When does a data management system benefit sustainability consultants?

When the same reports are produced periodically, data is provided by several units or suppliers and a time-consuming adjustment is required. For a small one-off job, orderly spreadsheets and documents may be sufficient.

Is it possible to use the calculators available to the client?

Yes, if their data and method of calculation can be verified. Compatible field names, units of measurement, and periods. It also determines who is responsible for data corrections.

How do you assess whether reports are prepared more quickly?

It compares the time for the same set of indicators to be collected, verified and submitted. It also includes the client's work and error correction so that saving at one stage does not hide additional work in another.

Who checks the figures and explanations of the report?

The final review is the responsibility of the designated specialist. The system helps to find sources and calculations, but the team has to work out missing or unreliable information with its provider.

Sustainability and environmental data management system

The consultant compiles environmental and sustainability data for the client, produces calculations and reports. Documents and previous calculations are visible, making it easier to explain the changed result.

The repeated request for the indicator does not rely on the customer's source already available, period and quality check of the previous submission. The customer and consultant search and revise the same data once again.

How the solution works

The consultant aligns the period of the report, the required indicators and the way they are calculated.
The customer and suppliers provide the data and supporting documents.
The team checks for flaws, units of measurement and duplicate records.
Calculations are made, and the responsible specialist checks the result.
A certified report is provided to the client. Subsequent corrections are saved with an explanation.

Key challenges

Customer environmental and sustainability data is re-assembled each time
It is unclear how the indicators were calculated and where the data came from.
The quality of supplier and value chain data is not controlled systematically
Computational methodologies are difficult to apply in another project
The explanation of the indicator developed by AI has no verifiable basis

Solution capabilities

List of report data

The consultant indicates what data is needed by the company and its divisions and for which period to submit them.

Customer and supplier submissions

A document or explanation of how it was obtained is saved to the given number. Defects and data that need clarification are seen.

Calculations and their verification

The data, formulas and coefficients used are saved together. The specialist can check the result before adding it to the report.

Corrections to reports

The correction of the data shows which calculations have changed and why. The previous report submitted to the customer remains available.

Reuse of methodologies

A consultant can use a developed computational methodology in the next work after verifying that it is suitable for a new client and its data.

Preparation of explanations

The explanation of the report is prepared on the basis of verified figures and documents. The specialist reviews the text, including drafts prepared by artificial intelligence.

Business context

Customer environmental and sustainability data is re-assembled each time: The repeated request for the indicator does not rely on the customer's source already available, period and quality check of the previous submission. The customer and consultant search and revise the same data once again.
It is unclear how the indicators were calculated and where the data came from.: The validated indicator is not associated with the calculation limit, units, version of the coefficient and the evidence used. A reliable restoration of the base of the number is not possible during correction or external verification.
The quality of supplier and value chain data is not controlled systematically: The number or alternate estimate provided by the supplier is used without specifying what part of the activity and the period it covers and how reliable the data is. The report seems more accurate than its basis, and a comparison between suppliers may not be justified.
Computational methodologies are difficult to apply in another project: The formula, application conditions, and previous expert correction remain in the separate project file. The methodology is created again or moved to another client without checking its suitability.
The explanation of the indicator developed by AI has no verifiable basis: A data classification or statement draft is accepted without a spent source and responsible methodological review. The final explanation may include an incorrect assumption or another client's confidential information.
The report helps the customer respond to their buyers as well.: In addition to the internal report, the sustainability data client may need a partner questionnaire or supplier assessment. Traceable calculations allow explaining the result presented and updating it more quickly. The consultant has more time left for conclusions and specific customer questions instead of re-collecting information each time.

Core features

List of report data
Customer and supplier submissions
Calculations and their verification
Corrections to reports
Reuse of methodologies
Preparation of explanations

Key integrations

Sources of customer activity and accounting: The fact of a specific scope and the state of its validation or correction.
Sources of methodologies and coefficients: Applied version, period, geographic and operational conditions.
Supplier Submissions: What data the supplier provided, where it came from and how they responded to a request for clarification.
Repository of reports and supporting documents: The value released, its use and access by the client.

Potential impact (%)

The ranges indicate an illustrative relative change in the metric under the stated assumptions. Results depend on the starting position and actual use of the solution. Percentages for different metrics must not be added together.

Work on the development of an approved indicator

12–36%Decreasing

This illustrative scenario assumes that 30-60% of manual data entry and handover work can be addressed. That share is assumed to fall by 40-60%. Company data is needed to verify both the addressable workload and the resulting change.

The active collection, repair and review time for the same set of indicators is measured by the client and consultant.

Time to verify computational data and assumptions

16–42%Decreasing

This illustrative scenario assumes that 40-70% of information searches and repeated cross-checks can be addressed. That share is assumed to fall by 40-60%. Company data is needed to verify both the addressable workload and the resulting change.

Checks how long it takes to replicate the selected previous value and explain its recalculation.

Part of negative feedback on the explanation of report data

4–15%Decreasing

Indicative assumption: 15-30% of negative reviews relate to unexplained report data and assumptions. The solution could reduce this proportion by 25-50%. This is a scenario of potential; the assumptions need to be verified by feedback collected by the company.

When a company starts collecting reviews, negative reviews about the explanation of report data are counted from all assessments received on this topic. The same method of evaluation is applied before and after installation and similar customer groups are compared. Without initial data, the actual change is not determined.

Conditional calculation scenarios. The assumptions have not been validated against client measurements.

When this solution is relevant

For periodic reports, employees re-ask the customer data already provided.
It is difficult to recreate which data and assumptions are based on the previous calculation.

Implementation requirements

Before installation, it is compatible with what indicators the team produces, where it receives data from and who checks it. Calculations, document storage and order of corrections are also discussed. Supplier self-service is included if it facilitates the repeated presentation of information.