Corporate KPIs could be in for a major shakeup: How AI is remaking the ways companies measure success

Corporate KPIs could be in for a major shakeup: How AI is remaking the ways companies measure success

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What if a firm could tap into expertise from all divisions to inform the all-important KPI of customer lifetime value? Going a step further, imagine a CLV-focused conversation among direct marketing legend Mary Kay, expert copywriter Mary Wells Lawrence, and AI pioneer Kai-Fu Lee—with OpenAI founder Sam Altman and advertising guru David Ogilvy chiming in for good measure. Well, this actually “happened” in a recent ChatGPT 4 session devised by an MIT researcher.

“I basically created dialogues between literally the customer lifetime value KPI and the churn management KPI,” explains Michael Schrage, a research fellow at the MIT Sloan School Initiative on the Digital Economy. “I turned the KPIs into a persona, and this turns out to be something ChatGPT does quite well.”

Schrage’s simulated chat among all-star execs produced a transcript that includes important insights and recommendations for getting the most out of CLV. He believes the findings offer a road map for firms to improve all manner of KPIs—from cash flow to churn rate—while also breaking down corporate silos.

Although the experiment—executives from various companies in various eras coming together for a conversation—sounds like the stuff of sci-fi novels, it’s also a taste of what the future could hold for companies bold enough to reimagine how to measure success.

Using AI and machine learning for KPIs 

The new report, titled “The Future of Strategic Measurement: Enhancing KPIs With AI” and copublished by MIT and Boston Consulting Group (BCG), includes the ChatGPT conversation in the appendix but mainly focuses on a broad array of case studies and surveys on how AI-based machine learning and predictive analytics are superpowering KPIs.

The authors argue that at a time when companies are using AI to transform fields like resource planning, they also should use the technology to reevaluate their KPIs—some of which may be decades old.

AI-enriched KPIs, or “smart KPIs,” improve on legacy metrics that simply track performance, according to the authors, who identified three types of smart KPIs: descriptive, predictive, and prescriptive. 

“What we’re saying is, you’ve invested hundreds of millions of dollars in building data capabilities, technology capabilities, AI algorithms, measurement capabilities—you can direct some of these investments and some of these capabilities to not just improving KPIs, but to redefining them,” Shervin Khodabandeh, a managing director and senior partner at BCG who coauthored the report, told Fortune

The report’s findings are based on a global survey of more than 3,000 respondents representing more than 25 industries and 100 countries. The researchers also interviewed 17 top executives from global companies including General Electric, Schneider Electric, Pernod Ricard, and Wayfair to understand how firms are having approaching this new paradigm in performance measurement.

The researchers found that AI-enabled KPIs strongly impact three aspects of alignment: Teams are more likely to agree on which KPIs to prioritize; KPIs interlinked across a company can be optimized as an ensemble, rather than in silos; and teams are more likely to share information when needed, increasing accountability and alignment.

Perhaps surprisingly, only 34% of the organizations surveyed have used AI to reevaluate KPIs, but 90% of those that did reported improvements. The report also showed that the firms assessing the quality of KPIs with AI were three times more likely to create a financial benefit. 

Schrage said the findings underscore how, especially in digital environments, relationships among KPIs have been harder to understand because of departmental siloes: “I’ve got a cash flow KPI. I’ve got a customer lifetime value KPI. I’ve got a churn KPI. How well do they play together? If I minimize churn, how do I boost the customer lifetime value?”

While AI offers multiple opportunities for companies to create new types of KPIs, Khodabandeh said this doesn’t necessarily mean it’s time to jettison legacy ones—it just means firms should take a more critical look.

How Pernod Ricard is boosting KPIs

Pernod Ricard, a $10 billion global spirits company that sells to both retailers and wholesalers, uses AI to describe and deepen the connection between two of its most important KPIs: profit margins and market share.

At Pernod Ricard, there’s a lag between when new advertising launches and seeing its impact on sales. That’s where AI comes in, Pierre-Yves Calloc’h, the firm’s chief digital officer, told Fortune.

“We have created smart KPIs, which is the return on sales of an advertising campaign—and the promotion uplift of a specific promotion,” Calloc’h said, adding that AI has helped the firm isolate specific impacts of TV and social media campaigns when they’re run in tandem, including the effects of, say, a change in price. He compared the process to isolating elements of a film.

“When you go to the movies, you have the voice of the actor, you have the music, and then you have the noise,” he continued. “And if you don’t have the tools to isolate each of them, it is difficult to identify which is causing a peak of sound.”

At Pernod Ricard, the KPI profit margin has historically belonged to finance, while marketing looked after the market share KPI—but the two are correlated. Now, as Calloc’h points out, it’s possible to use AI to simultaneously assess how a shift in marketing spend might impact both market share and profitability.

Potential pitfalls

Every company defines success differently. And for C-suite leaders, a KPI overhaul plan may sound good in theory, but it can create pain points—especially for employees—if leaders do a poor job putting that plan into action.

Darrin Brown, a former regional sales and operations manager at PPG Industries and Dillard’s, recently took to LinkedIn to describe the pitfalls that can come with KPI plans. Adding new software doesn’t always lead directly to actionable solutions.

“The last time I was involved in a launch, they asked us as employees to create customer profiles for each of our customers, prospects, and leads,” Brown told Fortune. “I had a very large territory with over 400 active customers and who knows how many leads and prospects. The data input took me weeks, and honestly at a point I just quit doing it.”

Implementing KPI software needs to be done with reasonable expectations, Brown added; sometimes companies tend to “get drunk” with what it’s capable of and what they think a successful company looks like.

“I also think that KPIs tend to box together what a road to success looks like,” he added. “In sales, especially, that’s not possible—salesmen pull from their strengths to leverage success.”

Brown does, however, believe that KPIs done right can be of a huge help to companies, especially when it comes to financial goals and managing employees. As for AI, he believes it could improve KPIs, especially when it comes to managing data collection and communication.

Overall, it’s still early days for AI-backed KPIs, but according to the research from MIT and BCG, the firms so far embracing the tech are seeing results: They’re more likely to see stronger alignment, increased collaboration, more accurate forecasts, and more efficiencies.

Although harnessing data to create new KPIs can prove costly and time-consuming, as Schneider Electric’s chief governance officer and secretary general, Hervé Coureil, acknowledges in the report, it’s a necessary part of moving forward.

“We want our KPIs to evolve over time,” he told the authors, “because we don’t want to drive our business on legacy or vanity metrics.”

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