Customer information at a glance: How Schmitz Cargobull wants to classify its customers in a more targeted way
Schmitz Cargobull (SCB), a leading manufacturer of trailers and semi-trailers, is faced with the challenge that the cost-benefit ratios in relation to the respective customer and market requirements can only be determined with an enormous amount of manual effort. In the it’s OWL project ‘Data-based product management (product.intelligence)’, the company is therefore developing a tool for a detailed categorization of customer activities. In this interview, Iwen Skutta, Product Manager at Schmitz Cargobull, explains the difficulties that product management currently has to overcome and what solutions are on the horizon to improve data consolidation and provide an improved overview of customer information.
What problem does product management currently have?
Iwen Skutta: “There is no optimized presentation of consolidated customer information for product management. A cost-benefit ratio is not immediately apparent, and a decision has to be made between the contribution margin and the time required. In addition, previous activities are scattered across the entire company, as customers have different points of contact with Schmitz Cargobull, such as complaints, the procurement of spare parts, services or trade-ins. These can only be determined with a considerable amount of time. The total cost of ownership, including all contribution margins across all points of contact, can only be determined with enormous effort.”
Total cost of ownership explained
The Total Cost of Ownership (TCO for short) refers to the costs incurred over the entire service life or life cycle of a product. These include acquisition, personnel and maintenance costs, etc.
How can the effort for data consolidation be reduced?
Iwen Skutta: “A tool that aggregates customers according to different categories from different phases, such as the offer, order and aftersales phase, would be conceivable. For example, it would show that customers with predominantly rear-loaded vehicles have a higher number of collision damages and consequently higher repair costs. Adapted vehicle equipment or additional service contracts could remedy this and increase the resale value. For individual customers or customer groups, the TCO could thus be reduced while at the same time increasing the contribution margin for SCB. This data could be presented both per customer and per category in relation to each other.”
What advantages does the detailed categorization of customer information offer?
Iwen Skutta: “For example, spare parts sales, usage data from telematics and potential buy-back values could be used to derive an adapted new vehicle portfolio. Conversely, the right service could be identified based on certain equipment. The overall result is a better assessment of the market. This enables SCB to optimize its company portfolio with regard to one-stop shopping in a targeted manner in order to continue to meet customer needs in the best possible way. It also promotes clean and time-saving decision-making. The implementation supports product management with a data-based argumentation basis that is as objective and comprehensible as possible.”
What challenges need to be overcome during implementation?
Iwen Skutta: “A comprehensive TCO calculation is fundamentally difficult to present, as it resembles a full cost calculation. A lot of data is scattered in different places in the company. This data must first be consolidated and correlated. This currently requires a lot of manual effort, as there is no automatic evaluation function yet.”
