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Point Sopact Sense at your cleaned dataset and it drafts the SROI value map — outcome by outcome, with a sourced financial proxy and the conservative adjustments — grading each row by the evidence behind it.
In short: An SROI value map lists, for each outcome and stakeholder, the indicator, the quantity, a financial proxy with its source, and the four adjustments — deadweight, attribution, displacement, and drop-off — to reach a net, conservative value. To build one fast, point Sopact Sense at your cleaned dataset; it drafts the value map and grades each row by evidence — green where the value is sourced, amber where a proxy is still a placeholder, red where there's no data at all. The steps below show how, with copy-paste prompts.
An SROI is only as honest as the data under it. Work from a clean dataset with persistent contact IDs, and load your Decision Brief first so Sense knows the decision, the audience, and the evidence standard:
You are the Sopact Sense Assistant working over the [DEMO] dataset (clean data + persistent contact IDs). Load my Decision Brief (decision, audience, outcomes, indicators, evidence standard) first, then wait for my task.
You don't fill the map by hand — you write the prompt that builds it and grades it. This is the one that lays out every outcome with its proxy and adjustments:
Build an SROI value map for [PROGRAM]: per outcome — stakeholder, indicator, quantity, proxy (source), deadweight, attribution, displacement, drop-off, duration, net value. Grade green / amber / red.
Five elements make it work: the dataset (clean data, not anecdotes); the value map (every outcome, every column); the proxy with a source (never an invented number); being conservative (the adjustments only ever reduce the claim); and the grade (green / amber / red at a glance).
Sense returns the value map with every row graded — the outcomes valued with a sourced proxy, the ones still on a placeholder, and the ones with no data behind them. The demo runs on the SROI Investee dataset, engineered to grade one green, one amber, one red:
Run on the SROI Investee dataset (DEMO 07) already loaded in Sopact Sense.
GRADE: green | Employment | valued with a sourced wage proxy; amber | Wellbeing | proxy still a placeholder, TBD; red | Debt reduction | no data collected yet
The green row is an outcome valued with a sourced proxy, the amber row rests on a placeholder proxy that still needs a real source, and the red row is an outcome with no indicator collected at all — nothing to value.
The map is worth most when you fix the row holding it back. Take the lowest-graded element and make it measurable with one realistic change:
Take the lowest-graded element above and fix it using only what the program could realistically measure. Show the before → after grade and the single indicator/edit that moves it to green.
For the investee, that's adding a debt or financial-stress measure at intake and exit — turning the red row from “no data” into a valued outcome.
Generate a decision-first report in your own brand, then a shareable link:
Create a 'missing & incomplete' report from this analysis in Sopact branding [or paste your website URL / brand guideline to apply your own]. List every element graded amber or red, what is missing, and the one input that fixes each. Lead with the decision this report informs.
Create a shareable link for this report and open it in a new tab.
Never let a proxy be invented. The fastest way SROI loses credibility is a financial proxy with no source. Ask Sense to flag any proxy without a named source — those are the rows a reviewer challenges first.
Be conservative on purpose. Deadweight, attribution, displacement, and drop-off should only ever lower the claim. If an adjustment is missing, the value is overstated — ask Sense which outcomes are missing an adjustment.
Value one outcome at a time. Add the indicator Sense suggests for your reddest row, collect it next cycle, and re-run the map — the net value firms up as the data does.
Tighten the dataset while you're here. Ask Sense which outcomes have too little data to value reliably, and what one question would fix each:
Which outcomes in this value map have too little data to value reliably, and what single question added at intake or exit would let me value each one conservatively?
SROI compares the value created to the value invested. You map each outcome to a financial proxy, multiply by the quantity of people who experienced it, then reduce the figure for deadweight (what would have happened anyway), attribution (the share due to others), displacement, and drop-off — to reach a net present value, which you divide by the inputs to get a ratio. The discipline is in the adjustments and the sourced proxies, not the headline number.
An SROI value map is the working table behind the ratio: one row per outcome and stakeholder, with the indicator, quantity, financial proxy and its source, the four adjustments, the duration, and the resulting net value. It's where an SROI is actually made credible — or where it falls apart.
A financial proxy is a money value used to represent an outcome that isn't itself traded — for example, the cost of treatment avoided as a proxy for improved health. A good proxy is drawn from a named, published source and applied conservatively; an invented or unsourced proxy is the most common reason an SROI is rejected.
Open Sopact Sense, paste your program description, and put it to work.
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