KFC Leverages Data to Support International Expansion

How does a Fortune 500 company expand strategically in the largest nation in the world, a vast area encompassing 11 time zones, multiple climates and cultures, and a population of 145 million people? This was the question facing fast-food giant Yum! Brands when it set out to establish the fried chicken chain KFC in Russia in 2010. For Tatyana Shamanskaya, who in 2014 began developing the expansion plan as Yum! Russia’s chief development officer for KFC, the answer came from capitalizing on the best available location intelligence.

Global franchise-based corporations increasingly rely on location intelligence to inform complex decisions about planning and development across multiple regions and countries. Their business executives use mapping technology, satellite imagery, and geospatial data on consumer spending and preferences to spot trends ahead of the competition and make smart location-based decisions.

Nine years after KFC’s first foray into Russia, the company is nearing the milestone achievement of 1,000 stores within the country and 2,000 in the region, thanks in part to spatial insight harnessed by Shamanskaya’s team. KFC has also become one of the leading drivers of business for the global Yum! brand. Sales in Russia, CIS and Eastern Europe made up 8 percent of worldwide KFC sales, according to the company’s 2019 second-quarter report. The region is the fried chicken outlet’s fourth-largest market after China, the US, and Asia.

A Playbook for Growth

From the start, location intelligence proved a key asset for the development office tasked with strategizing KFC’s expansion throughout Eastern Europe. “If you talk about new stores opening, then location analysis is of the utmost importance,” Shamanskaya says.

For a multinational franchise operator like Yum! Russia, location intelligence—powered by a GIS or geographic information system—creates advantages on three levels. The insight:

Digital maps have become a highly effective common language as Shamanskaya and her fellow executives communicate with each of these constituencies. “The power of visualization, the power of maps, is really huge,” says Oleg Kiselev, a market planning manager at Yum! Russia who works in development under Shamanskaya. “It really makes people believe in something when they see it with their own eyes.”

Applying Location-based Insight Internally

As the chief business development officer for KFC in the region, Shamanskaya is responsible not only for Russia but former CIS countries, Eastern Europe, and countries like Israel and Greece, adding up to a massive geographic area. Her top objective is opening new stores while simultaneously ensuring that existing stores aren’t closing and sales are growing. The department has come to rely on location intelligence as an indispensable tool to meet those goals, thanks to its ability to highlight location-based patterns that correlate with growth.

KFC has expanded rapidly in Russia since 2010, with roughly 100 stores opening per year. By 2015, sales were rising by an average of 40 percent annually, and KFC had a presence in the majority of Russia’s large metropolitan areas. Still, with restaurants in big cities, KFC is reaching only half of the population, with the other half concentrated in smaller cities whose residents number less than 100,000.

“There is massive potential for where we can still expand and continue to grow,” Shamanskaya says. “But it all stems from analyzing the market and actually identifying these hot spots where we want to be. And this is where location intelligence plays absolutely a key role.” In studying which markets to develop, Yum! Russia and other leading companies use GIS technology to analyze data on population growth; networks of competing chains; consumer demographics; psychographics (a more nuanced, sociocultural profile of customers); nearby transportation; and community hubs like schools, workplaces, and residential neighborhoods. Assembling all this information visually on a map can accelerate the process of developing a market plan.

Shamanskaya sees a direct link between the strength and insights of the company’s market analyses and the speed with which Yum! has been able to successfully expand in Eastern Europe. Apart from China, they are now the fastest-growing region in the Yum! portfolio, with sales expanding 19 percent year over year. Franchise-based companies like Yum! put an emphasis on scaling fast because once KFC or another chain has established multiple stores in an area, it gains brand recognition and can begin to broadly influence customer choice, driving sales across the board.

GIS-powered market planning has allowed KFC to outpace the growth of competitors like Burger King or McDonald’s, which has had a foothold in Russia for over 25 years. At the same time, Shamanskaya estimates that fewer than five KFC stores in the region have closed in recent years. Those kind of impressive metrics demonstrate the soundness of the model to both investment committees and franchisee partners.

Tatyana Shamanskaya of Yum Russia and KFC

If you talk about development and new stores opening, then of course location analysis and location intelligence are of the utmost importance.

Tatyana Shamanskaya, Yum! Russia

Opportunity, Mapped

The development office also relies on location intelligence for one of its most important tasks: ensuring that stores in close proximity don’t cannibalize each other’s sales. “With the franchise business, it’s really important to split your territories wisely,” Kiselev says. Through a GIS-based analysis of walk and drive times for existing or potential stores, Kiselev can predict the probability that a new location will draw customers away from the stores they’re currently frequenting.

It’s an issue that faces franchise-based businesses in all industries. Mattias Wallin, head of market research for US-based agricultural equipment manufacturer John Deere, looks for similar factors in making market predictions.

“The business driver is, ‘Let’s make our dealers successful,’” Wallin told WhereNext in a recent interview. “Let’s give them the insight and analysis that’s going to help them expand in the right ways and not waste their investment making wrong decisions.”

At Yum! Russia, the maps that bring such distinctions to life also allow Shamanskaya and her team to spot opportunities for new locations others might overlook. For example, some regions in Central Russia that are well populated but have lower incomes and are less developed were initially deemed not worth investing in. But an updated survey with additional data, including an analysis of the competition, led the team to reconsider the decision. “We managed to open some very well-performing stores, and we are expanding very fast in the region,” Shamanskaya says.

Similarly, otherwise “invisible” data about credit card activity in what seemed an unpromising trade area alerted Shamanskaya to the strong retail potential in that location. “You may not see the people around, [the] pedestrian traffic seems to be insufficient, but there was apparently a lot of payment activity happening” in the town, she says. After cross-referencing their first impressions with reliable geospatial data, company leaders decided to open a store in the area.

