Automotive manufacturers face many challenges when evaluating and optimizing the performance of their sales channel, which can include thousands of franchise and non-franchise dealerships in the U.S., Canada, and other countries worldwide. Yet, auto manufacturers often lack direct visibility into the day-to-day activities of an auto dealership. A manufacturer can identify low- and high-performing dealers by their bottom line, but gaining insight into why dealers perform as they do and increasing their performance proves to be more difficult.
A web-based dealer scorecard application can track performance for sales, customer satisfaction and other select metrics. Typical performance measures include a total score and scores for sales, customer satisfaction and other select metrics. To optimize dealer channel performance, a scorecard must do more than simply compile data and generate a report.
The design and implementation of a scorecard makes a significant difference. Too often a scorecard reports data from multiple, conflicting databases with little correlation between measured variables and performance. An effective scorecard must be timely, accurate and meaningful.
Meaningful Metrics
What is often missing from the development of a scorecard is metric rationalization. Performance results are tracked without an understanding of how metrics interact with one another and how they impact business goals. Tracking results does not evaluate how well a dealership is performing its activities, only their effects. For example, good or bad sales may be the result of general economic conditions or some other external factor. Consequently, a dealership that shows good sales numbers will get good scores even if its activities are deficient.
The meaningful scorecard correlates metrics to performance and allows users to drill down to more detail and supporting data for performance scores. If dealers understand the reasons for a score, they can make well-informed decisions that optimize their operations.
OEM corporate personnel can use the scorecard to evaluate and make decisions that further improve the operation of the entire dealer channel. Individual dealers may see the benefit of adopting best practices or certifications that have been designed to address low-scoring metrics, and OEMs can identify systemic problems in their sales channels and optimize performance accordingly.
As an example, a common performance measure in the automotive sector’s retail channel captures vehicle repairs by a dealership’s service department. This metric usually measures the efficiency in repairing customer vehicles by tracking the number of vehicles that are repaired correctly the first time. (Vehicle does not require multiple visits to dealership to correct the same problem.)
Supporting data for this metric may show that the service manager and technicians for a specific dealership have not taken training related to diagnosing and servicing vehicles. The dealership owner may then decide to increase staff training to address the metric. If the FFV metric is low for a large number of dealerships, the manufacturer may require the training through a certification program and establish other best practices that would improve the metric.
Another aspect of meaningful metrics is context. Scorecard users belong to different audiences: the organization they work for (corporate or dealership); the region where they operate; and for dealerships, the characteristics of their business that varies from others (size, for example).
Dealership staff should only be able to access and view detailed information for their own dealership and job function. A dealership owner or manager may see a larger picture that includes how they rank on metrics when compared to similar dealerships. Sensitive financial data should be restricted to the owner and others in accounting. Corporate users may see all dealerships or at least all those in their area of responsibility. These users may also have access to other reports that aggregate data so they can make region- or channel-wide decisions.
Since one size does not fit all — there is great variation among dealerships — performance scores and metrics should be calculated and scored according to the capacity of each dealership. Some metrics should carry more weight and score against established performance targets for differently sized dealers. (For example, a larger dealer must achieve higher unit sales than a smaller dealership to get an ‘A’ score.) Other metrics may be provided for informational purposes.
Most manufacturers have global operations, so the scorecard interface must be localized to the different regions where dealerships operate. Language preferences of individual users can be triggered in a few different ways. The preference can be stored in a centralized user profile that is used by the scorecard and other applications in a dealer portal. To change language preferences the user changes the profile.
User profiles provide a uniform mechanism to localize many different applications, but changing preferences requires a modification to the profile. Another common practice adds a toggle to the interface that allows a user to switch languages on-the-fly. A toggle switch provides flexibility, but uniformity is lost if the same toggle switch is not implemented across all applications accessed by the user.
Another alternative assumes that the user can set and change their browser settings according to their need. The scorecard simply renders the page in the language set by the browser. While this solution makes localization settings independent of the application, uniformity with other applications depends on how they handle language preferences. The advantage, however, is ease-of-use from the user perspective. If they have already set language preferences to meet their general web browsing needs, nothing additional is required of the user for the application.
Finally, historical context is important. The scorecard must maintain historical reports to track performance across time. With historical data, decision makers can make more informed judgments by correlating performance to other data trends and external events. For example, “Our unit sales on SUVs were greater a year ago than now, but fuel prices were much lower, and a new SUV had just been introduced.”
Timely and Accurate Data
When meaningful metrics and supporting data have been identified and implemented, the scorecard data must represent accurate data that can be easily accessed and reflects the most current performance of the dealerships. If assembling information is too cumbersome and time consuming and the data is outdated or not even correct, the dealer scorecard cannot enhance decision making for the manufacturer or the dealer.
One of the primary challenges when launching or overhauling a dealer scorecard application is the migration of a diverse range of existing data sources into an integrated solution. Data feeds may be processed on different systems, including those of third-party vendors. Creating reports and correcting mistakes can be difficult, often involving many people. In addition, unlike a balanced scorecard used solely by corporate managers, security and other technical or political requirements may dictate that dealership staff and cor
