Applying science to used car stocking

The best used car retailers are battling stock shortages by pairing their buying experience with intelligent data. High prices paid to acquire stock, coupled with increasing operating costs in addition to competition present big challenges.

This AM Live session focused on how retailers are intelligently predicting market trends and using the best digital tools to accelerate stock turn and boost used vehicle profits. Andy Whitehair, chief executive of Autofinity, chaired the session which saw Alex Jones, chief operations officer at used car group Carbase, Craig Petty, sales director at AM100 dealer group Hatfields and Neil Smith, chief executive at consultancy Motorvait, offer their insights.

Used car operators are grappling with stock shortages, navigating challenges such as over-age vehicles, high acquisition costs, and rising operational expenses amid fierce competition within the sector.

To combat these issues, retailers are adopting intelligent data solutions focused on predicting market trends, leveraging digital tools, and maximising profits in the used vehicle market.

This AM Live panel discussed the necessity of employing strategies to navigate such dynamic market conditions with the conversation underscoring the pivotal role of data in managing used car stock amid today’s market volatility.

Alex Jones, COO at Carbase, stressed the shift from patterns of predictable vehicle depreciation in the pre-COVID era to the current scenario where market dynamics are apt to change rapidly: “You look at the pre COVID world where everything was very repeatable so you could put a vehicle into stock and the depreciation curve was very familiar across the board with no wild differences between them but now you look at the different vehicles you buy in as you track the data through the life of that vehicle. You can see that that market has huge swings in it which just didn't exist previously.”

He said Carbase continuously surveyed the market and tried to work out what were going to be the key actionable future influences. “Of course, you can't make good decisions on all vehicles because you can't predict things like the big discounts that are going to come for some vehicles ahead of time but if you’re making better decisions on 99 out of 100 vehicles overall, you should get an incremental better result.”

Each panel member advocated for continuous data analysis to accurately understand trends and inform decisions although some has embraced it far earlier than others.

Former Imperial Cars operations director and Cazoo retail operations director Neil Smith said that for him it had always been a case of data-based decision-making and an understanding of the stock profile: what was moving quicker or selling quickest, days to turn value-added product penetration, finance penetration so that the process was optimised and allowed for incremental improvements across the whole process.

He said Imperial had developed all its own internal infrastructure moving away from proprietary DMS in order to have the ability to be dynamic, understand market influences and not just by understanding the market pricing. “It was about having that data insight and just being able to react to those market conditions,” he said.

Each speaker acknowledged the tension between ‘old-school’ gut instincts and data-driven approaches, noting a shift from emotional, experience-based decision-making to a more scientific approach. Practical strategies to support that approach included the development of dynamic, data-driven infrastructure optimising pricing, inventory turnover, and decision-making processes.

Smith, now chief executive at Motorvait said the key was to take the emotion out of buying: “At Imperial we had seven buyers who were office based. Everything was done with data. So you would overlay experience but predominantly due to the volume, everything was done on data - we had five, six different data streams coming in so it was data really that drove that business.”

Craig Petty, sales director at Hatfields, confessed that when he took my step up as sales director, he espoused the ‘old school’ approach. “You were either an Auto Trader subscriber or you weren’t. I was definitely ‘I do not subscribe’. But when you get into the science of it, stock turn and all the rest of it, I'm now an Auto Trader believer.  So now I look at retail rating. I look at the views. If it's 30 days old and only getting 15 views a week, you have to ask ‘why have you got it. You're not going to sell it’. Trade it, take the loss, don't wait the 90 days to call it over-age.”

He talked about a journey between what stock is known to have worked historically but said that had to be questioned often, and take  in national marketplace data, especially when considering how volatile the market is today. “How could one possibly know whether your success was based on your own experience - or that you just got really lucky.”

“Even so,” he said, “if you're going to take a true scientific approach, you still should have a team around you that is going to push back against your ideas.”

“I think there is a huge amount of just going back to basics and saying, ‘how are we making our decisions? What data are we basing it on?’ and ‘when was the last time you went and did a review of that piece? And how often do you review that data?’.

The significance of historical data in predicting trends and making informed decisions was stressed. External data sources, such as market conditions and performance ratings, were deemed crucial for understanding customer preferences allied with the need for dynamic pricing and stocking strategies that were supported by real-time data and technology to enhance accuracy.

The challenges of handling vast data from diverse sources was explored, with an emphasis on integrating systems to enable a comprehensive view. As Neil Smith pointed out, you have to be integrating external data to inform you as to what is the best car right now that you may not be ‘stalking’.

The role of data enrichment in advertising vehicles accurately and avoiding misrepresentation was also highlighted, along with a discussion on operational efficiency, continuous improvement, and the evolving dynamics of customer behaviour.

Alex Jones, COO at Carbase, said the two challenges his business faced in advertising was firstly, compliance where advertising the correct derivative of the engine code, the emissions, etc is crucial: “Our finance partners will tell us straightaway that if we're signing someone up into a vehicle and it isn't that specific vehicle, we've got a huge liability.”

“The second piece of that is around how customers perceive what is the same vehicle versus what we would perceive as we are able to go into lots of granular detail although retail customers really don't care to the same extent.”

“Even so, you really have to make sure you've got a dedicated amount of time and so internally, we've got people dedicated to that to make sure that what we bought is what we think we've bought when it’s actually landed, and that we are then advertising it correctly. So we have robust checks in place to make sure that you're looking after all those different anomalies.”

Craig Petty, sales director at Hatfields agreed and cited the emergence of the big online disruptors: “They just didn't have those processes in place. So, dare I say, I think we may have bought quite a few cars as retail customers from Cazoo because they failed to understand what this limited edition F type was and what was special about it. They just saw a car, they saw its mileage and saw its age whereas we knew that the car may have £3000 worth of optional extras, and we could tell the story to the customer.”

The discussion also turned to developing the perfect DMS system. Here, Petty said it was all about partnering with good systems and essentially about partnering with people that actually know what they're doing so when it does go wrong – which it invariably will – people can react quickly.

Neil Smith said from experience that the biggest problem was when a propriety DMS doesn't open up every element. “However, you can certainly build your own ecosystem now with the help of some very competitively priced products and there will always be some manual transposition when you're pushing stuff into the DMS potentially.”

Carbase’s Alex Jones said the challenge posed by siloed data and multiple systems remains huge. “It’s going to be a very personal journey for all of us because, of course, we're going to have a huge amount of data in silos but I think the way that we can deal with it internally is to build in a certain amount of middleware to actually bring data back together.”

“We've got a certain element of our system that's always proprietary as everyone else is doing but we're always trying to just carve out a little niche to be able to at least think that we've got an advantage in the data that's going in.”

“There are some brilliant, brilliant partners in the marketplace with whom to have conversation and work out where you don't know what you don't know, where is your blind spot. After all, how can you possibly know what you're missing out on today until you've actually been through all the different areas.”

Panel chair Autofinity’s Andy Whitehair said that his business’s platforms power data accuracy across its customers’ businesses and is easily able to integrate with other industry systems to create a single view of the truth in real time. “When we go into a customer, some people adopt it really well. Some people don't. And a lot of that tends down to be the organisational structure and the organisation of the dealership and how they change the organisation to adapt to the extra data that comes through.”