Working with Departments: HR, Operations, Finance & Beyond

Working with Departments: HR, Operations, Finance & Beyond

You have shared the data requirement template. The sustainability team has nodded along during the walkthrough call. Now comes the part that no framework document prepares you for: actually getting data out of people who have never thought about ESG reporting and, in many cases, do not particularly want to start now.

Every department in an organization operates with its own priorities, its own systems, and its own language. Your job is to bridge between what the report needs and what each department can realistically provide. Understanding the landscape before you start chasing data will save you weeks of frustration.

The Department-by-Department Reality

Finance and Governance: The Easy Ones

Finance is almost always your most cooperative data source. Why? Because they already track most of what you need. Economic performance, tax payments, procurement spend, executive compensation: this data exists in audited financial statements, annual reports, and board minutes.

Governance data is similarly well-organized. Board composition, meeting attendance, ethics policies, risk frameworks: these are already documented for regulatory compliance and annual reports. You are not asking finance or the company secretary to create new data. You are asking them to share what they already have in a different format.

The typical turnaround from finance: one to two weeks, with minimal back-and-forth.

Operations and Facilities: Scattered but Findable

Environmental data is where things get interesting. Energy consumption might be tracked by the facilities team, the procurement team, or individual plant managers, depending on how the company is organized. Water data could sit with a different team entirely. Waste data might only exist as invoices from waste management vendors.

The challenge here is not that the data does not exist. It is that nobody has ever been asked to compile it in the format you need. A plant manager knows how much diesel they purchased last month because they track costs. But they have never converted that into gigajoules or calculated the associated Scope 1 emissions.

HR and Social Data: The Hard Part

HR data is where most engagements slow down significantly. Some of it is straightforward: total headcount, gender breakdown, new hires, attrition rates. HR systems typically track these.

But then you ask for training hours per employee, broken down by gender and employee category. Or diversity data beyond gender (age groups, persons with disabilities, regional representation). Or employee benefits beyond what is legally mandated. And suddenly you are asking for data that HR has never been asked to compile.

Two categories of social data are consistently the hardest to collect across almost every engagement:

1. Training data. Most companies do not systematically track training hours per employee. They might have records for mandatory safety training, but not for general skills development, leadership programs, or on-the-job training. When you ask, you often get estimates rather than actuals.

2. Supply chain data. Human rights due diligence, supplier labor practices, grievance mechanisms in the supply chain: this data frequently does not exist in any structured form. The company may have policies, but tracking actual implementation across suppliers is a different story entirely.

The Repeated Walkthrough Problem

Here is something nobody tells you upfront: you will explain the same template multiple times to different people, and sometimes to the same people twice.

The sustainability team understood your template during the kickoff walkthrough. But when they forward it to the HR manager, the HR manager has questions. When HR forwards the social section to the training department, the training coordinator has different questions. Each layer of delegation creates a new round of "what does this field mean?"

This is not a failure of your template. It is the nature of organizational communication. Accept it and plan for it:

• Create a one-page FAQ for each section of the template. Anticipate the most common questions and answer them in writing. This reduces the number of calls you need to take.
• Offer department-specific walkthrough calls. A 30-minute call with the HR team specifically about the social data section is more productive than having the sustainability team relay your instructions.
• Be available for quick questions. A five-minute response on email or chat can prevent a data request from sitting untouched for two weeks because someone was not sure what "GRI 404-1" meant.

Different Systems, Different Formats

One of the underappreciated challenges of ESG data collection is that every department uses different software. Finance uses an ERP system. HR uses an HRIS. Facilities might use a building management system or just spreadsheets. Environmental data might come from utility providers, waste haulers, or manual meter readings.

You will receive data in every conceivable format: Excel sheets, PDFs, screenshots of dashboards, Word documents, emails with numbers in the body text, and occasionally verbal estimates during calls.

Your job is to funnel all of this into the standardized template. This means you need to be comfortable with unit conversions, data cleaning, and polite but persistent follow-ups when something does not make sense.

Building Relationships, Not Just Collecting Data

The transactional approach (send template, wait for data, follow up) works for some departments. But for the harder data categories (supply chain, training, environmental), you need to build actual working relationships with the people who own the data.

This means:

• Understanding their constraints. The HR manager is not ignoring your request because they do not care. They are ignoring it because they have 15 other priorities and your data request requires them to pull information from systems they do not usually query.
• Making it easy. If you can tell them exactly which fields in their HRIS contain the data you need, they are far more likely to extract it quickly than if you give them a GRI standard number and expect them to figure it out.
• Giving context. "This data will appear in the published sustainability report that goes to investors and the board" carries more weight than "please fill column D of this spreadsheet."

When You Get Something Back

Data will not arrive all at once. It trickles in: a few tabs filled here, a partial dataset there. When data does arrive, resist the urge to simply file it away and wait for the rest. Start reviewing immediately:

• Does it cover the right time period?
• Are the units what you asked for?
• Does anything look obviously wrong (negative numbers, implausible zeros, wildly different from last year)?
• Are there gaps or blank cells that need follow-up?

Early review means early feedback. If something is wrong, it is much easier to correct when the person who compiled it still remembers where it came from. Wait three weeks and they will have moved on to something else entirely.

The next lessons cover what to do when data simply does not come (escalation strategies) and how to systematically check the data that does arrive (sanity checks). But the foundation is here: understanding that data collection is a human process, not a technical one, and approaching it accordingly.