Since 2008, a record number of U.S. dealerships have been closing. Overall dealership volume is down 6% from May 2008 to May 2009. According to the Urban Science Franchise Activity Report, this is the largest decline in the number of overall dealerships since 1991. Furthermore, the number or closures is steadily increasing and this trend is expected to continue as GM and Chrysler execute their network reduction plans and dealers across OEMs fall victim to the contracting market.
These widespread dramatic changes affect all manufacturers and make it challenging to manage an established network plan. Unforeseen dealership closures can mean a decline of market share, loss of a key location or a valuable operator. To date, manufacturers’ planning efforts have been limited to the use of dealer financial conditions, which provide little warning of future dealership distress.
To be proactive in managing a network in today’s troubling financial market, manufacturers need insight into which dealerships are on the brink of financial distress before it’s too late. By applying data-driven predictive analytics to the same historical data in use today, it’s now possible to flag distressed dealers six to twelve months in advance, allowing manufacturers to focus limited resources where they will have the maximum benefit on the overall network’s health.
Analysis helps OEMs see the future
Manufacturers need to change the traditional method of assessing dealer viability, and instead use a proactive scientific process that will arm them to appropriately allocate resources and protect market share.
The key to success is knowing in advance which dealers are most likely to be in distress. Using dealer business management data (operating reports) and predictive analytics, each dealer is assigned a score that indicates their likelihood of closure within the next six to twelve months; ultimately helping OEMs identify dealerships in distress when there is still enough time to take proper action.
To get the full picture of the network, manufacturers need to rank the dealer body based on a Risk Score, with the most at risk dealers receiving the highest scores. As the chart below shows, dealers identified early on using this methodology were proven to be 25 times more likely to close than an average dealer.
Identification - financial likelihood to fail
Armed with this knowledge, manufacturers should once again revisit their network blueprint and assess the importance of specific dealerships. Considerations include a combination of the location quality (visibility, accessibility, proximity to competition), operator performance and store size.
Next, OEMs should combine the dealer’s score based on financial data with their rank based on location importance, to plot dealers on a Dealership Risk Identification Matrix. This will reveal which of their most important dealers are at risk and identify the action that should be taken. This combination of network analysis and benchmarking dealerships against key financial performance indicators allows OEMs to focus scarce resources where they will have the most impact. Additionally, you can observe the healthiest dealers in the most strategic locations and extract best practices to share with others.
Dealer Risk Identification Matrix
The matrix provides the groundwork so OEMs can create proactive plans for each category focusing on high potential, at-risk dealers. It is also important to pay special attention to the geographical element since it provides context for your prioritised dealer list.
Unforeseen dealership failures can mean extended periods of lost sales as well as potential network disruption. OEMs need foresight in order to take control of their network planning. With an early warning system, manufacturers can identify distressed dealerships and be proactive in their planning. As a result, they will be able to mitigate unanticipated losses and position themselves for long-term success.
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