Deconstructing the Dealership

Remember when dealerships had body shops?  Two out of five still do, but they comprise less than 20% of this $35 billion market.  Somewhere along the line, it became clear that collision repair was better done by specialist facilities, unconnected to the dealer.  Scale, capital investment, brand diversification, and (lack of) synergy were factors.

We may now wonder if parts and service belong in the dealership, thanks in some measure to the rise of automotive eCommerce.  Jim Ziegler warns that Valvoline Express is beating dealers in the shop and online.  Ward’s makes the same point, with emphasis on Google search optimization.  In the same vein, Amazon has come up with a way to sell tires online.

There can be much synergy between the two ends of the business, which can be leveraged to manage and sustain customer relationships – Vincent Romans

My approach is to “follow the money” and, sure enough, here is Carl Icahn buying up repair facilities.  Icahn Automotive Group is a classic consolidation play, with 2,000 locations including Precision Auto Care, Pep Boys, Just Brakes, AutoPlus, AAMCO, Cottman, and CAP.  Icahn is vertically integrated through Federal-Mogul Motorparts, which includes ANCO wipers and Champion spark plugs.

So, will eCommerce pick off the dealer’s profit centers one by one?  In this example, we see the convergence of powerful megatrends.  The traditional dealer model is challenged by two new ones, which I like to call the Best Buy model and Amazon model.

History tells us that the Amazon model will prevail in the end, but it doesn’t tell us what the transformation will look like, or how dealers should prepare.  To learn that, we employ an old tool from Business Process Reengineering, and we discover a surprising result.  Here is a breakdown of the traditional dealer operations:

  • New Sales
  • Used Sales
  • Finance
  • Insurance
  • Parts
  • Service
  • Collision Repair

We can consider each operation in terms of how it will respond to the new challenges – and whether it belongs with the others.  We have to start somewhere, so let us define new vehicle sales as the nucleus of the dealership.  The test drive is the process most resistant to eCommerce although, as I wrote last week, there are ways around it.

Used vehicle sales will certainly not stay in the dealership.  It is vulnerable to both consolidators and eCommerce.  This is a shame because taking vehicles in trade used to be a great synergy.  The new specialists are true “auto traders,” using high-volume analytics to trade both ways with the public and the auction.

Coming back to fixed operations, there is a clear synergy.  According to Cox research, customers who are properly introduced to the service department are two and a half times more likely to come back for service.  But there are other ways to exploit this synergy, like the “zero deductible at our dealership” service contract – and the Amazon tire store shows that parts can be separated from service.

Lithia Motors has 186 locations including, by my count, fourteen collision centers.  There is not much synergy between body shops and vehicle sales, or even service, but they run fine as standalone operations connected to the brand.  Likewise, given a branded service contract, I can see Lithia’s mass market franchises supporting shared service facilities.

F&I is the subject of fierce debate, too much to cover here.  Can it be merged into the sales function? Can protection products be sold successfully online?  What is the future of indirect finance?  Do “F” and “I” even belong together anymore?  For our purpose today, we need only observe that while F&I has a workflow linkage to sales, it does not need a physical one.  F&I could just as easily skype in from a call center.

As Carl Icahn would tell you, these are distinct businesses without much synergy, if synergy is defined as “positive return from shared personnel and facilities.”  Dealers organized along these lines will, indeed, be picked apart by eCommerce and consolidation.

On the other hand, if synergy means “positive return from shared customer contact and branding,” then these businesses will hang together.  Dealers organized along this principle will have diverse and independent operations, making them resilient to disruption.  They will have “optionality,” to use Nassim Taleb’s term.

You may be taken aback by this assault on the venerable “rooftop,” and I admitted earlier to being surprised.  However, decoupling and diversification (and divestiture) are textbook responses to an industry in flux.  Just look at how many departments are no longer in department stores.

Menu Selling on an iPhone

Followers of my Twitter feed know that I have lately been looking at mobile apps, to see if anyone can present protection products on an iPhone.  I wrote about this three years ago and, according to my informal survey, the field is still open.

I don’t think anybody has a good way to present a menu on a consumer web site, much less an iPhone.

