08/02/2022 | Press release | Distributed by Public on 08/01/2022 23:17
As societies strive to become more sustainable, jurisdictions such as Europe and California are leading the world in establishing regulations governing environmental performance - including but not limited to carbon emissions, packaging, waste, and pollution. Laws vary by industry sector and jurisdiction but, regardless of the complexity this creates, it's essential that organizations comply with all regulations.
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.
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:
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.
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.
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