While it is physically impossible for the chief business development officer and her colleagues to be constantly on the ground in the 34 countries they’re responsible for, data creates a new kind of visibility that can bolster the growth of a far-flung web of franchisee partners.

Oleg Kiselev of Yum Russia and KFC

We're giving guidance to our franchisee partners. We're making smart maps to help them make a better business decision.

Oleg Kiselev, Yum! Russia

Empowering Franchisees through Data Analysis

Most of the franchisees that Yum! Russia works with are large, with half of them owning at least 20 KFC stores each. Those business leaders want to know about expansion risks and the likelihood of a return on investment. By walking through market analyses with franchisees, Shamanskaya empowers them to proceed confidently into new markets or find hidden opportunities in crowded retail arenas.

“It’s quite a scientific approach,” Shamanskaya says. “It’s absolutely critical for a partner to know exactly what they should rely on in building this model.” That includes predictions such as revenue per cost, food output, and budget requirements. “It’s in both sides’ interest that there are not unmet or unrealistic stipulations.”

Typically, the first step in working with a franchisee is a top-down analysis—looking at a map of the region, discussing the market development plan, number of stores that could be added, and a timeline for the rollout. They usually plan aggressively, aiming to penetrate at least 70 to 75 percent of the target region.

Once the corporate and franchisee teams are aligned on the market development plan, they break down the region area by area, using GIS-based analysis to identify trade zones with the best chances for success. For instance, data about traffic flow and new office or commercial buildings could point to unexplored trade areas where food chains aren’t yet established. Conversely, a potential location might pass the eye test, but data showing declining population levels in recent years might tell a different story.

“We share the tools with our partners,” Shamanskaya says. “We try to communicate in the same geographical language, lock in on the market analysis and the hot spot priorities, and focus the resources.”

Often the next step is for franchise operators to visit potential sites in person, sometimes accompanied by a member of the development or location analysis team. Through sophisticated GIS technology, they can upload notes, photos, and data from those field visits in real time. That on-the-ground knowledge helps franchisees and the development office adjust strategy and determine priorities for a potential store.

“The technology is helping you prepare in your office, but you still need to go there and check what you see,” Kiselev says. “You have the tool to make a fast evaluation and not lose any feedback.”

Customer Curation through Location Intelligence

In the end, all the planning, analysis, resource allocation, and collaboration come down to the final and most important point: serving the customers who walk in to a KFC restaurant looking for delicious chicken. Here, the advantage lies in the geospatial data KFC can gather on groups of consumers and nearby business drivers. That information helps ensure each store is equipped to satisfy customers in the area and is convenient to their everyday routines.

“To open a great restaurant, I need to understand where my customers are, where people are living, and where people are going,” Kiselev says. A wealth of data creates location intelligence that leads to better customer service—information about demographics; pedestrian traffic; what diners are spending; when they’re spending it; how orders differ for breakfast, lunch, or dinner; and the location of nearby universities, retail hubs, transportation options, and workplaces. With that insight, Yum! Can shift store locations, dining layouts, and menu offerings to improve the guest experience and the store’s business model.

“The most powerful combination is when you can combine location intelligence with consumer insights,” Shamanskaya says. This allows Yum! to tailor store formats and menus to nearby customers, and place ads and billboards where they’ll be most visible and effective in connecting with target groups.

Survey data about customer preferences could guide what kind of store format will be used, affect kitchen solutions, and influence which menu items a particular KFC store offers. Yum! may offer promotions for a particular meal deal or new menu item to attract customers in specific areas. And, a customer loyalty program could create repeat guests who are rewarded over the long term. Data that informs such strategies differs from market to market and Shamanskaya and her team rely on location intelligence to understand those geographic nuances to support better store performance.

Kiselev is looking forward to utilizing not just data about static points, but dynamic data from mobile operators and social networks to connect the dots about customer preferences in a regular research process, furnishing KFC with a deeper understanding of how to keep guests coming back.

Riding the Wave of Change

As KFC’s presence continues to grow in Russia and Eastern Europe, the team’s market analysis will reflect a region more densely populated with stores. Increasingly, Shamanskaya predicts, that will lead to greater innovation in market development as they seek to differentiate stores—experimenting with size, location, and offerings while still meeting investment goals.

The more location-specific data they can collect, the sharper and more accurate their market planning will become. What won’t change is the internal and external constituencies—from franchisee partners to the customer on the street—that location intelligence will help the company serve.

About the authors

Cindy Elliott heads Esri’s commercial industry marketing team. She helps to shape the role of geospatial analytics within the manufacturing industry related to new market analysis, supply chain operations, and advanced services. For more than fifteen years, Cindy has worked with global manufacturers and enterprise class technology companies to influence customer-focused business transformation. Cindy holds a senior visiting industrial fellow position at Aston Business School in Birmingham, UK, and is an established thought leader on servitization and manufacturers’ advanced services. She earned a master’s degree in international management from the Thunderbird Graduate School, and completed Harvard Business School’s Program for Leadership Development.

Gary Sankary joined Esri in 2014 as a subject matter expert in retail after spending 30 years in the industry. Gary’s retail career started in his parent’s family business more than 40 years ago. Along the way he had an opportunity to work with Cost Plus Imports, Mervyn’s and Target Corp. where he led a number of cross-functional teams developing technology and business process strategies to support store and digital merchandising initiatives.

Next Article

A Former “Ghostbuster” Combines Drones, IoT, GIS in Real Time for CSX

Read this article