Not only is the iPhone a restrictive form factor but we must assume that the customer, not an F&I person, is operating it.  We would like to apply our Best Practices for Menu Selling, but the app must be able to apply them on its own.

For example, if we want to retain the package concept with the carefully chosen payment intervals, we can use an accordion control.  I proposed this for a client once, in an F&I context, but it doesn’t make sense for consumer use.

No, the best way to “present all the products, all the time,” is simply to make one long column with everything in it.  The iPhone presents challenges, but there are offsetting advantages.  We can show fifteen products in one column, and the customer has his leisure to scroll through them.

I prefer scrolling to swiping for a few reasons.  In the prototype shown here, we have the obligatory vehicle photo.  After the first scroll, that’s gone and the screen space is devoted to products.

The prototype shows monthly prices for the vehicle and the products.  This assumes the finance process is settled, and the app can choose products matching the finance term.  Touching any of the products will open up a full page with details, coverage choices, and a “sales tool” as in the earlier article.

I recommend using analytics to determine the sequence of products in the column, and even to A/B test the format of the product blurbs.  I have in mind a few different formats:

  • Text with graphic and price, as shown here.
  • No price ‘til you open it.
  • Lead with the sales tool.

I discuss analytics here, but I am not a fan of the full “ownership survey.”  Of the eight standard questions, maybe you can sneak in one or two elsewhere in the process.  Apart from that, we’re counting on data points found in the deal itself.

I also think “less is more” when confronting the customer with choices.  As you can see in the mockup above, there must be no complicated grades of coverage (or deductible).  If you’re configuring the app for a specific dealer, you may want to filter some options out of the dealer’s product table.

Depending on who’s managing the app, the products themselves may be rethought.  If you want to offer chemical, dent, key, and windshield as a combo product, then that’s a single choice.  Alternatively – since we have unlimited  column space – you can offer each one individually.  What you do not want is a product having fifteen different combinations.

Coming back to my informal survey of mobile apps, and the workflow given here, I believe there are already good examples of vehicle selection, credit application, trade valuation, and payment calculator.  Menu selling has been the only missing link, until now.

Pay Plan Math

Feeling quantitative again today, so … suppose you have an F&I Director, or a menu trainer, or somebody, and their goal is to move product index from 1.0 to 1.2 over some time period.  To keep the numbers simple, let’s say the variable comp component is $10K.

One way to do this is to say that 1.2 pays $10K and the current performance, 1.0, pays zero.  This makes sense, right?  Why pay for no improvement?  This only works, however, if you place a cap on it.  As the salesman, I could come back and say, fine, if the two points of product index are worth $10K to you, what happens if I hit 1.4?  Are you willing to pay me $20K for that?

Most people resist the idea of capped pay plans.  Mathematically, you are making a linear relationship between compensation and performance, and you should be willing to honor that relationship up and down the line.  The problem here is that the line is too steep.

So, let’s try a shallower slope.  Once again, 1.2 pays $10K, but this time the zero point is 0.0.  That means the current performance, 1.0, still pays $8,333 and the salesperson doesn’t go hungry unless the index actually falls all the way to 0.0.  Obviously, this plan is too weak.

The weak plan may be desirable if your sales force is really counting on some of that money, and the “variable” is not as variable as advertised.  It also protects the company on the up side.  In this example, I can achieve a 1.5 index and it only earns me an extra $2,500 (on top of the $10K).

Now we have examples of two pay plans, one too strong and one too weak, as in the story of The Three Bears. The key to making the pay plan just right is to observe that the zero point is arbitrary. In the papa bear case, too strong, we set the zero point at 1.0, the current performance.  In the mama bear case, we set it at an index of 0.0.

Recall that a line on a graph is determined by two points.  One point is fixed by the target and the bonus (1.2, $10K) the other point is set by where you place the zero (z, $0) and between them they determine the slope:

If you’re making this chart right now remember to place the independent variable, product index, on the x-axis.  All that remains is to compute the y-intercept of your line.  The point where the bonus is zero, z, is the x-intercept.  A little algebra gives the y-intercept as:

Now we are ready to start plotting.  This time, let’s split the difference and set the zero point at 0.5.  This seems to be just about right.  Comp for standing still, 1.0, is $7,143; for 1.5, only $14,286, and our guy doesn’t starve until 0.5.

