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If a client, an auditor, or your own board challenged one of your social value figures tomorrow, could you show where it came from? For many organisations the honest answer is no, and that should worry them long before any regulator gets involved. Social value reporting has grown quickly, but the data underneath it has not always kept pace. The result is a set of numbers that look authoritative and turn out to be hard to stand behind. This piece looks at why that matters now, not later, and what a number you can actually defend looks like.
The number you might not be able to defend
Picture a social value lead opening your latest impact report. The headline figure is strong. Then a small question surfaces. Where did that number actually come from, and would it hold up if someone asked?
That pause is becoming increasingly common because it points to a real gap. Social value measurement has matured faster than the assurance and governance that should sit around it. Organisations learned to count and report impact well before they built the controls that make reporting reliable. And that’s why claims get made in public, written into contracts, and taken to boards on the strength of data that is often self-reported, inconsistently interpreted, and impossible to reproduce.
“Measurement has matured faster than the assurance and governance around the data. The numbers arrived before the controls that make them trustworthy did.”
Danni Aberg, Head of Social Value, Thrive
That single gap creates risk in three directions at once:
- The first is reputational, the risk that a claim fails in public
- The second is contractual, the risk that a commitment you are formally held to cannot be evidenced
- The third – the least obvious but most immediate – is internal. Bad data corrupts the decisions you make about your own social value
Two risks that arrive later
The most talked-about risk is social washing, the social cousin of greenwashing. The danger is not only deliberate spin. Any organisation can drift into it simply by making claims it cannot substantiate.
Trust in unverified claims has already thinned. Consumers, investors, and regulators have grown sceptical, and in that climate even genuine impact can be waved away as marketing. The bar has moved from telling a good story to proving one.
As we discussed in an earlier blog, impact reporting is travelling the same road environmental reporting once took, from loose and unverified toward standardised, governed, and assured. Social washing needs to be overcome not by better messaging, but by better data.
The second risk is contractual. Under the Procurement Act, social value commitments increasingly become formal, published key performance indicators, assessed over the life of a contract. Underperformance carries consequences, and at the far end those consequences can reach as far as exclusion from future work.
Right now, very few social value claims are being tested this way, and the new sanctions are largely untriggered, because the rules are recent.
But this is nothing more than a grace period. The mechanisms exist, the direction is set, and the cost of getting your data in order is far lower while the pressure is still light than it will be once scrutiny arrives in earnest.
Most organisations view these two obvious risks as the only ones, but you do not have to wait for an audit or a contract review to feel the damage. The same weak data is already costing you, inside your own walls.
The risk that is already here
This is the risk that does not wait for anyone else to check. Even if no client ever challenges a figure, even before a single KPI is assessed, poor data corrupts the decisions you make about your own work.
Poor data creates business risk today, even before external scrutiny arrives.
Start with the most important consequence: misallocation. Social value programmes exist to direct money, time, and effort toward the things that do the most good. They can only do this in an optimal way if the measurement is sound.
If the data overstates what one intervention achieved and understates another, you will keep funding the weaker programme and starve the one with greater potential.
Bad measurement misdirects your resources. You spend real budget on the strength of a number that was never reliable, and the opportunity cost lands on the very communities the work was meant to serve.
“Poor data becomes a commercial risk the moment you rely on it. That is true internally long before anyone external ever asks to see your evidence.”
Benjamin Fellowes, Chief Product & Strategy Officer, Thrive
Consider forecasting. Targets, bids, and commitments all get built on a baseline. If that baseline is shaky, you will promise things you cannot deliver, which is how a quiet data problem becomes the contractual problem described earlier. Over-commitment usually starts as over-confidence in a number, and by the time the shortfall shows up in a contract review of the sort commissioning authorities are being required to conduct far more of the original error is long buried.
Forecasting also depends on being able to look backwards cleanly. A number you cannot reproduce today cannot be meaningfully compared against last year’s either, so weak provenance destroys your ability to benchmark and to show improvement over time. When data is scattered across spreadsheets and partner returns, or held in a different system from the one you used last cycle, like-for-like comparison becomes almost impossible, and the year-on-year progress you are trying to demonstrate gets lost in the inconsistency. Capturing data consistently, and validating it at the point it is entered, is what keeps a baseline stable enough to benchmark against at all.
There is also a slower, corrosive cost: trust.
The first time a social value figure falls apart under questioning, your stakeholders stop believing in the next one. Social data loses its authority as a basis for decisions, and the goal so many teams are working toward, getting social impact taken as seriously as financial or environmental performance, slips further away. Credibility is hard to build and easy to lose, and it tends to go internally long before it goes in public.
If you cannot trace a figure back to its source, you cannot defend it, and neither can anyone who relied on it after you.
In social value practice, data routinely passes through partners, suppliers, and delivery teams before it is gathered up and reported. Every handover is a point where the link back to the original evidence can be lost. A number with no traceable origin is a liability waiting to surface, and it can surface anywhere: in a board meeting, in a contract review, or simply in a decision that quietly goes the wrong way because nobody could check whether the figure behind it was real.
