Building & Sharing the Data Requirement Template
If there is one document that defines the success or failure of your ESG reporting engagement, it is the data requirement template. This is the Excel workbook you share with the client that tells them exactly what data you need, in what format, for what time period. Get this right, and data collection becomes a structured conversation. Get it wrong, and you will spend months chasing fragments of information across departments.
What Is the Data Requirement Template?
The data requirement template is a structured Excel workbook based on the GRI Standards framework. Most consulting firms already have a version of this ready to go: it is one of those documents that gets refined over dozens of engagements and passed down within the team.
The template organizes data requests by GRI standard series:
- GRI 200 series (Economic): Revenue, economic value distributed, procurement spend, tax, anti-corruption
- GRI 300 series (Environmental): Energy consumption, water withdrawal, emissions (Scope 1, 2, 3), waste generated, biodiversity impacts
- GRI 400 series (Social): Employee headcount, diversity breakdown, training hours, health and safety incidents, community investment, supply chain labor practices
Each row in the template corresponds to a specific GRI disclosure. Each column asks for data across multiple years - typically the last two to three years plus the current reporting year. This multi-year structure is important because ESG reports almost always include trend data, and rating agencies specifically look for year-on-year progress.
You do not share the entire GRI universe with every client. If the company has past reports and you have done peer benchmarking, you select only the relevant indicators from the 200, 300, and 400 series. Sharing the full suite overwhelms the client and signals that you have not done your homework.
Tailoring the Template to the Client
This is where your peer benchmarking and materiality work pays off. Before sharing the template, you should already know:
- What peers are reporting: which GRI standards they reference, which metrics they disclose
- What the company has reported before: if they have past sustainability reports, review which indicators they covered
- What is material: based on the materiality assessment (whether existing or freshly conducted)
Using these three inputs, you narrow down the full GRI catalogue to a subset that makes sense for this specific company. A manufacturing company might need GRI 302 (Energy), 303 (Water), 305 (Emissions), 306 (Waste), 401 (Employment), and 403 (Health & Safety). A financial services firm might skip most of the 300 series but focus heavily on 205 (Anti-corruption), 401, and 405 (Diversity).
Example: Tailoring for a mid-size manufacturing company
After benchmarking five peers in the same industry and reviewing the company's one previous sustainability report, you select the following GRI standards for the data template:
- Economic: 201 (Economic Performance), 204 (Procurement Practices)
- Environmental: 302 (Energy), 303 (Water), 305 (Emissions), 306 (Waste)
- Social: 401 (Employment), 403 (Health & Safety), 404 (Training), 405 (Diversity)
That is 10 standards out of a possible 30+. Each standard has multiple disclosures, so even this subset generates a substantial data request, but it is focused and justified.
The Template as a Communication Tool
Here is something that is easy to overlook: the data requirement template is not just a data collection instrument. It is your primary communication tool with the client during the early phase of the engagement.
When you share the template, you are telling the client three things simultaneously:
- What you need from them: specific metrics, specific years, specific units
- What the report will cover: the template previews the scope of the report
- How much work is ahead: the size of the template gives the client a realistic sense of effort
This is why you cannot just email it and wait. The template needs a guided walkthrough.
How to Share It Effectively
The worst thing you can do is email a 50-tab Excel workbook with a note saying "please fill this out." Here is what actually works:
Step 1: Schedule a walkthrough call. Walk the sustainability team through the template tab by tab. Explain what each field means, what units you expect, and where they might find the data internally.
Step 2: Provide field-level guidance. For each data point, add a guidance column or comment explaining:
- What the field is asking for
- What unit to use (kWh, GJ, tonnes, litres, etc.)
- Where this data typically sits (HR system, utility bills, ERP, manual records)
- Whether it is mandatory or optional for the report
Step 3: Assign department owners. Help the sustainability team map each section of the template to the internal department responsible. HR owns the social data. Operations owns energy and waste. Finance owns economic performance. This mapping prevents the sustainability team from becoming a bottleneck.
Step 4: Set interim deadlines. Do not set a single deadline for the entire template. Break it into phases: economic data by week 2, environmental data by week 4, social data by week 6. This creates momentum and lets you start writing chapters as data arrives.
Think of the data template like an architect's specification sheet for a house. You would not hand a contractor a vague note saying "build me a house." You would give them precise measurements, material specifications, and timelines for each phase. The data template does the same for your report: it turns a vague request into a structured plan.
Common Mistakes When Sharing the Template
Asking for too much at once. If the company is a first-time reporter, even a tailored template can feel overwhelming. Consider phasing the request: start with the data they definitely have (economic, governance) and follow up with the harder stuff (supply chain, training hours).
Not explaining why. Department heads who have never dealt with ESG reporting will push back on data requests that feel arbitrary. For every data point, be ready to explain why it matters: "This is required by GRI 305, and your peers all disclose it. Rating agencies specifically look for this metric."
Assuming they understand the units. Energy data can come in kWh, GJ, MWh, or even litres of diesel. Water can be in kilolitres or cubic meters. Emissions can be in tonnes or kilograms. Specify exactly what you want, or you will spend weeks converting and reconciling.
Not requesting historical data. A single year of data has limited value in an ESG report. You need at least two years, ideally three, to show trends. Make this clear from the start: going back to request historical data later is much harder than asking for it upfront.
The data requirement template is your contract with the client. Every field you include is a commitment that you will use that data in the report. Every field you leave out is a decision that this metric is not material enough to include. Treat it with that level of seriousness.
What Happens After You Share It
Once the template is shared, the client goes into data collection mode. This is where you enter what many consultants call the "silent period": the client is working internally to gather data, and your inbox goes quiet.
Do not mistake silence for progress. The next few lessons will cover what happens during this phase: working with individual departments, escalating when data does not come, running sanity checks on what does arrive, and maintaining version control as data gets updated multiple times.
The template sets the stage. Everything that follows depends on how well you built it.
Key Takeaways
- 1The data requirement template is your primary communication tool with the client - it defines scope, sets expectations, and structures the entire data collection phase
- 2Tailor the template using three inputs: peer benchmarking results, the company's past reports, and the materiality assessment - never share the full GRI universe
- 3Always walk the client through the template live rather than emailing it cold - schedule a guided walkthrough call
- 4Add field-level guidance (units, data sources, mandatory vs. optional) and assign department owners to each section
- 5Set phased interim deadlines instead of one final deadline - this creates momentum and lets you start writing chapters as data arrives
- 6Request at least two to three years of historical data upfront - going back for it later is significantly harder