The Sustainability Data Buyer’s Guide

#1 Save Time and Money – With Automation

Every sustainability journey started with a spreadsheet, but today, sustainability teams are expected to create measurable business value. Manual processes that once worked for small projects now struggle to keep pace with growing reporting requirements and rising expectations from investors, regulators, and internal teams. An automated data service delivers exactly what’s needed – transforming time-intensive manual processes into streamlined, reliable systems.

Typical GLYNT.AI customers save 70 – 90% over current systems. With our Savings Calculator, you can quickly quantify your potential savings and present a clear, data-backed business case to your finance team.

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A NOTE ON ACCURACY: This Buyer’s Guide does not address accuracy. That’s because automation should produce highly accurate data. The cost to fix bad data is high, and insist on 99% accuracy, with verified testing and reporting. This should be table stakes for an automated sustainability data system.

Takeaway for sustainability teams: Deliver an immediate win by demonstrating time and money savings with an automated data service.

Takeaway for finance teams: Financial data is prepared in a streamlined, automated system. Get the same rigor and efficiency – with cost savings – in an automated sustainability data service.

#2 Liberate More Data Than Ever Before – with Automation

Just a few years ago, sustainability teams had a single mandate: Report. Only four data points were needed: How much energy or water was used, how much it cost, when it was used and the calculated emissions.

Now, sustainability teams must create business value. For example, with rising energy costs everywhere, sustainability teams are now charged with finding energy savings. They have the data, right? In fact, to answer the key business case questions — Where should action be taken? What is the payback of an investment? — sustainability teams need a lot more data. Consider the cost of electricity, which is rising everywhere. To build a case for energy-saving investments, teams need to answer: What is the business case for energy savings investments? Where should this action be taken?

Simple four point data sets simply can’t handle the complexity of how energy is priced, and how usage drives costs. Sustainability teams need more detailed data to build a reliable business case. They need granular data, at the meter level and line-item charge detail structured to quickly identify and calculate the exact amount of cost reductions.

An automated data service has the capacity to capture exponentially more data from every invoice.

Takeaway for finance teams: The header information on an invoice is just enough to pay the bill. But to build the business case for savings, get all the usage and cost data too.

#3 Make Apples-to-Apples Comparisons with Finance-Grade Sustainability Data

To drive business value, sustainability data must align seamlessly with existing business data and decision-making processes.

Here’s a frequent scenario: To win over a key customer, the sales team asks the product manager to show the carbon reduction plan for the product. The product manager must review the carbon content of all inputs, and the carbon added when the product is made. Looking for reductions, the product manager must make tradeoffs: How much should be spent to make that reduction? The business decision requires comparing the cost of change against the carbon reduced. Financial accounting already produces cost per SKU, sustainability teams must deliver emissions by SKU in the same format and timeframe.

Or consider the standard corporate need to forecast revenues, costs and profits. Now planning teams want to add in forecasts of energy costs, emissions, and emissions reductions.

Only finance-grade sustainability data, structured, validated, and fully aligned with business reporting standards can do the job. While spreadsheet-based workflows follow simple linear steps, finance-grade data is produced by a rigorous system with multiple layers of calculations, tests and controls. The system is run by software code and the code can be updated with lessons learned, increasing accuracy and reliability month after month.

Takeaway for sustainability teams: Business impact is a key mandate and it requires better data. Use sustainability data that is as rigorously prepared as financial data.

Takeaway for finance teams: With the rising cost and risk of climate change, this type of business tradeoff will be ever more frequent. Good decision making and risk mitigation requires finance-grade sustainability data.

#5 Make Better Business Decisions with Added Business Data

Surveys show that market leaders are using sustainability data to reduce key costs to manage business risk. Despite the politicization of ESG, companies are investing in data systems, and making corporate decisions that incorporate climate costs and risk.

Sustainability teams can support these new processes by insisting that sustainability data be integrated with business data. Metadata is data about data, and business metadata includes site codes, payment transaction IDs, vendor IDs and so on.

When sustainability data is linked to business metadata, powerful questions can be easily answered: What is the level of energy use at our high-profit sites? Which vendors produce the most emissions? Which products are the most carbon intense? These straightforward business decisions need business data married to sustainability data.