Sales Forecast Models highlight potential opportunities, but theory and practice must work together for success

Sales Forecast Models provide incredible benefit, but it’s also important to understand how to use and interpret them. Much is done to validate inputs, but if the site you are measuring is materially different than the ones used to produce your model, the results will be of little use.

In my previous role as a Real Estate Manager, I’ve pursued hundreds of sites and as the Manager of Capital and New Stores Analysis, evaluated over a thousand. For each investment, we were careful to capture why we gave the go ahead so we could go back and evaluate our hypotheses. One thing I learned early on is the mere presence of demand isn’t sufficient to produce success, and if you’re not careful, it can seduce you into site choices that do not meet expectations.

In these capacities, I had the opportunity to view site selection from both a corporate and field point-of-view. Part of my job was to articulate the selection rationale in terms of the different theories and put them to the test. While it was well-tracked if the store was successful, I always wanted to know why. Models help you find high potential areas, but the “why” helps you choose the right site. Your model is a useful tool if you know what it’s telling you…. and what it isn’t.

Let’s me share an example to help illustrate the point.

The Wrong Side of Demand

North Dallas is growing and there is always a land rush on the new major arteries. One issue with these sites is that they are not yet in the path of customers’ comings and goings. People are near the sites, but don’t go by them. Reps can sometimes use models to validate their desire for these new sites.

Highway 380 is the current high potential road. While it will no doubt be developed someday, currently most people live to the south and everything they do is south of them. There is little reason for them to go north to the road. The term for this is being on the “wrong side of demand”. Lesson: proximity to demand doesn’t mean you are poised to serve it.

It’s easy to see this situation at the edge of town, but less obvious in places bound by highways. Plano, Texas is a target for many retailers – several corporate headquarters and a largely affluent population approaching 300,000. This city’s unique opportunity and its road layout illustrate clear areas of residential and business activity. The lighter areas below have the highest population density, but the least number of businesses and it’s easy to see why. People use the main arteries to get to/from the places they need to go; but they generally don’t go through the center of town. This traffic pattern creates a “hole” in consumption.

If you ran a typical forecast model, it will identify that a lot of demand exists in the yellow area; however, the underlying presumption that customers will naturally pass near probably isn’t true and your Rep would know this. Even in the middle of town, you can be on the wrong side of demand. Not surprisingly, this part of town has many second- and third-generation tenants.

“Swing” Corner

Another example where one can be “almost right” is along major arteries. Sticking with Plano, as a northern suburb of Dallas, most of the “gravity” is southbound. A forecast model showed significant demand along a major North-South artery, but not all corners have equal opportunity:

 

SW Corner: collects traffic from both feeder roads going south (high demand side). They referred to it as the “swing” corner since people swing by on their way to work.

SE Corner: collects returning traffic from people returning east

NE Corner: collects traffic from both sides for people heading north (low demand side) 

NW Corner: collects returning traffic from people returning west. 

While there was lots of traffic at the intersection, only the SW corner would work.. You don’t want the other corners at any price.

Beauty is only skin deep…

While the right site is undoubtedly vital to a successful business, no amount of “pretty” can overcome shallow demand. I too have fallen in love a site that couldn’t fail. Exciting area…. traffic…. surely the model must be wrong. I could go on and on. This is not to say the model is never wrong, but I learned the hard way that if you can’t make a deal that’s viable at or below the model volume, you are usually smart to keep looking. I did the deal and that store came limping out of the gate and never found its footing.

Bringing Theory and Practice Together

The point of all this is to validate the importance of both contributions – store planning and the field. No field person likes it when a corporate “newbie” tells them what to do; similarly, the corporate folks have a broad perspective and don’t like to feel that someone from another area is not respecting their contribution. If blame were properly assigned, I would bet the cost of pride dwarfs many, more visible problems.

So how do you prevent this? One person has to go first and I’ve found that a little humility from the corporate person goes a long way. Quite often the planning person is younger and, because they have so much data, they have a very high trust in the results. Despite all efforts, their trade area lists will include some areas that cannot work; but if they present their targets as recommendations, rather than restrictions, the field is usually much more receptive. If they participate in constructing the argument in favor of the sites the field wants to submit, they are then on the team.

There are certainly situations where the model will miss opportunities – but in existing areas, my experience is that you will produce more good stores faster by working together, than by trying to prove that you are right.

If you would like to learn more about locating the optimal locations, download Tango’s Geospatial Location Platform datasheet below.