Uncovering potential ESG blindspots using AI in the Mars-Kellanova acquisition
Uncovering potential ESG blindspots using AI in the Mars-Kellanova acquisition
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Shares in the maker of Pringles surged nearly 20% last week after Mars announced it was considering taking over the $27bn US food giant Kellanova to create a $60bn total revenue behemoth. Kellanova (NYSE:K) which spun out of Kellogg’s last year produces various snacks and packaged foods including the infamous Pop Tart, Nutri Grain and Special K brands. The deal is still subject to regulatory approval and will undoubtedly be scrutinised by investors on many grounds including ESG risks and opportunities. What are these risks and how can AI tools such as Responsible Capital (www.responsiblecapital.io) accelerate identifying and analysing them?
Perhaps most notably Mars is a private company with lesser mandatory reporting and disclosure obligations than the publicly listed Kellanova. However Mars have long been a leader in transparency in the food sector in voluntary disclosures with dozens of disclosures available on their website covering key material sector topics such as human rights, land use change, supply chains and emissions amongst other key topics. Indeed on deforestation, a key material risk for the sector, Mars have scored an impressive #6 ranking in the Forest 500 partly due to strong supply chain policies and disclosures - including publishing regional supplier lists for deforestation risk commodities such as beef, soya and palm oil. So overall a transition from public to private markets in this case may yield positive impacts in bringing Kellanova into Mars’ potentially stronger ESG framework.
How can we assess whether this is a likely outcome however? One approach is taking a top down view and examining ESG scores and other ratings such as CDP scores. Unfortunately given ESG scores predominantly cover public companies this comparison is challenging. LSEG appraises Kellanova with an ESG score of 76 / 100 (as of 9th August 2024) highlighting overall strong performance in most pillars but highlighting Governance weaknesses in litigation risks, auditor tenure, anti-takeover devices and Environmental risks in product recycling / takeback. Unfortunately as a private company no equivalent score or sub-ratings are available for Mars and only SDG alignment is measured by LSEG. So to do any comparison we have to examine raw data in the form of disclosures and third party sources. Whilst this can be challenging to do quickly, GenAI technology and Large Language Models (LLMs) are significantly accelerating the process of running ESG assessments and peer benchmarking. In this case we leverage the Responsible Capital Disclosure Assistant and Bulk Q&A features - let's jump into what we were able to discover in just a few hours of analysis….
Step 1 - Key Facts
Mars is a more diversified company than Kellanova who specialise mainly in the snacks and cereals market. Although the business models of both companies are distinct; frameworks such as SASB can be useful in identifying common ESG risks for the broader Processed Foods sector in which they both operate.
Step 2 - Specific Risks & Controversies
However, the aforementioned risks are very broad and largely theoretical. LLMs can perform a useful function in summarising more specific empirical risks, impacts and controversies companies are exposed to. Using a General Knowledge model such as GPT4o for instance we can rapidly identify more specific and commonly referenced controversies for both companies in the public domain:
Cross referencing this with real news stories in Responsible Capital News Screen we can then measure risk exposure using measures such as news volume and sentiment for particular topics such as those as shown in the heatmaps below. We can see in terms of news coverage for example cocoa supply chain issues are a standout topic for Mars with Kellanova’s news volumes more anchored around labor rights issues.
Step 3 - Disclosure Analysis
We can also use Responsible Capital Disclosure Assistant to assess exposure and mitigation steps for particular issues of concern. For example, Mars has significant exposure to the Ukraine-Russia conflict. Will the Kellanova acquisition add to this exposure or ease it? We can use our Disclosure Assistant to analyse Kellanova’s 96 financial and sustainability disclosures to answer this question. As we can see from the below screenshot Kellanova completely exited Russia in July 2023. As such, an acquisition of Kellanova will diminish Russia in Mars’ revenue mix.
Another capability we can use within Responsible Capital is to examine to what extent companies acknowledge risks identified by external parties, and what steps, if any, they are taking to address them. Interestingly, both companies approach the two widely recognised risks for their sector, Ultra Processed Foods and Deforestation, very differently.
Kellanova in depositions to the UK Parliament have made it clear that they do not believe the term ultra processed food is helpful for consumer guidance and do not acknowledge this as a specific risk in their disclosures.
Nonetheless, Kellanova does recognise broader marketing risks and elevated compliance costs linked to unhealthy food sales.
Step 4 - Benchmarking
Uncovering the deforestation blindspot
Kellanova’s poor performance on cocoa, for which no traceability or certification processes are in place, is perhaps the most significant blindspot in the deal.
LLMs are also very strong at peer benchmarking which is another feature of the Responsible Capital platform available via our Assessment tools. Assessments can be performed on both an entire universe of disclosures and individual types of disclosures for more specific comparisons. Very useful when comparing target and acquiring company’s ESG profiles and analysing lengthy disclosure framework documents. In this case we look at CDP Forests for which Mars disclose a lengthy 235 page report vs a smaller 75 page disclosure for Kellanova. Analysing results on a line by line basis would normally take days - this is just the task for an ESG-AI Co-pilot!
Mars achieves a stronger BABB rating and Kellanova a B-CC rating - however the reasons are not immediately obvious without delving into the detail of CDP Forests disclosures. Using Responsible Capital AI Co-Pilot, we were able to distil the headline differences between the two companies:
- More of a commodity specific focus by Mars
- Mars’ traceability and risk management is more subnational in focus for commodities than Kellanova
- Considerably higher traceability and certification levels by Mars across a many more tiers of suppliers - up to tier 4 for palm oil
- Considerably more ambitious target setting by Mars with 18 targets measured vs just 3 for Kellanova
- Mars is significantly adopting satellite monitoring and geospatial analysis whereas Kellanova’s disclosure suggests this is more limited
- Mars also uses a classification system to determine risk of deforestation and engages with a much wider group of governmental and non-governmental stakeholders and in landscape / jurisdictional approaches
- Mars is aiming for 100% responsibly produced cocoa by 2025, with significant progress in traceability and supplier engagement.
- Mars have more detailed and higher performance disclosures on Deforestation Conversion Free (DCF) volumes
Many of these findings are more clearly demonstrated in the table below with key statistics extracted from each companies’ respective CDP disclosures. Kellanova’s poor performance on cocoa, for which no traceability or certification processes are in place, is perhaps the most significant blindspot in the deal. Given the historical press coverage and controversies around Mars’ cocoa supply chain exposure this will undoubtedly be an area of focus for investors and others.
Note: Various figures extracted from CDP forests reports 2023 - where multiple traceability stats under different regimes for the same commodity are available we have taken the highest % figure per commodity
Conclusion
Historically, analysis of this complexity would take an analyst several days to perform. However, using Responsible Capital, we were able to uncover salient differences between these two companies, and identify potential sustainability risks and opportunities. Both investors focused on these issues, or companies interested in assessing such risks and opportunities in the context a strategic transaction, stand to benefit from leveraging Responsible Capital AI-enabled analytics.
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