Helping a national restaurant franchise open 1.5x more locations

Helping a national restaurant franchise open 1.5x more locations

This successful restaurant group had grown rapidly, but was now experiencing diminishing returns—leadership had made a promise to continue adding more locations, but franchisees weren’t seeing the results they expected. RestaurantCo hired Bain to reevaluate their growth strategy, and Bain consultants used Bain’s Vantage℠ software to help them find better margins at even greater scale.

These teams helped analyze locations for smarter decisions

Bain’s consulting, data science, and other teams modeled RestaurantCo’s performance and used a site selection tool to build a better model. When this worked, they delivered a customized solution built on top of that software so RestaurantCo’s own real estate team and franchisees could continue making accurate location decisions.

These teams helped analyze locations for smarter decisions

Bain’s consulting, data science, and other teams modeled RestaurantCo’s performance and used a site selection tool to build a better model. When this worked, they delivered a customized solution built on top of that software so RestaurantCo’s own real estate team and franchisees could continue making accurate location decisions.

Advanced Analytics Group (AAG)

Data scientists from AAG helped restaurantCo build a sales predictive model, develop a whitespace assessment, and integrate the results into Bain’s software tool, Vantage℠, for RestaurantCo to use.

These teams helped analyze locations for smarter decisions

Bain’s consulting, data science, and other teams modeled RestaurantCo’s performance and used a site selection tool to build a better model. When this worked, they delivered a customized solution built on top of that software so RestaurantCo’s own real estate team and franchisees could continue making accurate location decisions.

Bain Capability Network (BCN)

BCN helps case teams collect and analyze data. For this case, they helped prepare restaurant performance data for analysis and contributed to a fact base that was used to diagnose how prior locations performed.

These teams helped analyze locations for smarter decisions

Bain’s consulting, data science, and other teams modeled RestaurantCo’s performance and used a site selection tool to build a better model. When this worked, they delivered a customized solution built on top of that software so RestaurantCo’s own real estate team and franchisees could continue making accurate location decisions.

General Consulting

The consulting team led the case. They built a fact base on restaurant development to understand the key drivers that made restaurant locations successful, defined a tool to uncover new unexplored opportunities, and trained stakeholders on that tool. They coordinated with the client throughout the case and ensured the handoff went smoothly.

These teams helped analyze locations for smarter decisions

Bain’s consulting, data science, and other teams modeled RestaurantCo’s performance and used a site selection tool to build a better model. When this worked, they delivered a customized solution built on top of that software so RestaurantCo’s own real estate team and franchisees could continue making accurate location decisions.

Product, Practice, and Knowledge (PPK)

The PPK team sources and disseminates knowledge throughout Bain so every case team can bring the best of Bain to bear. For this one, they helped codify and productize the consulting team’s approach so they could test hypotheses and prepare RestaurantCo’s team to use the tools themselves.

These teams helped analyze locations for smarter decisions

Bain’s consulting, data science, and other teams modeled RestaurantCo’s performance and used a site selection tool to build a better model. When this worked, they delivered a customized solution built on top of that software so RestaurantCo’s own real estate team and franchisees could continue making accurate location decisions.

Research & Data Services (RDS)

The RDS team conducts supporting research into the vast market for proprietary and secondary data. For this case, they provided data on restaurant performance in North America.

These teams helped analyze locations for smarter decisions

Bain’s consulting, data science, and other teams modeled RestaurantCo’s performance and used a site selection tool to build a better model. When this worked, they delivered a customized solution built on top of that software so RestaurantCo’s own real estate team and franchisees could continue making accurate location decisions.

  • Advanced Analytics Group (AAG)

    Data scientists from AAG helped restaurantCo build a sales predictive model, develop a whitespace assessment, and integrate the results into Bain’s software tool, Vantage℠, for RestaurantCo to use.

  • Bain Capability Network (BCN)

    BCN helps case teams collect and analyze data. For this case, they helped prepare restaurant performance data for analysis and contributed to a fact base that was used to diagnose how prior locations performed.

  • General Consulting

    The consulting team led the case. They built a fact base on restaurant development to understand the key drivers that made restaurant locations successful, defined a tool to uncover new unexplored opportunities, and trained stakeholders on that tool. They coordinated with the client throughout the case and ensured the handoff went smoothly.

  • Product, Practice, and Knowledge (PPK)

    The PPK team sources and disseminates knowledge throughout Bain so every case team can bring the best of Bain to bear. For this one, they helped codify and productize the consulting team’s approach so they could test hypotheses and prepare RestaurantCo’s team to use the tools themselves.

  • Research & Data Services (RDS)

    The RDS team conducts supporting research into the vast market for proprietary and secondary data. For this case, they provided data on restaurant performance in North America.

Background

This successful, quick service restaurant company had grown to serve millions of happy customers. But now, at national scale, franchisees were feeling their returns begin to diminish. Hundreds of newly opened stores weren’t achieving their sales goals. Something about the model was not working, yet the company had already announced plans to expand even further. RestaurantCo was at an impasse. They reached out to Bain for help developing a more profitable growth strategy.

Leadership wanted to still deliver the next wave of locations, but do so in a way that would maximize store returns without cannibalizing the profits of existing sites.

The plan

As a first step, Bain’s consulting team worked with RestaurantCo’s real estate development team and franchisees to better understand how recently opened stores were performing. To do this, they deployed Vantage℠, Bain’s software for analyzing a geographic area for retail and restaurant opportunities. Vantage℠ displays potential locations on a map where clients can test hypotheses and use the proprietary geospatial data and algorithm to predict performance. The tool revealed which potential sites were most likely to thrive and which placements might undermine existing sites.

This analysis allowed both teams to run what are known as “counterfactual” scenarios—alternate realities that reveal what might have changed had they chosen the last wave of sites with different criteria. This work confirmed that better site selection could have indeed improved performance. The model discovered that RestaurantCo’s newest sites were achieving diminishing cash-on-cash returns, and Vantage℠ would have advised against most of these locations.

Next, the consultants switched to assessing new, unaddressed areas of opportunity, known as white space.

  • Why was RestaurantCo’s growth plateauing?

  • What role did site selection play in the franchisees’ diminishing returns?

  • How could better site selection have altered performance?

  • How could RestaurantCo’s team continuously select profitable sites?

  • What white space opportunity still existed for RestaurantCo?

  • How would they get buy-in from franchisees to develop a white space solution?

The approach

For the white space analysis, the team applied the Vantage℠ machine learning algorithm to hundreds of geocoded variables such as demographics, the presence of other retailers, proximity to competitors, traffic, and insights into consumers’ habits generated by commercially available, anonymized mobile phone and location data. It identified hundreds of new sites that would be profitable.

After testing, these new high-ROI locations exceeded both teams’ initial expectations. The model ranked them according to their varying levels of attractiveness and suggested which restaurant format might be best for each location. With these findings, RestaurantCo’s development team and franchisees were able to confidently commit to increasing the number of new locations by 1.5x over the next five years.

And then, to allow RestaurantCo to apply this analysis on its own, Bain’s data scientists and knowledge team helped productize a version of Vantage℠ for the client to continue to use. This customized version is now continuously refreshed with new data and its user-friendly interface allows RestaurantCo’s development team and franchisees to explore attractive areas for future stories.

The results

Confident in its new location intelligence, RestaurantCo has been able to commit to far more builds. The stores are more profitable and the franchisees trust the system, which means stronger relationships. Now RestaurantCo knows they’re able to avoid two in three placement mistakes they would have previously made, and it’s cleared their path to growth. All told, it was a big boost to total shareholder return.

Offices involved

Offices involved