Sustainability Data Automation Checklist

The Sustainability Data Automation Checklist

At the same time, the business landscape is changing quickly with new types of AI. How will you get today’s job done, deliver a smooth transition to the AI-powered future?

Here is what to look for when evaluating the next step in sustainability data preparation.

Determine Your Scope

Determine Your Baseline Cost

Align with Tomorrow

Does Your Next Sustainability Data Preparation System Check All the Boxes?

DETERMINE YOUR SCOPE

The Amount of Effort

To get an accurate estimate of the cost of your ideal system, evaluate the scope of work you are trying to get done: How many sites, sites, buildings, and assets do you want to cover? What services do you want to report (water, waste, electricity, other fuels, and/or emissions? What is your reporting period today, and going forward? How frequently do you want to share fresh accurate data internally and externally? What are the mandated deadlines throughout the year? Automated systems keep costs low at all project sizes and reporting frequency.

The Amount of Variation

Sustainability data is characterized by a very hard problem: Disparate data. This is a fancy expression to say data sources are scattered and siloed, and then when you find the them, the file types and layouts are hugely varied. Think through your requirements for languages, and character sets. Find a single system for the varied formats and layouts. Pin down how exceptions are identified and handled. The inability to handle variation breaks automation and drives up your cost. GLYNT’s data preparation system was built for this challenge, combining years of experience with AI expertise.

The Need for Customization

If you have developers standing by to integrate a standard data output, skip this box. But if you must send your sustainability data to one or more business systems, you’ll need to factor in the cost of customizing and validating your data for each. And what happens if those systems change? Look for a sustainability data solution, like GLYNT, that takes on the burden of customization for you. And maintains and verifies automated, accurate data flows on every data package sent.

DETERMINE YOUR BASELINE COST

Estimate Your Current Hours and Accuracy Rate

To compare alternatives, you’ll need a baseline of current costs. Because a low accuracy rate needs layers of additional data validation and checks, most companies find that the post-data entry cost is 2.5–4 times higher than the cost of data entry itself. A data preparation system that delivers highly accurate data from the start saves time and money.

Detail Your Process and Hours for Complex Data Sources

An unfortunate additional challenge of sustainability data is complex data sources. Invoices with multiple services (such as electricity and natural gas, water and sewer) and multiple locations are difficult to parse, both semantically and with automation. Without a clear plan, these data files may be 15% of your volume and 80% of your cost.

Detail Your Process and Hours for Changes in Data Sources and Assets

The one thing guaranteed in life is change, and sustainability data is no exception. Expect changes in assets (adding a new building, terminating a lease on another) and data sources (procurement switched electricity suppliers to save money). Again, without a clear plan of how these changes flow through your sustainability data, your costs will rise. And this is an area where poor data management processes will quickly lead to inaccurate data.

Detail the Path to a First Internal Audit

Before you spend time and money with external auditors, who are not paid to be forgiving, try out your sustainability data with your internal audit team. This exercise gives the sustainability data preparation efforts a clear focus and timeline, and it will give you the information you need to close the gaps. A good sustainability data preparation solution should get you into an internal audit in weeks, not months.

Will You Need Additional Headcount or Developer Resources?

No one wants to spend more than they have to on climate reporting. But the cost of compliance and audits is fairly high. So, to limit spending, companies often limit access to additional headcount and/or developers. For every path forward you are evaluating, consider the additional resources you you’ll need to to turn into an effective solution. Platforms like GLYNT, do the heavy lifting for you avoiding headcount and developer time.

ALIGN WITH TOMORROW

What Does Year 2 Look Like?

Many analysts have made the analogy between building automated sustainability data flows and the introduction of Sarbanes-Oxley (SOX) reporting standards years ago. A key lesson from SOX is that Year 1 costs were only 80% of Year 2. Costs increase over time as regulations deepen and gaps are closed. To reduce uncertainty, layout your Year 2 agenda and the additional expense. Select a data preparation system that is built for expansion.

Will You Be Ready for an External Audit?

EU regulators estimate that audit costs can be reduced by 15–20% through good data preparation. So, the challenge for your team is both: Are the data files and documentation well organized? Is the compliance checklist complete? This takes extra effort to set up. Look for a solution that does this hard work for you.

How Will You Track and Report Reduction Plans?

In the scramble to get reporting started and to meet the fast approaching deadlines, sustainability and finance teams focus on wrangling the data. But regulators, investors and customers want to know about your emissions reduction plans too. You’ll need a constant stream of fresh, accurate, granular data to identify the high ROI opportunities. You may not want this level of data detail today, but you’ll need it very shortly.

What Are Your Built-In Checks to Avoid Disclosure Risk?

Climate reporting is surging forward in a data-hungry environment. In particular, investors
have all the tools they need to slice and dice your sustainability data. This means every CFO and finance team is walking into a high level of scrutiny from the first climate report, and the opportunity for a disclosure error is high. Layers of data validation and verification are needed to avoid this risk. In other words, your sustainability data should be prepared as rigorously as financial data. Dig deep and work on compliance. Your CFO will be glad you did.

Will Your Data Be Ready for Enterprise AI?

We’re on the cusp of an AI revolution, in which AI reshapes every enterprise workflow. Trusted AI is built on Trusted Data – data that is accurate, verified and contextualized. When data is truly the new gold, don’t forget to check this incredibly valuable box. The AI future is racing towards us.

STREAMLINE ACCURATE, AUDIT-READY FINANCIAL DATA

Get Automated Sustainability Data Preparation

Using GLYNT’s data preparation services delivers more accurate sustainability data at a lower cost than current ad hoc systems. Built on years of experience and deep expertise in finance, sustainability and AI, GLYNT expands to the AI-powered future with trust and ease.

• Are you struggling with sustainability data today?
• Do you wonder how you can get the job done without increasing headcount or using developers?
• Do you have a sustainability data tangle that simply won’t scale?
• Do you want to stop thinking about data entry and start spending time on strategic insights and planning?

If you answered yes to any of these questions, talk to GLYNT. We’ll show you how GLYNT is simply better, faster and cheaper than current ad hoc methods. We’ll feed your sustainability data into systems of your choice, giving you fresh, automated data every day, month or quarter. Click the button below for a short, first conversation. Let’s find out if GLYNT’s AI-powered system, built on years of experience, can help you.