“Good data has a few plain qualities. It is evidenced, specific, consistent, attributable, and plausible. When one of those is missing, the number cannot carry weight.”
Michael Bole, Product Lead, Thrive
None of these costs depends on outside scrutiny. They are already in the building, shaping decisions whether or not anyone has thought to test the data behind them.
What a number you can defend looks like
So what does a defensible number actually look like? It helps to walk through a simple, illustrative example.
Imagine a contract reports that it put 100 local people into work, with a financial value attached to each job. That is the headline claim. Now apply the questions an honest analysis would ask.
- First, what would have happened anyway? Some of those people would have found work without the programme. Say that accounts for a fifth of them
- Next, who else helped? If a local college and a government jobs scheme contributed, you cannot claim the full credit, so a further share comes off
- Then, did the programme simply move jobs around rather than create them? If some roles displaced other local workers, that is not new impact either
- Finally, does the benefit last? A job that ends after a few months is worth less than one that endures, so later years should count for less
Run those adjustments and the headline 100 becomes a materially smaller number. That can feel like a loss but it is exactly the opposite.
The adjusted figure is the one you can put in front of an auditor, a client, or a board and defend without flinching. A smaller number you can stand behind beats a bigger number you cannot.
The deeper point is the internal one. That unadjusted figure was not just risky to publish. It was misleading you. If you had believed the full 100, you would have kept backing an intervention doing less than it appeared to, and you would have done it with real money.
The honest number is not only safer to report. It is the only number that tells you what is genuinely working. Defensible data and useful data turn out to be the same thing.
The same discipline is what lets you report honestly against a top-level KPI. Most headline indicators, a single “local people into work” figure, say, are fed by many different activities across several contracts and suppliers.
Rolling those diverse activities up into one number is exactly where overstatement creeps in, because each contributing figure carries its own questions of additionality, attribution, and durability.
Apply the same adjustments you would to a single claim, and the aggregate KPI becomes one you can stand behind rather than a sum of soft numbers. Defensible figures are what keep a top-level KPI honest when the activity beneath it varies widely.
Why now, and what to do about it
Every mature form of reporting has made this journey. Environmental disclosure moved from voluntary and unchecked toward assured and audited. Financial reporting did it long ago, and nobody now imagines publishing accounts they cannot evidence. Social impact reporting is on the same path, and the evidence is already visible.
Thrive’s own research across around 900 ESG and impact reports found that social disclosures are now independently audited more than half the time, and that some organisations are already dropping real impact from their reports because they cannot assure it.
In a recent Thrive validation webinar, only around 9% of attendees said they felt very confident in their data and evidence.
The message is not that regulation is coming to punish you. It is that good data pays off now, in sharper decisions and stronger bids, and de-risks what comes later. Preparation taken early is cheap. Retrofitting under pressure, as many organisations found when CSRD landed, is not.
It also pays off every time you have to produce a report. Pulling diverse activities from multiple suppliers and contracts into one coherent, public-facing ESG report is precisely where provenance gaps surface, usually under deadline.
Data that has been validated and traced at the point of entry is, in effect, report-ready: it cuts the end-of-cycle scramble and rework, and it means the figures you publish can be defended line by line. For anyone whose name sits on the report, that is the difference between publishing with confidence and hoping no one asks where a number came from.
This is the problem the Impact Evaluation Standard was built to solve, and the thinking behind Thrive’s approach of validating data at the point it is entered.
Data that is checked as it goes in, traced to authoritative sources, and reproducible by someone else is data you can defend, and data you can actually use.
Which brings us back to where we began. Could you defend your social value data if someone asked tomorrow? If you can’t answer that question in the affirmative, the least costly time to fix it is right now.
Want to see what defensible social value data looks like in practice? Book a Thrive demo and we will walk you through it.
It is the social equivalent of greenwashing: presenting social impact that the evidence does not support. It can be deliberate, but more often it happens by accident, when an organisation makes claims it cannot substantiate. The remedy is data you can evidence, validate, and trace to source.
The mechanisms exist under the Procurement Act, including published performance indicators and, at the far end, exclusion from future work, but because the rules are recent, few claims have been tested and few sanctions triggered. That is a grace period rather than an all-clear.
Data that is checked at the point it is entered, traced to authoritative sources, and reproducible by an independent third party. In short, if someone asked where a figure came from, you could show them, and they could arrive at the same number.
It misdirects your own decisions. If a number overstates what an intervention achieved, you keep funding work that is doing less than it appears while better work goes without. Poor data creates business risk today, even before any outside scrutiny arrives.
No. Suppliers and buyers feel the contractual side most directly, but the internal risks, misallocated budget, faulty forecasts, lost trust, apply to any organisation reporting social impact, including corporates doing it as part of wider ESG commitments with no procurement mandate at all.
Social impact is the “S” in ESG, and it is following the same path the “E” took toward assurance and verification. Organisations building credible social data now will find their wider ESG reporting stronger and easier to defend as expectations rise.
Alan Boyce
Senior Researcher More articles by Alan >
