Point de vue
Predicting needs to improve profits
How Advanced Analytics can Help Automakers and Car Dealers Better Prepare for Success
Automakers spend billions of dollars on incentives every year in an attempt to sell off their inventory due to an offer greater than the demand. But optimized demand planning, by way of advanced analytics to optimize car’s distribution, could curb such excessive spending and increase customer satisfaction and margins for dealers, distributors and automakers.
The automotive market has evolved over the past decade, similarly customer needs and desires have evolved. However, the economic model of automakers and car dealers remains the same and still relies on a key principle to enable success: fulfilling most of OEM plants capacities. The consequences of this over-production are high level of inventories and the need to implement incentives in order to purge inventories. A question here is also whether OEMs and dealers are not mainly following two principles: Profitable volume. Selling a well-equipped car is sometimes as profitable as 10 others?
As described in the press release wrote in May 2020 by Jochen Funk – “IMPACT OF CORONAVIRUS TO AUTOMOTIVE RETAIL IN EUROPE”, the Covid-19 outbreak has plunged OEMs into a thoroughly new situation, with unprecedented challenges to be tackled by the automotive sector. Whilst China has recovered from the outbreak, one third of the world is in quarantine, with strong consequences on sales. In France, the car market dropped by 72.2% in March, while car manufacturers predict a 20% decrease in the French market in 2020 (source: CCFA).
Although it is unsure to predict the end of the Covid-19 outbreak, some of the impacts on sales and after-sales that OEMs will face in the wake of the pandemic can be anticipated as of now. Three factors will shape the business of tomorrow for both sales and after-sales part. The purchasing power per household will be impacted by the pandemic: jobs are at risk and companies must deal with major losses, possibly leading to an economic downturn. Furthermore, consumers’ behaviors will evolve, after weeks of upheaval. Social distancing and general precautions may as well lead to a shift from public transportation to individual transportation in urban areas and a potential revival of car ownership. Finally, OEMs are bracing themselves for a decrease in production volumes, due to supply chain perturbations, thus, forcing automakers even more to find additional pools of revenues.
Advanced analytics can help automakers and car dealers better predict the needs of customers and improve forecast in order to reduce risks of over or under production. Consequently, this will increase the availability of cars, optimize inventory management, and reduce the number of incentives required to sell premium and generic cars. The effectiveness of advanced analytics has been proven in other industries such as consumer goods and services (CG&S).
Customer needs are becoming more complex and harder to forecast
The automotive industry is under pressure to understand the exact needs of customers, resulting in more complex forecasts. It represents a key operations challenge, according to 66 percent of operations executives.i The causes for this shift in behavior are more diversified offers, new consumer trends, and government’s regulations:
More diversified offers
The development of new technologies coupled with rising concerns about environmental issues has led to a proliferation of car variants, e.g. different propulsion systems, assisted/autonomous cars, electric vehicles, etc. The influx of variants has exacerbated demand for customized cars that can meet the exact needs of all customers. In fact, the number of new car models has increased by more than 30 percent in average, over the last 15 years.ii In this context, forecasting the demand becomes a key element for OEMs and dealers in order to offer the right product mix to customers.
Automotive products are extremely complex due to the multiple possibilities of combinations of all the options, paintings and equipment’s. For instance, for one basic range model (Berline C-Segment) with 7 levels, 12 possibilities options of engine/gearbox, 8 possibilities of paints and 18 possibilities of options, we end up with a vehicle with more than 4 million possibilities of combinations! This figure is growing exponentially as we add more features. Therefore, forecasting the right combination of vehicle features is very complex for OEMs and have direct impact on productions. Forecasting and distributing the vehicles with the right options into the network is a key element in order to increase sales, customers satisfaction, and decrease time to market.
