By the time this article is published, the nation’s largest car wash facility should be open for business in Englewood, CO.
This car wash is the brainchild of Boise, ID-based Metro Express Car Wash whose mission is to give cars the attention to detail of a hand wash with the low price and efficiency of an automated wash. The company’s value proposition is customers will feel better in a clean car in only five minutes.
Metro’s plan to achieve this is to retrofit a 34,000-square-foot warehouse with two conveyors capable of washing a total of 5,000 cars a day. Reportedly, the wash will employ between 14 and 16 workers, and prices will range from $8 to $16.
In the July 2015 issue of Auto Laundry News (Finish Line column), I suggested a huge car wash would be potentially disruptive and offered some counter arguments that competition is good for consumers and the industry.
The disruption I’m referring to is described in The Innovators Dilemma, a book written by Clayton M. Christensen, Kim B. Clark professor of business administration at Harvard Business School. Unlike his predecessor, economist Michael Porter, who was interested in why companies succeed, Christensen was interested in why companies fail.
Christensen argued one reason for failure isn’t because executives made bad decisions but because they made good decisions — the same kind of good decisions that had made those companies successful for decades. In short, the “innovator’s dilemma” is that “doing the right thing is the wrong thing.”
Christensen argues the problem is the velocity of history, and isn’t so much a problem as a missed opportunity. For example, manufacturers of mainframe computers made good decisions about making and selling mainframes and devising refinements or “sustaining innovations.” However, by pleasing mainframe customers, they missed out on what customers really wanted — personal computers.
This market was created by what Christensen called “disruptive innovation” or selling a less-expensive, lower-quality product that initially reaches less-profitable customersbut eventually takes over and devours an entire industry.
Tech bloggers insist there is something even scarier called “big bang disruption” or devastating innovation. They cite smartphones and apps, which wrecked travel agencies, record stores, mapmaking, fleet dispatch, and other businesses.
So, the question is — will Metro’s huge express-exterior car wash disrupt or possibly devastate the market?
What might be disrupted is a trade area with a population density of 3,000 persons per square mile and roughly one car wash per square mile and almost an equal number of detail businesses. The area is a retail district, and there is a good variety and density of stores with most major brands present.
However, in the first ring of suburbs, the concentration is working-class and lower-income households. The majority of these homes were built before 1960, measure 1,000 square feet or less, and most do not have parking stalls.
Similarly, the car wash fleet in this market is older businesses along with some that are newer as well as some that, from outward appearances, have seen better days. The mix of wash facilities includes conveyors, in-bay automatics at gas sites, and self-serves with the total number of washes weighted slightly towards self-service locations (wands and combination sites).
According to our estimate, the trade area should have a total available market of about $5 million plus business from transient traffic.
Based on same store sales, the index of retail saturation would be 100 percent. Of course, this is what we would expect in a mature market. Areas tend to fill up with retail stores until the market can no longer support another new store.
Into this mix comes what is essentially the big-box store of the car wash industry and technology to offer a cheaper alternative to the products and services sold by most of the established players. There is plenty of historical evidence to support the argument that big-box stores, discounters, gasoline super sites, etc. meet the definition of disruption innovation.
Likewise, we can demonstrate how much disruption or devastation may be caused by applying the law of retail gravitation, which is well accepted.
The law of retail gravity basically says customers may be willing to travel longer distances to larger retail centers as long as the centers are big enough. For example, Reilly’s gravity model relates the share of customers that a retail outlet attracts as being inversely proportional to distance they must travel and directly related to store dimension (i.e., size, capacity).
This model also allows us to find a point of indifference between two locations so trade area of each location can be determined. The point of indifference is the point of equal probability that a consumer will patronize one store or another.
For example, if we apply this model against Wash-A and Wash-B, each tunnel measuring 3,000 square feet and separated by a distance of three miles, the point of indifference would be halfway in between or 1.5 miles.
However, if Wash-A were 15,000 square feet in size, the point of indifference would be 2.1 miles. Similarly, the market range or distance consumers are willing to travel to go to Wash-A is greater than Wash-B (i.e., 5 miles instead of 3 miles).
Huff also developed a gravity model to calculate the probability that a consumer will patronize a location. If we apply this model to our example, a customer would have a greater chance (83 percent) to visit Wash-A at the mid-point than Wash-B (17 percent), the smaller wash.
There are also gravity models that include variables such as appearance, product mix, price, quality, etc. that are aggregated into an “attractivity” measure to make the model suitable for turnover forecasting for different locations.
If we apply a simple formulation of this model against the Metro site and competition, we would expect probability of sales of 25 percent or $1.254 million ($5 million X 0.25).
Conversely, if we modeled the location with industry standard software (analog model or site checklist) we would expect a daily capture rate of 1.5 percent. If we apply this against available traffic and revenue benchmarks, expected sales would be $2.7 million.
Since $2.7 million represents 54 percent of the total available market, we could argue Metro’s huge wash would be devastating to established players in the market (3-mile radius).
Additionally, since we determined Metro would have a much larger trade area boundary than other stores, we could argue the new store would be disruptive to established players within this range. For example, at 5-miles and probability of sales of 25 percent, the new store would have anticipated sales of $3.8 million.
In the final analysis, the strength of a model depends on the quality of the historical evidence and on the reliability of the methods used to gather and interpret it. Historical analysis proceeds from certain conditions regarding proof.
Here, none of these conditions has been met sufficiently. Yes, there is historical evidence of innovative disruption in the U.S. car wash industry, and there are even larger car wash operations in existence overseas but no one has built or operated a huge wash like Metro’s in this country.
So, how quiet or constructive or disruptive or devastating this wash will be remains to be seen.
Bob Roman is president of RJR Enterprises – Consulting Services (www.carwashplan.com). You can reach Bob via e-mail at firstname.lastname@example.org.