Reinventing data for the push to net zero

At the same time, enterprises in most sectors today understand that treating sustainability solely as a compliance issue is no longer an option. A poorly defined, poorly executed sustainability strategy has significant negative consequences. Here are details on some of these.In Consumer Products and Retail: How sustainability is fundamentally changing consumer preferences, the Capgemini Research Institute found 79 percent of consumers are changing purchase preferences based on sustainability – and that sustainability has the potential to significantly impact customer experience, happiness, and loyalty.

• Organizations in certain sectors – such as automotive, consumer products and retail, and energy – are particularly vulnerable to the impact of sustainability on brand image. But sustainability issues have the potential to affect any organization. For example, just as sustainability strategies inform consumers’ purchasing decisions, they also influence a company’s reputation with its B2B customers and its desirability with potential hires as a place to work.

• Investors increasingly assess net-zero strategies as part of their due diligence before investing in an organization. A poorly-defined strategy makes it harder for companies to attract this important source of funding, and incomplete, inaccurate, or unreliable data is a hurdle in demonstrating the strategy’s effectiveness.

• Climate change and extreme weather events are already having a massive effect on companies across all industry sectors. Without a solid sustainability strategy, it’s difficult for companies to assess risk and take action either to avoid such events or mitigate their consequences.

These few examples make it obvious that sustainability performance and financial performance are intrinsically linked – which is why many companies now assign responsibility for environmental performance to the chief financial officer.

Measurement and innovation

In today’s data-powered business environment, it’s a given that having high-quality data is necessary if a company is to comply with regulations and benefit from a strong sustainability strategy. But few organizations possess the tools, technologies, processes, and culture required to capture, qualify, and activate trusted data. Collecting and managing high-quality sustainability data should be the first objective of every enterprise.

The good news is that once this is achieved the company can start leveraging that data to innovate. AI is a powerful tool for this, able to combine data from across the organization – as well as from upstream and downstream sources such as suppliers, distributors, and retailers – and then derive insights, make recommendations, and share them across business functions and the value chain. Some examples from my work at Capgemini Insight include:

• Building an AI-powered simulator to help a company in the mining sector anticipate and reduce the carbon impact of proposed IT projects

• Applying AI to review the manufacturing operations at another company in the mining sector, to reduce the carbon footprint of its raw materials use

• Using AI to assess consumer shopping behavior, reducing fresh fruit waste for a European retailer

• Implementing AI-optimized processes to help a manufacturer reduce energy consumption, and cost, by seven percent.

Anticipation and digital twins

Companies can also leverage data to anticipate the impacts of sustainability decisions on company performance. For example, subcontractors with excellent sustainability track records are generally not the cheapest option, so enterprises must determine how best to balance financial performance with sustainability performance – and then convince stakeholders such as investors that this is the right decision.

Digital twins are emerging as a useful tool in cases such as this. Digital twins allow enterprises to use their data to create a virtual representation of their operations and then use AI and other technologies to apply simulations to the data and measure the outcomes. Changes can have significant, company-spanning repercussions, both positive and negative, impacting everything from customer satisfaction to financial performance. It’s crucial that decision-makers have the opportunity to test and assess such ideas before implementing them.

As with many new initiatives, companies looking for success should take a pragmatic approach. Articulate a clear vision and focus on internal assets before incorporating data from partners, subcontractors, clients, and other outside sources. AI-derived insights can help decision-makers prioritize sustainability issues. Companies can then focus on a pilot project before scaling up to span the enterprise’s ecosystem.

Data mastery links sustainability with innovation

Companies that become data masters find it easier to supply the information required for compliance with environmental regulations. But that’s just the start. Whether it’s helping R&D develop new products and services, providing marketing with the insights to boost brand image, or identifying potential new business models for the company to consider, data masters can use AI tools and that strong data foundation to help drive innovation, unlock value throughout the company’s ecosystem, and accelerate the organization’s sustainable transformation.

Watch our Linkedin Live where we discussed how organizations, such as Volvo Cars, are leading their path to net-zero:

Innovation takeaways

Sustainability is about more than compliance

Accurate, trusted sustainability data is essential for satisfying regulatory compliance. But many others – from consumers to investors – also demand high-quality data about a company’s sustainability strategy.

AI powers sustainable innovation

Applying AI to high-quality sustainability data is an opportunity to innovate in ways that build brand image, attract investment, reduce operating costs, and mitigate risk.

Find the balance

Enterprises must walk a fine line between sustainability performance and financial performance. AI-powered simulations can help companies stay on the right path while avoiding missteps.

Interesting read?

Capgemini’s Innovation publication, Data-powered Innovation Review | Wave 4 features 18 such articles crafted by leading Capgemini and partner experts sharing inspiring examples of it – ranging from digital twins in the industrial metaverse, “humble” AI, serendipity in user experiences, all the way up to permacomputing and the battle against data waste.. In addition, several articles are in collaboration with key technology partners such as  Alation, Cognite, Toucan Toco, DataRobot, and The Open Group to reimagine what’s possible.