New consumer trends
Customer perceptions are changing, and more people are starting to view cars as more of a service and a mobility solution rather than a status symbol. Millennials prize convenience iii, which has resulted in the development of services such as car sharing, leasing, pay-as-you-drive, etc iv. To remain relevant in the automotive ecosystem, OEMs must adapt their offerings to this new type of demand and diversify their revenue streams by providing new automotive technology (connected vehicles, autonomous driving, etc.), services, and implement strategies to target fleet owners (such as new mobility platforms. Therefore, OEMs and dealers need to forecast the new demand and to understand new usages in order to offer vehicles and services responding to those new customers trends. New mobility is also increasing the part of cars sold to “fleet owners”, whom are already key customers for OEMs. Therefore, we are expecting a shift of the current business model and revenues repartition between now and 2035 with a decrease of the sales of new vehicles and an increase of revenues through Mobility as a Service.
To remain competitive, OEMs and dealers will need to anticipate and forecast the deep evolution of the demand.
New consumer trends are also expected to increase the likelihood of customers switching dealers, brands and even the way they use cars. Quick and easy access to the internet, plus the spread of offer comparison websites, has made switching easier than ever. Although OEMs websites are involved in more than 90% of customer journeys, only 60% people actually think that the website has met their expectations (source: 2018 Deloitte Global Automotive Consumer Study).
Used car market
The prices of new cars are increasing due to new technologies, more complex configurations and higher levels of customization. Customers are more willing to buy second-hand cars as they are now more affordable. In France for example, the used car market is 2.5 times bigger than the new cars market.
Used Car market is currently dominated by digital/new/independent actors. The distribution of Used Cars by OEMs is limited: many Used Cars at dealer level are generated by Trade-ins, RAC/Leasing Buy backs, Test Drive and courtesy cars and so OEMs focus then at redistributing their buy backs and the company cars.
That said, Used Cars sourcing has become a strategic element for OEMs and dealers in order to compete with those digital marketplaces.
OEMs and dealers need to capture the trends of the market and be able to forecast accurately the demand (type of vehicles, options, equipment, etc.) in order to, as for new vehicles, distribute the right vehicles to the right dealers or online.
New regulations have been put in place at European and French level and have a direct impact on production and demand on the automotive market. The CAFE regulation at the European level regulates compliance with an averaged CO2 emission limit (95 g / km in 2021), moreover vehicles with high CO2 emissions can no longer circulate in certain urban areas. In addition, in most markets urban limitations are depending on NOX not CO2 leading to prohibition of older Diesel engines although they have better C02 than petrol.
The LOM regulation requires all agglomerations with more than 100,000 inhabitants to study the establishment of “Low Emission Zone”.
These new regulations being implemented have major impacts on two aspects:
- Production: Production rationalization and investment to accelerate research and production of alternative powertrains and low-emission vehicles, disposal of stocks of high-emission vehicles, potential high fines
- Demand: Increase in demand for low-emission vehicles depending on regions and applied investments (vehicle charging infrastructure, critical area, public transportation services, etc.)
OEMs and dealers need to anticipate new regulations in order to avoid high level of inventories and the use of high customers incentives.
Automakers are constrained by the current industrial model
While customers’ preferences are shifting, the automotive industrial model remains unchanged. In fact, the current model still faces two major challenges:
Full capacity production
Automotive manufacturers are producing cars with a high utilization rate (60-70% up to 100%) until the end of the lifecycle of a model, as part of an effort to maintain employment and amortize important fixed costs. Because of this and notably the necessity to respect the quotas around Engine, segment, body shape, production volume does not always match market demand, which has an impact on dealers: they order potentially unappealing cars and then strive to sell them.
Despite the implementation of measures to improve productivity while reducing lead time (just-in-time, Kanban, etc.) and facilitate collaboration among business partners, OEMs still possess poor capacity change management and are facing constraints due to frozen horizons in production. See above. Commitments on annual production volume must be made and new methods for dealing with demand volatility are a necessity. v
Deep discounts ‘consume’ OEM and dealer margins
Due to the above challenges, OEMs and dealers are unable to sell large volumes of unwanted cars every year. These cars remain in inventory, waiting desperately for a buyer, until specific actions are taken to sell them off. However, such actions can also have a negative impact.
