Apr 28, 2022
How to get the most out of your sustainability data?
Around this time, many of us are just about done with last year’s sustainability report – not an easy feat, we know! We also know that if you’re done with your sustainability reporting now, you probably spent the past few months fervently collecting all types of sustainability data, crunching numbers, finalizing your sustainability report, and now can’t wait to slam your laptop shut and forget all about this time-consuming task… that is, until you have to do the same thing all over again next year.
It might be tempting to finally take a break from your sustainability data for now, but we’d say that would be a huge mistake. Why? Because data transparency and traceability matter in sustainability , along with many other practical reasons, which we’ll get into in this blog.
In order to understand your company's current impact and to drive actionable change, you need data, and therefore you need to collect data. More specifically, data collection is the process of measuring different variables and collecting all the information related to them. But then what’s next? What do you do with all of the information you’ve gathered from your data collection?
To go through all that rigorous data collection, just to only use the data for a sustainability report, or to keep compliant and safe, would truly be a waste of data and effort. Not to mention you would be missing out on a lot of data-driven insights that could drive significant impact.
There’s so much more you could use your data for! Data is the key to figuring out where you need to improve, and how you can reach your goals. So, let’s dive straight into it: how can you get the most out of your data?
The blog will cover the following topics:
How can you use data to reach your goals?
You probably set some sustainability goals at the beginning of the year. Right now, a lot of companies are trying to reduce their emissions, and perhaps you’ve decided to do the same. More specifically, perhaps you’ve decided to cut your emissions by 20-30% by 2030. So, how should you go about reaching this goal? That’s where sustainability data can be helpful!
Let your data help you reach your goals by putting it to good use. For example, you can use your data to revise your plans and predict if you are on track to reach your targets. As you start to measure your emissions data, you will be able to better predict if you’re going to reach your goal, and when. The data collection can help you gather information, and with more data comes a more precise analysis.
Following the example of cutting your emissions as a goal, here are a few specific ways you could use your data to help you reach your goal. To better understand your greenhouse gas emissions, you can collect and use data from your factory electricity invoices, and with a sustainability software like SustainLab, add a simple calculation that will transform your energy consumption into greenhouse gas emissions. A great tool for this is an emission factor database, and here at SustainLab we have built one that might be right up your alley!
So what happens if you set a goal entirely too high? Or maybe your work towards cutting emissions is not exactly giving the results you wanted? Well, don’t fret - simply let the data guide you, and use it to redefine your plans.
Where do you need to improve?
The road to perfection is never-ending, but good thing there’s data to help with that. Data collection can help you uncover interesting insights that highlight areas of improvement: maybe some areas start to appear more problematic, or maybe some instances where you need to step up your game become clearer. You might also find out about large impacts that were previously unaccounted for, and previously not being targeted.
When it comes to sustainability management, some businesses tend to forget about the importance of their supply chain. In order to fully understand all of your company’s impacts, it is vital to know how to measure what influences your supply chain by gathering data throughout different stages. Comparing data from different parts of the organisation is an essential step to find out where you need to be better. Perhaps there is a department that is responsible for most of the negative impact, and that will need to be dealt with. We know every company has a different structure, and that is why at SustainLab we made sure that customers are able to build and replicate their organisational structure on our platform, so that they can have the choice to collect and analyse the necessary data according to their unique workflows.
In your sustainability journey, you always have to find new ways to improve. With the help of data, finding the best practices will be easier than ever. When you can see clearly where your negative impact lies, figuring out your next steps becomes a lot simpler!
What are you not measuring?
Sometimes it’s easy to see what is already there, but a good sustainability manager knows that it’s a lot more difficult to see the information that is missing. You might have set out the data collection process, and you can clearly see where you need to improve, but is there something that you’re not measuring? Perhaps some hidden areas that might actually enhance your picture of the impact you have?
Let’s take the example of gender data collection. You’ve been tasked to measure the gender pay gap on different seniority levels. You start by collecting data on the gender of your employees, but forget to gather information about the department and seniority of each of your employees. The result? There might be a problem with your gender distribution that you’re overlooking entirely. Maybe the employees in director roles tend to be men, or perhaps some departments are predominantly male or female-dominated. Either way, missing data can be problematic in obscuring insights that might have otherwise been helpful and useful.
And this is why data collection is important. You should always stay on top of your game. By having a thorough data inventory and ensuring you’re measuring everything that could be important, you are enhancing your sustainability impact.
How can you collect data? Lagging vs leading indicators
We’ve talked about what data collection can help you with, but what about the type of data you are collecting? How can you ensure that the data you’re collecting, and the indicators you’re using, can actually enhance change? The key is a new data strategy: the future of sustainability indicators !
There are two types of indicators: lagging and leading. Lagging indicators are what people usually measure. This means they focus on gathering data about things that have already happened. One example could be the number of accidents that have occurred in the workplace. Lagging indicators are easy to measure and are important, but often fail to see the cause of the issues.
Leading indicators on the other hand, measure things before they happen. Leading indicators can be measured once you have enough sustainability data, and are different from lagging indicators in that they work proactively to measure efforts put in place to prevent the issues in the first place. Going back to the example of accidents in the workplace, a leading indicator might identify how to stop accidents from happening, for example, by measuring the number of employees that have gone through a security course training, or the amount of security gear available.
If you want to take things to the next level, leading indicators are the solution for you.Industry sectors have started to abandon lagging indicators in favour of leading indicators. Lagging indicators measure past failures to act on reactively, while leading indicators can help you figure out how to preemptively avoid issues, and create better performance.
How can you improve the process?
Imagine this: you’ve just finished gathering all the data for your report, with the data collection and reporting process fresh in your mind. Except, maybe you’re not completely happy with it, and wish it could be easier. An integral part of gathering sustainability data is questioning how the data is collected. Now is the best time to understand how you can make the process better going forward.
Is the data collection process taking too long? Is the data collection method not the right one for you? Or perhaps the information is not completely accurate, and you can spot several errors when you finally get to the analysis stage? How did you make last year’s calculations anyway?
One way to ensure this doesn’t happen, which more and more sustainability managers are looking into, is investing in software that can help to automate the data collection process. With a software, once you have all your workflows and processes in place, all you’d have to do is to insert new data. Automation can even help in improving the whole sustainability process and enhancing your entire strategy! You finally can focus the rest of your time into making decisions and driving actual change.
Here at SustainLab, we’ve created a sustainability management software that helps you reduce your workload in your sustainability journey with the help of automation magic. The software automatically extracts the data from invoices and documents of all file types, and uploads the extracted data directly into the system. There you can review and refine your data, edit and even add calculations – all while keeping the original files intact. This means better data traceability!
With the data now connected to our system, we’ve made it easy for you to map the data to the relevant KPIs you wish to track. All you have left to do is upload new documents and review the information anytime you want, not just before your sustainability report!
The automation of data collection ensures the information is streamlined into reports, and helps you with already-available data visualisations and dashboards. With a much easier process, you don’t have to lose precious time, and can make change happen. With a sustainability management system in place, you can check on your data every quarter, or even monthly. Just imagine how much more relevant the data would be for decision-making if it can be as recent and often as financial or sales data!
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