Case Study: Carvel

Carvel is the category leader in uniquely shaped ice cream cakes and a nationally recognized brand in premium soft-serve and hand-dipped ice cream. With hundreds of franchised and foodservice locations and thousands of supermarket outlets carrying its cakes, Carvel operates a business where timing, freshness and execution matter as much as demand.

Ice cream is emotional. Operations can’t be.

The challenge:

Seasonal products demand precise execution

For Carvel, much of the business revolves around holidays and events. Products are made fresh, demand spikes sharply and shelf life is short.

“An Easter Bunny Cake doesn’t do us a lot of good the day after Easter,” said Steve Gottlieb, Vice President of Planning and Financial Reporting.

As Carvel expanded its wholesale and supermarket presence, leadership needed a way to understand performance at the store level in detail, not just in aggregate.

What product went into each store
What products sold
What products didn’t
What products came back

Without that visibility, learning from one season to the next was difficult and underperformance could easily hide inside averages.

The decision:

Clearly benchmark store performance

Carvel partnered with Salient to gain a more practical, flexible view of store-level performance that reflected how the business actually operates across regions, routes and products.

The goal wasn’t simply to report sales. It was to measure and defined “good” performance, compare performance fairly and identify where execution could improve.

One of the most impactful shifts came from introducing a consistent way to benchmark stores against one another.

“Average Per Outlet became an excellent way for us to tell, on a relative basis, how well a store is doing,” Gottlieb said.

Rather than relying on raw volume alone, Carvel could now evaluate performance in context:

By region
By market
By chain
By route
By product

That made it possible to distinguish true demand issues from execution gaps.

“You want to know what the average per store is,” Gottlieb explained. “Because that’s the best performance benchmark.”

The outcome:

Prescribed Action. More predictable seasonality.

With clear benchmarks, underperformance stopped being abstract.

When a store lagged behind its peers, teams could drill into the details including product mix, timing, delivery, and to identify the root cause.

“When we find a store that’s underperforming, we can start to understand the problem and resolve it,” Gottlieb said.

That feedback loop turned each holiday season into a learning cycle, improving planning and execution year over year.

Carvel was able to:

Understanding store-level execution
Learning quickly from what worked and what didn’t
Applying those lessons before the next seasonal spike

With insight at the outlet level, Carvel strengthened its ability to deliver fresh products at the right time, in the right quantities and to continuously improve across its entire network.

Carvel’s story shows that even in highly seasonal businesses, performance can improve when benchmarks are clear, comparisons are fair and learning is built into the operating rhythm.