Home Technology Artificial Intelligence Why tools that aid reporting hold the key to ESG success Digital tools that can aid sustainability reporting are as important as any other weapon in businesses’ digital transformation armouries by Bob De Caux November 29, 2022 Every business now has a sustainability manifesto, or at least a stated ambition to operate more efficiently, ethically and responsibly. However, as this metric becomes more and more significant in the eyes of customers, employers, regulators, auditors and partners, how can companies go on to prove that this declared vision is yielding tangible outcomes? And how can that group of onlookers be sure that organisations are practising what they preach? From both sides of the fence, there is a need for data – indisputable evidence that the technologies and innovations being deployed to enhance sustainability performance are hitting their mark. In this regard, digital tools that can aid sustainability reporting are as important as any other weapon in businesses’ digital transformation armouries. The data deluge It’s certainly not the case that data is unavailable to companies, which seems like a good start. Parallel to this rightful obsession with sustainability is a separate obsession with the capturing, storing and analysis of data that can theoretically aid decision-making from that point on. This is where the challenge arises, however. The data deluge that is occurring as a consequence, is often unguided by an initial reason and rationale, or a strategic roadmap for what companies want to improve at the other end of the automation filter. The result is companies drowning in a sea of data, generated by numerous, often misunderstood, tools which can’t be tied together to create meaningful statistics. Sustainability is one of many metrics to suffer when it comes to the fostering of these progress reports, which also puts pay to an ultimate ability to showcase sustainability credentials to the wider industry. What this disconnect, and inability to generate clear reports, also leads to, is a sense of confusion about how to proceed from there. If you can’t clearly see where you’re currently at from a sustainability perspective, how do you know where to improve, invest or refine from that point on? Direct digitisation What businesses need is dedicated software targeted towards outcomes, not simply towards the data itself. Artificial intelligence (AI), in particular machine learning, provides fantastic, necessary tools, but they’re only responsible for interpreting the data they’re being fed, and generating patterns as a result. If these results aren’t focused on specific outcomes and designated strategies, then it becomes extremely difficult to wade through that chaos and find what you’re looking for. And, of course, if there isn’t a strategy guiding the machines, there is also unlikely to be clear guidance for even the best data scientists to follow, either. The solution is to, firstly, deploy solutions that can confirm data’s connection with environmental, social and governance (ESG) ambitions. There are ESG add-on solutions, or even bespoke ESG frameworks within wider products which directly allow users to produce reports and map statistics for progress around said ESG bucket. This could be used, for example, for CO₂ emissions of vehicles, building a remit for the automation tool deployed to gather information around emissions per vehicle and to generate reports around that specific statistic. However, this is only stage one of the digitisation journey. Driving future progress Stage two then has to be an embedded function which not only aids reporting but then points towards solutions and optimisations. Going back to the vehicle emissions example – great, you now have clear visibility over this sustainability metric; but what can your company now do to improve those statistics? Organisations should be looking into bespoke ESG frameworks where data isn’t just more targeted and therefore visible, but it becomes a launching pad for decisions beyond that. After all, reporting, at its core, is more than just an audit document. It’s a gauge of where things are going well, and where they’re not. And only with that level of transparency can reports drive future progress. Don’t fall behind In the outcome-based service world that we are currently moving towards, sustainability epitomises what businesses should be striving for across all metrics. A single source of truth to confirm how efficient your business is can set the tone for a more connected and targeted automation framework across the whole business. Analysts and AI feed off what you precisely want to achieve, while the data being yielded and reported on will give clear pictures of where improvements are required. For those who are already hitting ESG expectations, they will also now have a way to showcase that ability and differentiate themselves in the eyes of those aforementioned onlookers. Just like implicated organisations, service providers are also feeling their way into this environment, and bespoke frameworks as part of broader automation products will only become more advanced in the months and years to come. But if the past two years have taught us anything, this is no time to fall behind. Connecting data to sustainability via bespoke reporting mechanisms that can also inform future decisions is the holy grail for everyone wanting to flex their ESG muscles. Bob De Caux is the vice president of automation at IFS Read: Will it be business as usual after COP27? Tags Artificial Intelligence Carbon Emission ESG IFS Sustainability 0 Comments You might also like UNCCD COP16: Global Drought Resilience Partnership launches, $12bn pledged in support Financial gap to meet SDGs in MEASA hits $5tn annually: NYUAD Leading with passion: The CEO’s journey and strategic goals for Emirates Park Zoo Measurement to action: Carbon management for net-zero success