Putting the ‘S’ in ESG: How AI and Automation Can Increase Social Impact

Environmental, social and governance (ESG) initiatives will shape brand and customer behavior in 2022 and beyond. Forrester predicts that more than half of adults in the US will regularly purchase from brands that align with their personal values, and this trend will drive brands to focus more than ever on driving their ESG commitments. While each part of ESG has its own framework, the social aspect of ESG is often considered the most difficult to define and follow.

Many avenues can be used to define and orient social impact, including how unconscious and systemic biases can influence employee experiences at work and when consumers interact with brands. Many organizations want to address these biases, but it is not clear which approaches are most effective.

Social impact requires consistent experiences and inclusive processes

Providing consistent, inclusive experiences for employees and customers will undoubtedly improve a brand’s reputation and increase its competitive advantage. But even when intentions are good, human behavior can be inconsistent and unconsciously biased, resulting in a mismatch between a company’s social goals and the associated experiences they provide. For example, an audit of customer service emails from 6,000 US hotels by assistant professors at Harvard and the University of Virginia found that frontline agents were less responsive and helpful to minority customers.

While training can be the quintessential first step to overcoming a customer service bias, the entire premise of implicit and unconscious bias is governed by the assumption that the bias is unknown. So even with training, this response is hard to bend and customers are likely to continue to have negative experiences.

Rather than taking the traditional training approach, we believe that AI and automation technologies have the potential to help companies reduce bias in processes at scale. Organizations can collaborate with experts in business, behavioral economics, and psychology to help identify how biases manifest themselves and affect customer experiences. Using these insights, enterprises can develop automation or AI-based solutions, such as automated email responses or programs that score text for implicit bias, to help employees engage better with customers and reduce the potential for unconscious bias and inconsistency.

From an internal perspective, AI and automation capabilities can also help companies improve employee experiences and foster diversity, which in turn improves organizations’ ability to innovate and even increases market share by 45% year-over-year. For example, automation can help companies screen resumes to level the playing field for all candidates and assess employee performance to improve the consistency of evaluations.

With an arsenal of automation and AI tools available, how can organizations find the best solutions to tackle social inequalities and boost their ESG programs? These are the most important steps.

Build a business case for change

Some brands may start the process because of their commitment to social justice, while others may start because they want to attract talent or retain customers, but ESG also has positive effects on the top and bottom lines, demonstrating that profitability and social wellbeing go hand in hand. can go in hand. By staying consistent with inherent company values, long-term performance can be improved by fostering innovation, trust and loyalty.

Gain insight into and measure existing results

To determine the future course, organizations must look to their past and gain insight into ESG results for accurate measurements. Net promoter scores, employee retention rates, customer churn, and patient outcomes are just a few of the many results companies can use as benchmarks for forecasting future social impact initiatives.

Understand process inputs that lead to current results

Interview managers to understand the criteria they use to arrive at the output, determine which inputs to measure, and decide how to measure them. Consider engaging behavioral and industry experts to conduct interviews and observe processes.

Observation is an important part of the data collection process, to ensure consistency of the starting point and to identify where deviations from the planned process occur. There are often gaps between what people should do under policy, what they say they will do in theory, and what they do in practice. Comprehensive understanding requires looking at theory and intention, as well as practice.

Using outcomes as a benchmark and insight into the inputs, the organization can set criteria for any step in their processes where human behavior introduces inconsistent responses to clients or candidates. At this point, the organization can begin to automate those steps to provide a better and more consistent experience for diverse groups of customers and employees — an experience that can drive loyalty, reduce churn, and improve organizational performance.

By tracking KPIs such as NPS score, churn, candidate interviews, and employee retention rates, organizations can track the effectiveness of their automation for social goals and fine-tune the technology as needed. Over time, companies working to deliver more consistent experiences can strengthen their brand reputation, become more innovative and generate more revenue.

Ying Liu is ServiceNow partner executive at Capgemini Group and Sheila Patel is VP Sustainability at Capgemini Invent.

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