The introduction of deep incentives, in addition to more stringent compliance regulations and growing R&D investments, has impacted OEM and dealers’ margins yearly since 2013. Nowadays we estimated tactical incentives represent 75% of the variable margin (see graph below). Incentives are typically overspent and allocated in a suboptimal manner, not just by automakers but also dealers. As a result, dealers may be required to dip into their own pockets at some point, which will in turn negatively affect their margins; this even if over the last years, New Car dealer profitability has been relatively constant, notably thanks to the SUV boom.
Manufacturer-to-dealer and Dealer-to-customer incentives
These incentives are determined by the controversial stair-step formula (corresponds to bonuses for achieving sales targets), regional inventory and dealer inventory.vi Dealer holdbacks are often 2 to 3 percent of the Manufacturer Suggested Retail Price (MSRP) (Edmunds). Automakers frequently announce manufacturer-to-dealer incentives at the beginning of the month but can change their program as desired. This understandably has a big impact on dealer sales.
At their level, dealers leverage those incentives to apply sometimes significant commercial discounts to their customers in order to sell their inventories and ensure continuous increase sales and achieve objectives fixed by the OEMs.
Another method for getting rid of unwanted or unappealing cars is to sell them as zero-kilometer cars. These are new cars with low mileage that are registered by OEMs or dealers for sale as old cars to final customers at used car prices, i.e. with large rebates of 20 to 30 percent of MSRP.
Zero-kilometer cars help dealers meet their sales targets. However, due to the aggressive discounts on offer, customers who are initially interested in purchasing a new car are now more willing to buy a zero-kilometer car. This can negatively impact new car sales.
The limits of incentives and other countermeasures are showing. OEMs and dealers are struggling to handle the complexity of customer demand and the industrial model. While almost all automakers have invested in technology solutions like car configurators, and many have reviewed their supply chain and adopted a build-to-order approach to introduce some flexibility in their planning model, most still use outdated demand planning processes and remain unable to “sense” fast-changing demand trends.
Thankfully, new technologies enable more accurate forecasting to better match the volatile preferences of customers and are already used in other industries. New technologies and advanced analytics are not used enough in the automotive market. Better planning will create three competitive advantages for automakers and dealers:
- Increased customer satisfaction by reducing time-to-market.
- Increased customer profits on the sales of new cars by reducing the number of rebates offered to customers.
- Decreased the level of inventories thanks to a better alignment between production and demand.
Leveraging advanced analytics to foresee customer expectations
So how exactly can automakers and dealer tap into the wealth of data advanced analytics provide? Put simply, they need to equip their cars with edge devices capable of sensing, collecting and transmitting data to their network via the cloud. This enables automakers and dealers to learn about user behavior and vehicle performance and maintenance.
To fully leverage the power of advanced analytics, it’s essential that automakers and dealers embed edge devices not just within their cars, but in every piece of machinery suitable for data collection. This permits automakers and dealers to gain a 360-degree view of their operations.
When brought together, the various threads of advanced analytics coalesce into a comprehensive data visualization map, i.e. the “bigger picture”. This helps automakers and dealers to better understand customer needs and how they can be satisfied. Ultimately, advanced analytics enables better demand planning, which is essential for driving profits.
Put demand planning at the center to drive revenue
Demand planning for new cars is necessary to drive other revenue streams. In France, the market is slowing down, with a decrease of 0.7% of new vehicles registration in 2019.
OEM’s expect revenues generated by the sales of new cars increasing after the lockdown due to Covid-19. However, if incentive policies remain unchanged and outdated planning tools are kept in use, we can expect a similar increase in the amount of rebate money spent by OEMs and dealers. Therefore, it’s critical OEMs and dealers act as soon as possible to limit the erratic rise of this expense.
Optimized demand planning is about achieving the most successful product mix
We believe that it is possible to optimize demand planning without fundamentally changing how the entire supply chain works. Such optimization could be operated at the assembly plant for different planning horizons.
