Tuesday, June 23, 2015

Why Ford Is Brilliant – Carlisle Scrapbook
by David P. Carlisle

Thirteen years ago, in 2002, Ford announced Daily Parts Advantage (DPA) to the world. Back then, it seemed simply brilliant. Now, more than a decade later, it seems even more brilliant.
DPA was an integrated strategy of revised stock order cycle times (“daily”), revised terms and conditions, and revised network structure. Perhaps the cleverest aspect of DPA was looking at parts very differently than anyone ever had previously. Ford concluded that parts were of three different types : (1) parts that needed to be close to dealers for a 24-hour cycle time and 24-hour order response time (ORT), (2) small parts that could be easily shipped by a parcel carrier and beat a 24-hour ORT, and (3) large bulky parts, typically used in collision repairs, that required a sparser network and could easily flourish with a 48-hour ORT.


Seems obvious. But, it sparked a lot of debate … particularly concerning the large bulky parts. Did dealers need them in 24 hours, or was 48 hours sufficient? Would collision market share suffer with longer ORTs? Would insurance companies react to longer ORTs that could ripple over to longer rental contracts for the insured? After thirteen years, the answers are in:
  • Nah
  • Nah
  • Nope
Collision market research that we are currently conducting confirms all this, and more. Ford was right and kudos to their team of innovators: Don Johnson, Kent O’Hara, Frederiek Toney, Anu Goel, Joe Kory, John Sullivan, Helmut Nittman, Brad Wallis, and many many more. Cisco Codena headed up aftersales at the time and his leadership (call it courage) deserves mentioning.


The collision research we are doing spans a wide area – the primary objective is to refine our estimate of the impact driverless vehicles and collision avoidance technologies will have on collision parts sales. However, one work stream involves process mapping typical current-state collision repair facilities. So far, we’ve seen three things that are interesting:
  1. Price. Because the insurance industry largely controls what goes on in a collision repair shop, the advantage always goes to the low price option. This explains why non-genuine parts dominate repair orders for “unprotected” vehicles. In some states, laws protect some owners from repairs using non-genuine parts. However, these laws typically only cover only newer cars and not all specify “genuine.” States with significant “genuine parts” protective legislation cover only about 22% of the population. Outside that, it’s the wild, wild west.
  2. Price. Order lead-time differences between genuine and aftermarket (AM) parts are not much of a deciding factor when sourcing a collision part. For “competitive” parts, OE order lead-times are generally competitive with aftermarket parts. However, aftermarket return rates are ~30%; almost six times the return rates of OEs. Factoring in this return rate differential (in order to receive a correct part) the expected cycle time difference between an AM and OE nearly vanishes. Problems arise with “non-competitive,” slower moving, genuine parts that have erratic lead-times. Since they are “non-competitive,” this is not much of an issue . I suspect that there’s never been a successful aftermarket company that decided to invest in tooling simply because they thought that having inventory and quicker-than-OE lead-times would make a difference. No, the decision is always made on volume and price.
  3. Price. OEs’ aggressive collision parts “price matching” programs might not cut it. In a case study of one collision shop, the owner took advantage of every price matching program offered by OEM dealers. Most of the OEM parts were bought at either an extended 11% discount off the already reduced OE part list price or a 30% discount off the independent aftermarket part list price. At the end of the eight months, the shop analyzed the results: labor profits increased 3 points, while whole parts profits decreased 12 points due to the price matching programs. The part profit impact is a pure, measurable loss, while the labor gain isn’t even necessarily absorbed by the shop. Overall, shop profits dropped by 5%. So, while collision shops readily admit OE fit makes for timelier repairs, the benefits do not drop to the bottom line.
So, yes, Ford was brilliant. Carving out separate supply chain strategies for different classes of parts saved money … and worked well in an integrated
strategy that led to huge improvements in dealer and end-customer service.
(Most of these customer benefits were encapsulated in Ford’s move to a daily stock order.) Our research, so far, seems rock-solid in supporting what Ford did with their bulk parts centers – because the big issues in the collision market are price, price, price. Marginal advantages in lead-times have about the same lasting market impact that larger tail fins did on late 50’s sedans.


