Recently, we looked at BPI (Business Process Integration/Process Integration) and how it can enhance customer experience and revenue. Next, let’s look at data integration and its impact on profits. Data integration involves extracting or sharing data from dealer systems and aggregating it into an OEMs database(s).
Data Integration and BPI Differences
BPI involves data synchronization in real time (or close to it) and typically involves a single process or transaction that can be influenced quickly. Providing customer incentives in real time as the car buyer is making decisions in the showroom is one example.
Conversely, data integration typically involves moving large amounts of data on a scheduled basis, often at the close of business for the retail locations. This data is then warehoused, processed and sent to various business groups for use in reporting, business analytics and business intelligence.Typical examples of this data could include retail sales, and parts and repair orders.
Process integration and data integration have important differences as to their use. Process integration can help a dealer find a critical part at another dealership, assist in the sale of a vehicle and boost the profits of the F&I department.
Integrating dealer data is usually retrospective in nature, yet can be used as a powerful tool that can drive business analytics which can be used for forward looking strategic decisions. A business unit focused on aftersales may use it to fine tune their programs on a national, regional or global level.
Data Integration and BPI Similarities
Both can have large impacts on a company’s bottom line. In terms of economics, process integration often has more of an effect on a micro level. An example would be a small retail transaction that is frequently repeated at many dealerships. Think of a bucket that is filled continuously by drops of water. BPI can drive retail sales by improving customer experience via leveraging CRM data to fine tune vehicle selection, optimize incentives, and speed up the F&I process.
Data integration is typically opposite of BPI in scope and affects the macro scale. If BPI’s are drops of water, then integrated data is a firehose. It often impacts large processes such as manufacturing, supply chains and global business planning/analytics. Just how important is solid data integration? Consider these examples from a recent IBM study of analytics within the automotive industry.
A global automotive company was able to reduce their defect rate by 50 percent in 16 weeks using predictive analytics to better understand and eliminate issues in the production process.
A European OEM was able to identify over GBP400 million in savings through the creation of a data pool, which allowed them to analyze and compare the worldwide spare parts business in detail for the first time.
No matter how you slice it, both BPI and data integration require that at the retail level, data can be collected, organized and integrated into the OEM system. The key component of successful implementation of both is the presence of a strategy that recognizes how valuable quality data is to the economic viability of an OEM and focuses adequate resources on ensuring that collected data can be leveraged to improve all levels of operations.
Once enough emphasis is placed on process integration and data integration, they will be seen as true opportunities for revenue growth and or reducing costs. This will then move retail and other integration programs, which are essential for monetizing data, from the category of “necessary evil” to programs that can be expanded and utilized in new and exciting ways. In future posts, we’ll dive into the current state of integration in automotive and look at characteristics of well conceived integration programs.