- First, on a large horizon, at model level (body style, engine, etc.): keeping in mind the full capacity model in use today, the right product mix should be found to maintain total volumes produced at the plant. Since models within the same series are produced at the same plant, finding the right product mix is about allocating production volumes to the right models within the same series. On average, major OEM plants produce between 1.4 and 5.7 models per plant.
- Then, on a shorter horizon, at configuration level (color, etc.): keeping in mind the trend towards higher levels of customization and demand volatility, optimized late differentiation would enable car customization that is more in line with the latest trends, prior to delivering “final” cars to dealerships.
This optimization will ensure that dealership cars will better correspond to customer expectations:
- Fewer customers will have to wait for their ideal model: this can reduce the risk of customers switching to another dealer, or even switching to another brand/OEM. More and more customers are visiting dealerships with a firm idea of what they want to purchase and are expecting to validate their choices with test-drives. Around 50 percent of customers will even spend more than 10 hours exploring potential options before visiting a dealership.vii Therefore, if the desired models are not available, the customer will have no qualms about switching to another dealership.
- Reduced wait for customers thanks to a shorter time-to-market: this will increase customer satisfaction. In markets such as France, there is plenty of leeway for improvement, as the average wait is 20 days.
Technology has always been the limit for the dealers and OEM’s to improve the forecast of the most probable combinations the customers will buy most certainly.
- Usual demand planning and forecasting tools are designed for experts: in all industries, sales forecasting is one of the most complex process and in automotive, the incredibly large amount of combinations increases even more the likelihood to fail in the prediction. Those tools are also usually driven by transformation programs of the entire Supply Chain; they are usually seen as systems to collect the demand of the whole distribution network to allow the Supply Chain and the Manufacturing to plan the cars, their components and then to deliver them to the dealers. Often, the dealers chose then to use the sales history, the quotas of their OEMs and their knowledge of their local markets to order the cars that will fulfill their inventory.
- New technology enabled notably by Artificial Intelligence will help the dealers and the OEMs: using sales history to perform a reliable sales forecasting process is not enough. Adding the “market intelligence” represented by the knowledge of the dealer on his market is also more and more tricky and source of mistakes. Consumers follow market trends, often being influenced by social medias and also their neighborhood. The recent events, notably the Covid-19 pandemic, have generated new parameters that will impact drastically the demand patterns and trends across all professional and social categories. All those criteria won’t be easily managed by the standard behaviors, systems and processes. New technologies enabled by Artificial Intelligence to combine dozens or parameters in a very short time and in a very comprehensive way for any dealer will be beneficial. Digital capabilities will help the buy-in by providing simple tools as easy as any app installed on the mobile applications of almost everyone.
Reducing excess stock also enables other benefits for the rest of the supply chain
- At suppliers’ level: More reliable spare parts orders therefore better relationships with OEMs.
- At plant level: Production more aligned with customer needs hence more efficient use of automaker resources.
- At OEMs HQ level: Decreased cost of inventories and improve network relationship management.
- At dealership level: Increased power and accuracy when negotiating objectives and number of vehicles with OEMs, decreased cost of inventories.
- At retail customer level: Less wait time therefore increased customer satisfaction.
The automotive market is very different to how it was ten years ago. Changing customer mindsets, regulations, new technologies and a constrictive industrial model that limits innovation are forcing automakers and car dealers to spend billions on incentives every year. But deep incentives cut into margins, reducing profits and the ability to keep profits growing at a steady rate.
However, by leveraging the power of advanced analytics, and Artificial Intelligence notably, right along the entire supply chain, automakers and dealers will be equipped with the data necessary for predicting customer needs. Advanced analytics enables optimized demand planning and the ability to accurately forecast customer trends in order to improve offer and demand matching. In an era of disruptive technologies, it’s time for the automotive industry to re-establish its relationship with consumers by giving customers what they need, when they need it.
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