Bottom Line: That was the good news. The collision market is steadily becoming even more price driven, and Ford got ahead of the curve here. The bad news is that the insurance companies have been busy and have effectively commoditized the market during the past few decades. Price is more important than ever, and the squeeze will continue to tighten. Most of the genuine collision parts are used in the newer car parc, which is still continuing to recover from the 2008/9 recession. This makes for pretty nice year-over-year sales gains in this segment. However, when we finally achieve a steady state that resembles pre-recession conditions, we are bound to see that the OE segment of the collision market has shrunk. Big time. Then, when we lay on the anticipated market-melting impacts from collision avoidance technology and driverless vehicles … as my grandmother in-law would say, “oy veh!”

Tuesday, June 9, 2015

“Small Data” and Dynamic Scripting – Carlisle Research Scrapbook

“Big Data” is a big thing in aftersales service support – it will make our lives better in inventory management, sales forecasting, parts and service pricing, … and, ultimately, in better serving the needs of service customers. But, it’s going to take awhile.


Sorting through blizzards of data, big data is a valuable predictive tool. But, when the sightlines are fairly clear, we don’t have to put a lot of time and effort into fancy models and monster analyses. Effective service processes and simple surveys can capture the data directly from the customer - sample size of one - and be 100% accurate.


We might start with some recently available “small data.” We are about to release the syndicated 2015 Consumer Sentiment Survey – Dealer Customer Wave. Let’s take a peek.


#1. Some people will wait a long time, others won’t wait at all, yet others (more than a third) will wait an hour. Knowing the customer’s urgency is important information when prioritizing service, offering substitute transportation, and dispatching jobs to the service bays.


#2. Some people want to be greeted at their vehicle; others prefer to be greeted at a more traditional service advisor’s desk. Knowing this is important in designing dealer service lane processes – but again, “small data” shows us that even within a single dealership; there is no one size fits all.


#3. Not every service customer has the same preferences regarding how they are contacted for status updates. Less than 40% prefer “modern” methods – about the same as those who prefer phone calls. Again, different people are different.


These simple insights come from “Small Data” – a few thousand surveys of individual brand-service customers. The insights here show us that there isn’t one right answer that fits all – the data steers us into looking at customers within discrete segments, each segment having discrete preferences. We all know this is true.


So, why do we treat each service customer the same way when they schedule/arrive for a service appointment? It makes no sense.


Bottom Line: The technologists who are designing the tablets for Service Advisors should rely on some “small data” to accommodate service customer segment preferences. The service experience should be dynamically scripted to maximize accommodation of consumer preferences, which should then maximize consumer satisfaction.


To be perfectly clear, if I know Mary-Joe’s preferences are that: (1) she will wait up to 1.5 hours, (2) likes to be greeted at her car, and (3) wants texts to keep her up to date with her service, then I can…
  1. Prioritize my workload to make sure her car is finished inside 1.5 hours and not have to give her a loaner,
  2. Give her a priority customer card and shift her to a desk-less service lane, and
  3. Set up a texting schedule that keeps her apprised of progress.
We can accomplish results more readily than with big data by doing simple things like capturing customer profiles at first appointment, at service handoff, at scheduling, or at the owner portal. These can be done up front and occasionally refreshed. This removes the margin of error of big data, because we know we are right. And it’s a lot cheaper.


And, most importantly, we can deliver to Mary-Joe a flawless, repeatable service experience.


Wednesday, June 3, 2015

The Connected Vehicle First Needs To Be Connected – Carlisle Research “Scrapbook"

We do a lot of research about what goes on in the dealer service lane. Sometimes it is interesting to connect the dots between disparate sources of data and see if it better explains life, or what life promises. Here are three pictures from our scrapbook and some simple messages. What do you see in the scrapbook?
  1. According to dealers, not many repair orders are scheduled online.
  2. According to customers, many prefer to schedule online (more than those actually doing so, as shown above), while many others prefer to just call in and schedule their service.
  3. It seems that most customers would prefer to connect from their vehicle to schedule service.
Bottom Line: It seems that we have a problem with the tools we provide customers to schedule service today. Many are interested in doing it electronically, but less are actually doing so. Either dealers are slow to adopt or the current set of web-based service schedulers are flawed and not liked much by customers or dealers. Beyond this, customers want the convenience of scheduling from their vehicle, but we still have some work to do here.