’s exactly where we are.

The result is a lot of activity, but not always a lot of clarity.

Data is collected, reports are produced, dashboards are created. But without consistency, that data becomes difficult to interpret and even harder to trust. And when data isn’t trusted, it doesn’t get used.

That’s where the “so what?” problem starts to creep in.

You can see numbers, but you’re not entirely sure what they mean. You can spot patterns, but you don’t know whether they’re real or just a result of how the data has been captured. So decisions get delayed, softened, or avoided altogether.

Or, more often than not, they revert back to instinct.

At the same time, expectations are shifting.

Clients are becoming more confident in the questions they’re asking. Not just “what does your workforce look like?”, but “how does this compare?”, “where are the risks?”, “what has changed as a result of what you’ve seen?”

Those are harder questions to answer because they rely on something we don’t yet have as a sector: consistency.

Not perfection. Just alignment. A shared understanding of what we’re measuring, how we’re measuring it, and what good actually looks like. Because once you have that, everything changes.

You can start to see patterns properly. You can identify where risk is genuinely sitting. You can compare across contracts in a way that feels fair and credible. You can track progress over time and actually believe in what you’re seeing.

In other words, the data starts to do what it’s supposed to do.

It informs decisions.

And this is where FM needs to go next.

We’ve already taken the first step, which is recognising that EDI data matters. That in itself is a shift from where we were even a few years ago. But the next step is the one that really makes the difference.

It’s about moving from isolated data points to something more structured. Something that allows us to look across organisations, not just within them. Something that turns individual insight into sector-wide intelligence.

Because without that, we’ll continue to collect data, talk about data, and report data… without ever fully using it.

So the real question isn’t whether we should be collecting EDI data anymore.

It’s this:

How do we make it consistent enough to actually mean something?