REVENUE STRATEGY & LEADERSHIP

Illustration: Anna Kim, Photos: Adobe Stock

It might be summer, but for high-value, low-price (HVLP) gym Crunch Fitness, it’s bulking season. With 154 locations worldwide in 2016, the brand now boasts over 550 premises globally, padded by expansions into several countries around the world, including new targets in Western Europe and Southeast Asia. The big picture: Crunch is generating growth at a time when other low-cost gyms are struggling to weather broader macroeconomic trends.

The gains didn’t always come easy for Crunch, which opened its first location in New York City in 1989. It filed for Chapter 11 bankruptcy in 2009 and has changed hands twice since 2019. Now, it’s fair to say it’s rocking an impressive pump, with a successful franchise model acting as the backbone of the enterprise.

Revenue Brew spoke with Crunch executives on how they built the momentum and what comes next.

Build it, and they will crunch: While data is essential to how Crunch has built its expansion engine, new CEO Chequan Lewis prides himself on being in a Crunch facility essentially “every day, somewhere.” As a result, he constantly has eyes on what’s resonating with consumers, and what’s not.

“I walked into the gym, and I was like, ‘This seems more crowded than last time I was here.’ I go pull the operations manager, [who said,] ‘You know what? I’ve been getting some complaints about this. It might be helpful if we did [something] different.’ That turns into a decision,” Lewis said.

While rolling out the new “Crunch 3.0” gym layout, Lewis and his team are emphasizing “flexibility, modularity, and adaptability.” These three factors, and the local expertise of individual franchise owners, helped Crunch make in-gym decisions that account for geographic preferences and trends while scaling.

“Sometimes in a secondary town in Wisconsin, you may not have a space that big. It may be 20,000 or 25,000 square feet, so that means you have to make some choices,” Lewis said. “[The local operator] may say, ‘Hot yoga, for example, is a must-have here.’ In another place, they may say, ‘You know what? Hot yoga is just not playing in this market. Don’t put it on me. Let me do the ride studio instead.’”

Read how teamwork helps Crunch’s expansion.—LI

      

Sponsored By PwC

AI’s pricey, and that’s why cost control tools for it aren’t uncommon. But they may not be enough.

The problem is that everyone’s trying to use AI everywhere, so even if token costs are dropping, totals are not.

PwC notes that with how fast AI spend is growing, AI value per cost is pretty crucial for the C-suite to have down pat. It soon may be what allows you to transform operations, enter new markets, and stand up new business models while competitors may still scramble to find the funds.

In this article, PwC explores how CIOs and CFOs can scale AI with discipline to achieve cost efficiency.

Give it a read.

REVENUE OPERATIONS

Illustration: Shannon May, Photos: Adobe Stock

When ChatGPT first spurred a run on enterprise AI licenses, Emmanuel Frenehard resisted the peer pressure.

Frenehard, the chief digital officer at pharmaceutical company Sanofi, said he didn’t want to get locked into contracts that would ingest the company’s lifeblood data. And Microsoft Copilot didn’t seem like much of a productivity boon for the cost at the time.

Instead, Frenehard worked with Snowflake and a Snowflake-backed startup called Elementum to build a central data lake and an internal AI system called Concierge. In the next two years, Frenehard wants 80% of the company’s IT tickets to go through Concierge.

But even given Frenehard’s efforts to avoid these contracts, moving away from outside vendors involves some tricky navigation, especially as each platform increasingly offers its own stable of agents.

“We’re working on new ways of how you prepare the disentanglement of it,” Frenehard said. “Because the last thing you want to do is to be locked in for a long term.”

As companies spin elaborate webs of agents and other AI workflows, the logistics of switching agent vendors or underlying foundation models has become more complicated.

‘A lot messier’

Whereas traditional software is deterministic—a given input always yields a set outcome—a foundation model is a black box that requires extensive evaluation to ensure that the AI won’t do something unexpected. To further complicate the already cumbersome process of vendor switching, best practices around agents are still in flux, token costs are uncertain, and it’s difficult to replicate outcomes in fine-tuned models.

“It’s a lot messier than it used to be traditionally,” Gartner VP Analyst Kjell Carlsson said. “There’s an element of uncertainty that we don’t know how to do migrations in the same kind of way…We’re just not even sure what we need to migrate.”

Keep reading why simple prompts may be the key.—PK

      

STRATEGY

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Many companies aren’t “seeing the game-changing effect[s]” of agentic AIthat they expected, because they’re “not optimizing” how they use the technology, according to Deirdre Ryan, global finance transformation leader at professional services firm EY.

Companies are “apply[ing] agentic AI to existing processes” and “tweak[ing]” them, according to Ryan, who estimates she speaks with two to three CFOs a week. While this may drive some “operational efficiency,” Ryan recommends that companies reimagine what they’re trying to accomplish. Then, determine the tasks needed to achieve this result, and “translate these jobs to an agentic finance workforce” with humans in the loop, Ryan told CFO Brew.

“What we’re saying to clients is that you don’t want to do things differently. You want to do different things—and what do we mean by that? What we mean is, understand the capabilities of these disruptive technologies and build in AI,” Ryan said.

Less strategic. What’s true for agentic AI is true for AI investment generally—the focus tends to be process efficiency. In a Gartner survey of more than 200 finance leaders conducted in March, 45% of respondents said their AI investments in finance lean toward productivity, while 20% said theirs lean toward decision quality.

“Many CFOs are prioritizing AI use cases focused on productivity and efficiency. However, boards place greater emphasis on investments that drive growth, improve decision-making, and deliver competitive advantage,” Shankar Keshav, principal analyst with Gartner Finance, said in a statement commenting on the survey in July.

AI use cases tend to be concentrated in areas “that enhance individual productivity or streamline transactional processes,” but “there is a ceiling to the benefits they return for most organizations,” according to Gartner.

Read about the importance of AI for scenario planning.—LB

      

active pipeline

Stat: 30%. That’s how much pickle-flavored snack sales grew in the past year according to Circana’s data—largely due to Gen Z having an exploratory palate. (the Wall Street Journal)

Quote: “Unhappy consumers buy less than happy consumers. Consumers are quite unhappy by historical standards.”—Carl Weinberg, High Frequency Economics chief economist (Reuters)

Read: New Yorkers can’t stop lining up for this sushi. (the New York Times)

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