If you have this set up in a spreadsheet, you can tweak the zero point until you have the desired amount of exposure for both parties.  Below is the chart for my “goldilocks” line, with the mama bear case for comparison.

We always give careful thought to the target, but sometimes neglect the slope of the payoff line.  Next week, we will talk about two-dimensional pay plans, combining product index and PVR.

In the Amazon Wilderness

I concluded Car Dealer Megatrends with the clear and present dominance of consolidated groups, which I like to call the Best Buy phase.  Today, I will indulge in a little futurism, and explore the Amazon phase.  In the Amazon phase, it will be possible to buy a new car enitrely online and have it delivered.

By 2025, experts estimate 30-40% of car sales will be online.  The high end of that range is from Mark O’Neil.  Used cars are easier to sell online, witness Carvana, Vroom, and Shift, but new cars will be there too.  An estimated 25%, and that’s only seven years away.

The industry is rapidly solving problems like pricing and trade valuation.  The only challenge people still talk about is the test drive.  Carvana solves this with its seven day return policy, and Shift will bring the car to you for a test drive.

 “The current dealer model is not a dying breed,” Benstock said. “It’s dead. It’s absolutely dead.”

I will order a new BMW sight unseen, because I know the product and I trust the manufacturer.  Their online configurator is awesome, and I really would press the “build and ship as shown” button, although the process isn’t quite there yet.  We’ll come back to BMW later, but for now let’s assume a test drive is required.

The tension between Best Buy and Amazon centers on a practice known as “showrooming.”  This is where you sample the product at Best Buy, interrogate the Best Buy sales associate, and then turn around and order the product from Amazon.  Amazon even makes a clever app you can use to scan product codes while you’re in Best Buy.

As auto retail moves into its Amazon phase, I can imagine the same challenge for dealers.  You have invested in a monument to your manufacturer’s brand image, where customers can sample the product and then go order it online.

I had been pondering the showrooming challenge for a while when I ran across this piece in the Wall Street Journal.  Nordstrom is opening stores with no stock, where shoppers can try on clothes and accessories, and then have them delivered.

It will contain eight dressing rooms, where shoppers can try on clothes and accessories, though the store won’t stock them.

The Nordstrom story reminded me of the old “catalog showrooms” operated by mail order retailers like E.L. Rice and Service Merchandise.  Ironically, this was the last gasp of mail order, put out of business by brick and mortar retailers – including, ultimately, Best Buy.

All of this goes to show that, in the Amazon phase, showrooming and fulfillment can be disconnected.  Where the customer goes, to test drive and learn about the vehicle, does not have to be the dealership or even affiliated with the dealership.  This opens up a world of new possibilities.

I can think of several applications for standalone test drive centers.  For instance, suppose a manufacturer wanted to enforce its ideas about how to present its vehicles, and also – since this is the Amazon phase – protect its own position online.

Were it not for U.S. franchise laws, manufacturers would run their own retail outlets.  In Europe, they have company stores, where ideas about brand image, sales training, and product positioning do not depend on a network of autonomous dealers.

An OEM test drive center would bypass the dealer network (or complement it, if you prefer).  It would be staffed by salaried, factory-trained product experts with no other objective than to educate customers in the finer points of their company’s vehicles.

There would be minimal inventory, attractive video displays, simulators, and samples of paint and fabric.  No transactions would take place, but there would be plenty of Wi-Fi bandwidth and gourmet coffee for the online shoppers.

As I said, this is just one scenario.  The new techniques of digital retail will create untold opportunity for dealers willing to adapt.  Our exploration of the Amazon phase has just begun.

Seasonal Adjustment Factors

I felt like doing something quantitative, so this week we look at seasonal adjustment factors.  Everybody always talks about SAAR, and you probably know that it stands for “seasonally adjusted annual rate,” but what does this really mean?

Well, suppose it’s March 2017, and you are wondering what total sales will be for the year.  The industry sold 1.55 million vehicles that month so, if you multiply by twelve months, you might estimate 18.6 million for the year.

