Moneyball: How to Use Data Analytics to Level the Playing Field with the Big Chains

Data Analytics, Baseball and Convenience Stores

Last weekend, I was looking for a movie and Moneyball showed up in my suggestions. It’s been years since I’ve seen it. This time, I couldn’t help but notice the parallels between the story of the Oakland A’s and the data analytics challenges faced by convenience store operators. In the movie, Brad Pitt plays Billy Beane, the general manager of the 2002 A’s, a small market baseball team that couldn’t afford to compete with the big clubs. In the movie, he challenges that his management team is focused on the wrong problems. The real problem is that baseball is an unfair game.

Playing an Unfair Game

Convenience store operators face the same problem: it’s an unfair game against the big chains. Why unfair? Because the big chains can afford to spend millions of dollars gathering and analyzing data. As a result, they have a greater understanding of the performance of every store, product and employee. Smaller chains and independents run their stores based on intuition and industry experience, without the help of computer analytics and data. Because of this advantage, large chain stores beat smaller chains and independents on every yardstick. They average 11 times greater EBITDA , and they double in-store sales per square foot ($66.15 vs $32.23).

Do your managers say convenience stores don’t “run by computer”?  Do they say that the only way to run a convenience store is with industry experience and intuition? In the movie, Beane faces a dire situation after his key players Johnny Damon and Jason Giambi are lured away from the A’s by bigger clubs. Against the resistance, Bean adopted a strategy based on data analytics to field a team of under-valued players. That season, the Athletics set the American League record with a 20 game winning streak. They also clinched their division while operating on a third the budget of the big clubs. This accomplishment was so incredible that it caused a revolution – every other MLB team adopted their analytic approach overnight.

For the Athletics, it was “Adapt or Die”. Well, in this time of great change, it is going to be “Adapt or Die” for us, too. Any kind of significant change works to the benefit of those with the data (i.e. the big chains). They can react more quickly, making profits instead of losses when customer behavior changes and defies their intuition and past experience.

COVID-19 Business Impacts

Today when we ask operators what their biggest problem is, they answer “Covid”. They say “We’re going to ride this out until things get back to normal.” We recognize that operating during Covid is an incredible challenge. The pandemic has taken a toll on our families, our businesses, our economy and our spirits. 

But Covid could be with us longer than we expect – it may return each year like the flu.  A large fraction of the workforce may telecommute, reducing gas consumption. It could be years before travel returns to pre-Covid levels or supply chains recover from the disruption, causing significant changes in product mix. Just when things seem to be returning to normal, the next event occurs. Change is constant, and the key to survival is being able to adapt.

Why Keep Playing An Unfair Game

Every time a major disruption like Covid occurs, the big chains are set up to outperform the smaller chains and independents. “The Problem” is that it is not a fair game. Smaller operators do not have real-time visibility into their business operations.

You might ask: “Why do smaller chains and independents keep playing an unfair game?” There are several answers:

  • Until now, data analytics systems were custom built for the large chains at high costs. These costs were absorbed by the big players who could spread them over many stores.  While these same costs would have overwhelmed smaller chains and independents.
  • The smaller chains and independent chains need a data analytics vendor that can lower pricing by spreading costs across many independent chains. However to do this the new vendor would need to handle the wide variety of IT systems typically found in even a single independent chain.
  • Large chains can enforce IT uniformity. Smaller chains are usually built from many M&A transactions that result in non-identical store setups.
  • Large chains can afford big IT organizations that can manage the logistics of installing complex software. Smaller chains don’t have big IT staffs to devote to complex installations.

How to Turn the Tables With Data Analytics

But now Taiga has introduced the first data analytics platform (Our Front Office Platform) that eliminates all these roadblocks:

  • Our Front Office platform can handle all the diverse sources of data found at convenience stores. As a result, Taiga spreads development costs across many smaller chains. This action lowers pricing to a level easily absorbed by smaller chains.
  • Installation is simple. Just plugg Taiga’s patented data dock into the network at each store.  This minimizes discussions with the IT staff. The data dock finds the information produced by each store system and sends it to the cloud.  There our Front Office Platform organizes, analyzes, and displays custom dashboards for managers. Store transactions show up on the dashboard at headquarters (or at an executive’s home office) in approximately three minutes! This is faster and more rea-time than the big chains.
  • Our Front Office Platform has also introduced extended product categorization to the NACS standard.  This categorization allows a comparison of apples to apples across hundreds of product lines.

A Data Analytics Revolution is Coming!

This means there is a revolution in the convenience store industry . You no longer have to play an unfair game! Smaller chains can level the playing field, and even get a jump on the major chains with Taiga’s Front Office Platform real-time data.

Our Front Office Platform will empower you to detect and respond to increased foot traffic as people move about more freely when the pandemic begins to subside. If another external event such as a hurricane or blizzard occurs, the central office will see changes in sell through rates of common and uncommon products immediately. If a new office building or apartment complex opens up and changes buyer dynamics of a single store, our Front Office Platform will send alerts in real-time. The store can then adjust inventory to keep those customers coming back.

Adopting Business Intelligence allowed the Athletics to field a winning team, beat the big clubs and revolutionize baseball. Smaller chains can do the same as  Taiga’s Front Office Platform can level the playing field with the big chains, giving you the ability to identify changes and adapt. In most industries, the smaller companies drive innovation because they are more nimble compared to the bureaucratic establishment.

If you haven’t watched Moneyball for a while, it’s a great way to spend one of these boring Covid nights. This time, you should watch it from a different perspective.  See if you notice that the revolution in Major League Baseball is playing out in a similar way at your hometown convenience store chains.