Tag: network

Network Effects in Dealer Systems

Last month, I wrote that the recent acquisitions of several Digital Retail vendors were driven by the need to accumulate dealer data for predictive analytics.  Today, I’d like to discuss another of Professor Rogers’ five themes, “network effects,” and how it applies to F&I software.

We’ll consider a hypothetical company that supplies admin software for F&I products, and also sells one or more dealer systems.  Having two distinct, but related, customer groups will allow us to explore “cross-side” network effects.

If the value of being in the network increases with the size of the network, as it often does, then there is a positive network effect.  Social networks are the model case.  The more people who are on Facebook, the more valuable Facebook is to its users (and its advertisers).

This is the textbook definition of “network effects,” but it’s only one part of what Iansiti and Lakhani call Strategic Network Analysis.  Below is a handy outline.  This article will walk through the outline using our hypothetical company – and some real ones from my experience.

Network Strategy Checklist

  1. Network effects (good) – Value grows as the square of the node count … maybe.
  2. Learning effects (good) – There is valuable data to be gleaned from the network.
  3. Clustering (bad) – You can be picked apart, one cluster at a time.
  4. Synergies (good) – Your business includes another network that talks to this one.
  5. Multihoming (bad) – Easy for customers to use multiple networks.
  6. Disintermediation (bad) – Easy for customers to go around your network.
  7. Bridging (good) – Opportunity to connect your network to others.

By the end of this article, you will understand how networking relates to the data concept from the earlier article, and how to apply it to your own software.

Speaking of vocabulary, let’s agree that “network” simply means all of the customers connected to your software, even if they aren’t connected to each other.  It will be our job to invent positive network effects for the company.

The early thinking about networks dealt with actual communication networks, where adding the nth telephone made possible n-1 new connections.  This gave rise to Metcalfe’s Law, which says that the value of a network increases with the square of its size.

Working Your Network

If you are supporting a “peer-to-peer” activity among your dealers, like Bruce Thompson’s auction platform, Car Offer, then you have Metcalfe’s Law working for you.  By the way, Bruce’s company was among those in the aforementioned wave of acquisitions.

If you are supporting a dealer-to-dealer activity, like Bruce Thompson’s auction platform, then you have Metcalfe’s Law working for you. 

Research has shown that naturally occurring networks, like Facebook, do not exhibit Metcalfe-style connectivity.  They exhibit clustering, and have far fewer than O(n2) links.  Clustering is bad – point #3, above – because it makes your network vulnerable to poaching.

Even if you don’t have network effects, per se, you can still organize learning effects using your dealers’ data.  Let’s say you have a reporting system that shows how well each dealer did on PVR last month.  Add some analytics, and you can show that although he has improved by 10%, he is still in the bottom quintile among medium-sized Ford dealers.

That’s descriptive analytics.  To make it prescriptive, let’s say our hypothetical company also operates a menu system.  Now, we can use historical data to predict which F&I product is most likely to be sold on the next deal.  The same technique can be applied to Digital Retail, desking, choosing a vehicle, etc.

Note that we have data from our reporting system doing analytics for our menu system – and pooled across dealers.  Any data we can accumulate is fair game.  This is why I recently advised one of my clients to “start hoarding now” for a prospective AI project.

Cross-Side Network Effects

So far, we’ve covered points 1-3 for our hypothetical company’s dealer network.  I’ll leave their provider network as an exercise for the reader, and move on to point #4.  This is where your business serves two groups, and its value to group A increases with the size of group B.

I like to say “cross-side” because that clearly describes the structure.  Iansiti and Lakhani say “synergy.”  Another popular term is “marketplace,” as in Amazon Marketplace, which I don’t like as much because of its end-consumer connotation.

It’s hard to bootstrap a network, and it’s twice as hard to bootstrap a marketplace. 

Is there an opportunity for cross-side effects between dealers and F&I providers?  Obviously ­– this is the business model I devised for Provider Exchange Network ten years ago.  Back then, it was voodoo magic, but a challenger today would face serious problems.

It’s hard to bootstrap a network, and it’s twice as hard to bootstrap a marketplace.  In the early days at PEN, we had exactly one (1) dealer system, which did not attract a lot of providers.  This, in turn, did not attract a lot of dealer systems.  Kudos to Ron Greer for breaking the deadlock.

Worse, while PEN is a “pure play” marketplace, our hypothetical software company sells its own menu system.  This will deter competing menu systems from coming onboard.  I’ll take up another of Professor Rogers’ themes, “working with your competitors,” in a later post.

Finally, network effects are a “winner takes all” proposition.  Once everybody is on Facebook, it’s hard to enroll them into another network.  That’s not to say it can’t be done.  Brian Reed’s F&I Express successfully created a dealer-to-provider marketplace that parallels PEN.

This brings us to point #5, “multihoming.”  Most F&I product providers are willing to be on multiple networks.  When I was doing this job for Safe-Guard, we ran most of our traffic through PEN, but also F&I Express and Stone Eagle, plus a few standalone menu systems.

The cost of multihoming is felt more by the dealer systems, which are often small and struggle to develop multiple connections.  On the other hand, Maxim and Vision insisted on connecting to us directly.  This is point #6, “disintermediation.”

New Kinds of Traffic

Fortunately for our hypothetical company, Digital Retail is driving the need for new kinds of traffic between providers and dealer systems.  This means new transaction types or, technically, new JSON payloads.  Transmitting digital media is one I’ve encountered a few times.  Custom (AI-based) pricing is another.

Digital Retail is driving the need for new kinds of traffic between providers and dealer systems. 

Controlling software at both ends of the pipeline would allow them to lead the market with the new transaction types.  Key skills are the ability to manage a network and develop a compelling interface (yes, an API can be “compelling”).

As before, note that the same concepts apply for a dealer-to-lender network, like Route One.  There is even a provider-to-lender network right here in Dallas.  Two, if you count Express Recoveries.

So, now you have examples of Strategic Network Analysis from real-world F&I software.  This is one of the methods the Virag Consulting website means when it says “formal methods” to place your software in its strategic context.  

If you’ve read this far, you are probably a practitioner yourself, and I hope this contributes to your success.  It should also advance the ongoing discussion of data and analytics in dealer systems.