You would be wrong, though, because March is always a strong month.  Here are the estimates produced by the simple “times twelve” method, relative to the actual total for 2017, which was 17.2 million.

Using data from Fred for the five years 2013 through 2017, and converting everything to a percentage, you can see how March always overestimates the year’s results.  Each year’s dots are a different color, though it doesn’t really matter which is which.

Some months are highly variable, like September.  Not a good gauge of anything.  Remember to distrust any SAAR figures published in September.  April, oddly, is a tight group and bang on the annual rate.  April 2018 sales were 1.4 million, so a good guess for the year is 16.8 million.

Taking an average across the five years, we find that March, May, August, and December each overshoot the annual rate by roughly 10%.  Finally, we convert these percentages into monthly adjustment factors.

Instead of multiplying last month’s sales by 12, multiply by the monthly factor to predict the year’s total.  Of course, we have more data than just a single month.  We can also look at cumulative sales since January.  For example, do a quarter of the year’s sales occur in the first quarter?

No.  It takes a while to make up for the weak January and February, and then the actual historical cumulative pace slowly comes into alignment with the idealized linear cumulative pace.  I made that chart, too, but it’s not pretty.  That’s enough quantitative stuff for this week.

The Automotive eCommerce Ecosystem

Around the turn of the century, I was helping RouteOne to build their now-ubiquitous credit system.  Then, I moved on to aggregation models for the “I” side of F&I.  It was a lot of work.

We had to develop scores of unique interfaces for lenders and product providers.  We had to develop deal calculation engines, and then reverse engineer each DMS so our payments would match.  There were no automated sources for finance or product rates.  We had to walk ten miles in the snow …

Today’s eCommerce startups have it easy.  All of the key tasks are supported by readily available services, leaving the entrepreneur to focus on user experience and dealer support.

When I started writing about this space, the key challenges were price negotiation and trade valuation (and the test drive, but I’ll cover that in a later piece).  Today, you have reliable online trade valuation from Kelley, Trade Pending, and others.  Price negotiation can be handled through chat or one-price, generally on used vehicles.

You can have payment calculations, including incentives, from MarketScan, provider networks from PEN or F&I Express, and finance networks from RouteOne or Dealertrack.  Everything in this paragraph is an API, not to mention passing data from your eCommerce platform into the corresponding dealer system. Finally, even the old faithful DMS now exposes a variety of databases, like inventory.

A few months ago, I described the role of venture capital in driving process change.  I think this eCommerce ecosystem is equally important.  Entrepreneurs can enter the space at a very low cost, relative to ten years ago, and meet most of their requirements through interfaces.

Speculation on Fractal Programming Language

We flew east out of Panama City, and I looked down on the faceted green hills of the Cordillera de San Blas, perhaps for the last time.  In the sky were statistically similar puffs of white cumulus cloud.  Naturally, I was thinking of fractals.

I had spent the past few days coding technical analysis indicators in Python, which reminded me of coding same in C#.  This, in turn, reminded me that although the TA community talks a lot about geometric repetition, we have yet to invent a single fractal indicator, much less a trading strategy.

I write my trading strategies in C# on the MultiCharts platform.  Its procedures for time series data look a lot like the vector-oriented syntax of Python.  Here is how to do Bollinger bands in each:

  • StandardDeviationCustom(length, devs)
  • df[price].rolling(length).std() * devs

I have to admit not having much intuition about vector operations.  Matrices and summations just look like for loops to me – clearly an obstacle to the proper appreciation of Python.  I have worked with SAS and SYSTAT, though, so Python at the command prompt seems natural.

What I noticed with the Python exercise is that the classic TA indicators were designed with an iterative mindset, reflecting the programming languages of the day – Sapir’s theory, again – and so I imagine that the reason we have no fractal indicators is that our language can’t express them.

Here are some basic things I would expect from a fractal-oriented programming language:

  • Create a dataset from a generator function
  • Derive fractal metrics, like the Hausdorff dimension
  • Compare two datasets for statistical similarity
  • Compare a dataset to subsets of itself

Admittedly, I have only a cursory notion of how this would work.  That’s why this piece has “speculation” in the title.  Meanwhile, I will continue plugging away in C# and Python.