Using Data to Optimize Wholesale Distribution
In talking with wholesale distributors around the world, I’m always amazed at just how much data they collect and store in-house. From original manufacturing and assembly data to shipping and logistics information, I’m certain that distributors have access to more data than any other player in the value chain.
Interestingly, most distributors are not using this data to their full advantage. By accessing huge volumes of Big Data combined with powerful predictive analytics solutions, the opportunities to gain value from data are broad and continue to grow. Yet these data assets – which should provide ongoing insight into the business – are rarely analyzed or optimized.
I understand why this happens. Sales managers and finance executives struggling to keep pace with day-to-day activities believe they lack the time and technology to perform detailed analysis or use business intelligence to optimize operations. And that may have been true – 10 years ago.
Today it’s a different story. A variety of business tools can help you analyze raw data and better understand your operations, customers, and partners. The solutions are easy to use, and they can be deployed quickly and affordably. With the resulting insight, distributors can make changes that improve not only the business but also the bottom line. Here are a few examples of how wholesale distributors can use technology to maximize their profitability.
Identify the true cost-to-serve your customers
Many distributors view any customer as one worth having. However, the reality may be a little different.
By analyzing all of your data, you can understand the true cost to serve each customer. Analysis can help you identify which customers are profit makers, which destroy profitability, and which fall somewhere in between. Further analysis can help you determine which factors contribute to profitability.
Once these fundamentals are clear, you can pinpoint changes that will increase profitability. For example, changing the service model from direct sales to tele-sales, reducing discounts, or imposing minimum order quantities can reduce the cost to serve your customers.
Anticipate what’s next
Predictive analytics can help distributors analyze existing data to gain insight into what may happen next. Using these tools to review past patterns and spot current trends, companies can anticipate when a customer is likely to turn to a competitor or when local or regional conditions may impact operations.
For example, a food distributor could combine in-house data and long-range weather information to predict when certain products are likely to be in demand. Let’s say the long-range weather forecast calls for a cold front to hit Chicago in 30 days. A distributor can use this insight to provide a value-added service to its retail customers in the Chicago area, recommending that they stock up on hot chocolate mix and pancake syrup to prepare for heightened customer demand.
Many of the new predictive analytics tools are easier than ever to use. Instead of requiring data scientists and mathematicians to gain insight, these solutions offer intuitive dashboards and querying tools that can be used by traditional business users.
Performing profitability analysis
Every business changes over time, and so do its technology solutions. In the past, reporting and analysis were limited by the structures defined when the software was first implemented. This restriction could limit the analysis performed on newer data sources, business systems, or organizations.
Using the power of in-memory computing solutions, distributors can quickly analyze profitability for their companies, products, and customers – without reconfiguring solutions each time something changes. Using raw data captured from sources as diverse as general ledger postings, sales orders, and invoices, companies can use these solutions to determine the best steps for maximizing profitability.
For example, a pharmaceutical distributor was considering bidding on a new contract and wanted to understand whether such a contract would be profitable. Using an in-memory computing solution, the company was able to crunch all of the data and determine in less than one day whether it made good business sense to submit its bid.
Most distributors already have all the data needed to make smarter, faster business decisions. SAP offers business analytics solutions that can be deployed rapidly, with a fixed scope and an affordable cost. We’d be happy to show you how quick and easy it can be to turn your data assets into business intelligence. Are you ready to get started?
Karen S. Lynch
Global Head of Wholesale Distribution Industry Business Unit SAP