Putting data and analytics front and center in the used car industry

It is anticipated that the institutional retail used-car market in the US and Europe will generate around $1.2 trillion in sales by 2023. This market is highly fragmented in both nations; in America, the top 20 used-car merchants hold less than 20 percent of the market, while in Europe, their share is less than 10 percent. This historical fragmentation has caused a slower adoption rate of innovative digital and analytics capabilities throughout the value chain as compared to other retail industries. Additionally, it has increased pressure on established players to innovate by creating chances for digital-first newcomers.

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Furthermore, used-car companies have been thrown into a new and difficult environment, having to deal with shifting consumer tastes, shifting supply-and-demand dynamics, and economic constraints as they develop from the complex market dynamics brought on by the epidemic. Due to these factors, it will be harder for participants in the used-car ecosystem to expand and there will be more pressure to keep profit margins high compared to the epidemic period.

Companies throughout the used-car value chain—B2B and B2C dealers, OEMs, financing and leasing companies—need to rethink and redesign business strategies to be more analytically astute if they hope to stay ahead of the competition. This includes protecting margins, improving performance, and tapping into customer demand.

Status of the market for old cars

Supply chain difficulties and geopolitical concerns, particularly the shortage of chips1.Over the past several years, the supply of both new and old cars has been impeded by electronic components—such as automotive semiconductors. Ondrej Burkacky, Johannes Deichmann, Michael Guggenheimer, and Philipp Pfingstag, “Will the supply–demand mismatch persist for automotive semiconductors?,” McKinsey, October 14, 2022. Due to the constrained supply and strong demand, new and used car prices have increased, resulting in larger profit margins. Demand is currently under pressure due to purchasing power depressions caused by inflationary tendencies in many locations, even while supply is recovering for certain models. Dealers are therefore losing part of their pricing power: the average cost of a used automobile in the US rose by 25% between 2020 and 2022, when it peaked, but it has subsequently decreased (Exhibit 1). Disruptions in fiscal policy in both markets have an additional impact on supply and demand: rising interest rates raise the cost of borrowing, which reduces auto finance companies’ profits and drives away some potential customers. This is particularly true for electric vehicles (EVs), as the promise of lower total costs of ownership that EVs have made to private retail customers is being jeopardized by rising energy prices, concerns about uncertain residual values, and changes to subsidies in some countries.

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Customers are continuing to make more of their car-purchasing decisions online in the interim. Over 95% of used-car searches begin online with a purchaser looking up vehicle information, and over 70% of buyers use third-party websites to compare pricing, according to McKinsey research.

As seen by the emergence of used-car marketplaces with value-added services, seamless omnichannel alternatives, and digital financing, digitally ahead enterprises have capitalized on these preferences. These businesses let clients examine and contrast prices while perusing an extensive inventory of pre-owned vehicles. These businesses then offer delivery across the country, with all back-end procedures being automated using algorithmic decision-making.

How analytics and data may add value

Many businesses in the automotive value chain still rely on internal experts and intuition for many crucial decision-making processes, failing to fully utilize data to optimize business processes. Dealers, OEMs, and car finance businesses may be able to boost customer demand, boost profitability, and enhance performance by implementing data-driven decision making.

In the last two decades, there has been a proliferation of real-time automotive retail. This implies that pricing ought to be determined as dynamically as airline tickets; long-term assortment decisions ought to be curated according to customer demand, as in consumer retail; and throughput management ought to be managed as dynamically as manufacturing.

Used car firms can take four steps to realize the advantage of analytics along the value chain. To assist keep ahead of market trends and consumer needs while preserving a strategic competitive edge, they can first merge external and internal data to build a consolidated bank of proprietary data. Secondly, they can create proprietary algorithms that mirror their unique company reality instead of using generic tools or solutions that are sold on the market. Thirdly, instead of restricting analytics-based decision making to certain applications, they may integrate it into decision-making at all organizational levels. Finally, they can centralize essential functions and free up frontline staff to concentrate on client demands by modifying their governance and operational structures. The use of these stages by various ecosystem participants and the outcomes that follow are described in the following section.

Dealers can transition to a more sustainable business model with the aid of digitalization; more particular, data-driven analytics can assist dealers in identifying the best sourcing, pricing, and car allocation methods to meet consumer preferences. Dealers have three options for maximizing value through the use of data and analytics.

Approach to sourcing and bidding. Dealers can maximize margins and optimize bidding prices by using data on current market inventory. Dealers can identify the desirableness of an automobile at several price points and calculate the best bidding price while cutting expenses internally by using analytically driven sourcing and bidding models that make use of real-time market data.

The present status of the auction process, which has an average margin of roughly 6%, is displayed in Exhibit 2. Using dynamic bidding tactics that take advantage of real-time used car market pricing data, an analysis of 15,000 auto sales in 2022 and 2023 revealed an added 2 percent margin-expansion opportunity. This translates into a $22 billion opportunity in the US and Europe combined.