We Know the Data

Moneyball: How to Level the Playing Field with the Big Chains

Last weekend, I was looking for a movie and Moneyball showed up in my suggestions. It’s been years since I’ve seen it and this time, I couldn’t help but notice the parallels between the story of the Oakland A’s and the challenges faced by c-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 his management team that they are focused on the wrong problems – the real problem is that baseball is an unfair game.

C-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, giving them greater understanding of the performance of every store, product and employee. Smaller chains and independents are forced to 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 tell you that c-stores can’t be “run by computer” – that the only way to run a c-store is with industry experience and intuition? In the movie, Beane was facing a dire situation after his key players Johnny Damon and Jason Giambi were lured away from the A’s by bigger clubs. Against the resistance from industry veterans, including his own manager, 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 and 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 (the big chains), because they can react more quickly, making profits instead of losses when customer behaviour changes and defies their intuition and past experience.

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. At Taiga, we hope that a vaccine will be released in the near future so people can live with greater freedom and shop, work, travel and see family and friends without the fear of getting sick.

But Covid could be with us longer than we expect – it may return each year like the flu. There will be associated events that disrupt business as usual, too. A large fraction of the workforce might decide to telecommute, reducing gas consumption. It could take years for travel to return to pre-Covid levels or supply chains could be disrupted, 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.

Every time a major disruption like Covid occurs, the tables are slanted setting up the big chains to outperform (as in “blow the socks off”) the smaller chains and independents. “The Problem” is that it is not a fair game – 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, 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, but they would have overwhelmed smaller chains and independents.
  • The smaller chains and independent chains needed an analytics vendor that would lower pricing by spreading costs across many independent chains. However to do this the new vendor would need to be able 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.

But now Taiga has introduced the first data analytics platform (StoreKeep) that eliminates all these roadblocks:

  • StoreKeep can handle all the diverse sources of data found at c-stores, allowing Taiga to spread the cost of this development across many smaller chains, lowering the pricing to a level that can be absorbed by smaller chains.
  • Installation is as simple as plugging Taiga’s patented data dock into the network at each store, so only a few discussions are needed with the IT staff. The data dock finds the information produced by each store system and sends it to the cloud where StoreKeep organizes, analyzes, and displays custom dashboards for managers. A transaction at a store shows up on the dashboard at headquarters (or at an executive’s home office) in approximately three minutes! Even the big chains don’t get their analytics updated in this real-time fashion.
  • StoreKeep has also introduced extended product categorization, allowing comparison of apples to apples even across hundreds of product lines.

This means there is a revolution in the c-store industry – you no longer have to play an unfair game! They can level the playing field, and even get a jump on the major chains with StoreKeep’s real-time data.

StoreKeep 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 bringing a new type of buyer into the neighborhood of a single store, StoreKeep will send alerts in real-time so inventory can be adjusted to keep those customers coming back.

Just as adopting Business Intelligence allowed the Athletics to field a winning team, beat the big clubs and revolutionize baseball, the Business Intelligence of StoreKeep can level the playing field with the big chains, giving you the ability to identify changes and adapt. In most industries, it is the smaller companies that drive innovation because they have the advantage of being 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 the perspective that the revolution in Major League Baseball is playing out in a similar way at your hometown c-store chains.