Monday, 12 April, 2021
Vehicle manufacturers (OEM) and spare parts suppliers (IAM) possess and manage very large spare parts portfolios. In order to maintain position in a fast-changing and disruptive environment, OEMs and IAMs need comprehensive and high-quality data that allow for fact-based and quick strategic or operative decision making. Eucon’s big data solution ‘Market Data Engine’ is a digital mirror of the global automotive aftermarket and enables all market players to identify market developments and make informed decisions. An interview with automotive expert Osvaldo Celani on data analytics and market intelligence in the automotive aftermarket.
Mr. Celani, how has the demand for big data changed in the automotive aftermarket?
To answer this, you first of all have to shed some light on the aftermarket. The well-known, large car manufacturers and automotive suppliers have enormous portfolios of sometimes several hundred thousand parts to manage, which are sold to workshops in the so-called aftersales business. For suppliers to make strategic portfolio and pricing decisions, it is essential to understand the market, which has become very fragmented, complex and volatile. Accurate and actionable market intelligence and data-driven processes are becoming more important than ever for aftermarket players to be successful in the market, i.e. to retain existing customers and to win over new ones. Eucon’s “Market Data Engine” is a comprehensive market intelligence platform with unique data assets and best-in-class analytics that acts as a digital mirror of the global automotive aftermarket.
What are the advantages of data-driven decision making?
Data analytics presents great opportunities, as it helps to market large portfolios that are sold in different sales channels using dynamic pricing. Ever-increasing amounts of data can no longer be controlled manually. The ability of algorithm-driven methods to process large amounts of data exceeds human capabilities by far. By applying statistical models to a mass of data, decisions can be made much smarter and effectively. If manufacturers are able to identify how conditions are changing – for instance due to the increased use of online sales channels – they can take appropriate action. The Covid-19 crisis is only accelerating the need for data-based market monitoring, especially driven by massive reductions in headcount throughout the whole industry. In this setting, big data analytics has become a key success factor and companies investing in this area will strengthen their market position during and after the crisis.
How does Eucon’s Market Data Engine work?
We create a digital map of the automotive aftermarket by collecting available market data and making this information available on a data platform. Our aftersales experts continuously monitor nearly 80 different markets around the world to understand price developments of spare parts across various sales channels. With around 12 billion pieces of market data, the platform provides insights based on mass data and advanced analytics, shifting away from one-off analysis to regular market monitoring to keep up with the speed of change.
Which data does the platform contain?
The Market Data Engine offers a unique set of the most important aftermarket product and market data types, for instance, spare parts catalogs, prices, market volumes, technical information or even trends. These data sources, singly or combined, form the basis for all analytics and can also be enriched with supplementary information, such car parc data. The biggest challenge is to collect and process the large amounts of data. Customers can then use the data to incorporate it into their own frameworks or applications. At the same time, we are building analytics functions on the various data pools, which help our customers make decisions on a variety of issues, for example with regard to the advantages of entering a market or as a basis for establishing a pricing strategy. The available information and business intelligence functions create the decisive factual basis for aftermarket players in a rapidly changing industry.
Other providers also offer digital market overviews. What is the difference?
Above all, most of our competitors can only offer limited sampling, but no worldwide market coverage. In addition, we provide our customers with big data analytics to extract usable information from the huge amounts of data. In principle, this means that they no longer must limit themselves to managing the most important 1,000 parts as in the past. With our technology, it is possible to view the entire portfolio. For example, an OEM or fleet operator can see who offers the right brake discs for a certain vehicle with a specific year of manufacture – and at what price.
The price comparison is of course an advantage that immediately makes sense. But is it possible to calculate price elasticities or to recognize developments based on historical data points?
Yes, there are most certainly situations where it is important to provide customers with historical prices. There is a certain price level for all parts for a specific model, built for example in 2004. But these prices evolve over the term of the production, known as “Lifecycle Pricing”. Competitors are added and after the warranty has expired, many car owners switch from an authorized workshop to an independent workshop that uses aftermarket parts. These developments can be observed with our tools and serve as a basis for the customer to identify trends. Or take another example. As a spare parts supplier or spare parts dealer, I can look at the price and market level in different countries. This means that I can design my sales or purchasing strategy accordingly.
Do the new mobility trends – such as electric drive or shared economy – have an impact on your database?
There are definitely new impulses. The electric drivetrain has led to the emergence of a new category of cars with its own spare parts portfolios. It’s all about the HV battery itself, its control system with all its electronic components and other specific systems such as battery cooling. All this has once again significantly expanded our database. When it comes to the shared economy, large fleet operators such as Uber and the trend towards full-service leasing from large leasing and car rental companies have led to changes of the customer demand structure in more and more countries. A new purchasing power has emerged vis-à-vis car manufacturers and also suppliers. These companies usually get special conditions due to their large purchase quantities. This creates an additional need for suppliers to know and understand the price information exactly. The complexity is continuing to increase, coupled with the ever-greater importance of online channels with their extreme price dynamics. To pool such information comes in handy, because more and more data is available and necessary to be successful in the market. Big Data is becoming “Big Big Data” here.
Looking ahead, what benefit do you see in Data Analytics, Artificial Intelligence and Machine Learning?
The advantage lies in being able to uncover the key insights from the massive amounts of data available today and derive proper actions. However, many companies are still in the very early stages of implementing intelligent data analysis. Data-driven analytics can reveal trends and metrics that would otherwise be lost in the mass of information. Artificial Intelligence and Machine Learning are taking data analytics to the next level. In the future, we will ask ourselves how we ever made decisions in the past.
Written by Osvaldo Celani, Geschäftsführer, Eucon GmbH