Industrial-Strength BI

Since first entering the Japanese market in 1999, RS Components has grown rapidly in spite of a stagnant economic climate, posting annual sales increases of nearly 30 percent.

The international distributor of industrial parts bases its world-class services in Japan on three tenets: on-hand inventory of more than 48,000 items, acceptance of even single-item orders, and same-day shipping by 6 p.m. The company dedicates itself to satisfying the needs of its customers through its high-quality service and support structure, which includes free technical support.

Along with the increase in the number of customers, orders and items in stock have come mounting volumes of data. To continue to enhance the level of customer satisfaction and to spur further growth, RS Components used SAS software to develop a business intelligence (BI) platform that provides deeper insight into products and customers.

Creating business through BI
RS Components is a global catalog sales organization that supplies products in 160 countries and regions around the world. The thousands of items it handles in Japan range from electronic and electrical parts to automation and mechanical parts, tools, service goods and consumables, and technical books. Because these are goods that may be required in small lots at the R&D or prototype stage, the company does not restrict customers to purchasing in bulk, but rather offers customers the product they need in just the required quantity and at the right time.

The model is unique to RS Components, according to Shoji Sugiyama, managing director in charge of data systems and customer service. "Since first launching services in Japan five years ago, we have continually repeated the process of data-based hypothesis, execution and verification to determine how to respond to customer questions and complaints about our products and services," he says. "From the very start, we have placed importance on data analysis and BI in company management."

SAS offers more effective data analysis
In conventional data analysis, the company would access enterprise resource planning (ERP), customer relationship management (CRM) or supply chain management (SCM) data as required, load it into the analysis database and carry out the analysis using a spreadsheet tool. However, the number of products – 25,000 when the service launched – increased by several thousand during the first half-year alone. The few hundred orders that it originally processed monthly grew to more than 1,000 per day. With the number of customers also increasing by several thousand every month, RS Components was rapidly approaching data overload. The time and cost involved in the analysis process became a major problem.

"While we had the data and the trained analysts," says Mariko Fujita, manager of corporate planning, "we were spending too much time in analysis operations, leaving us no time to promote new initiatives." In addition, due to the limitations in the volume of data that can be handled in the spreadsheet format, she felt that the company needed a full-scale BI tool capable of effective and finely tuned analysis. "So we decided to introduce SAS," she says.

Integrated BI platform, three interfaces
"There are not many tools that enable the effective processing of large volumes of data," says Sugiyama. For him, however, the deciding factor in choosing SAS was the ability of its consultants to understand his company's goals, way of thinking and approach. "They responded to our requirements as a partner we could trust, rather than as a simple vendor," he says.

Introducing SAS as the integrated platform for BI utilization and developing a data warehouse made it possible for RS Components to conduct analyses in all sectors of the company based on integrated data. In addition, SAS provides the management interface, featuring standardized reports that offer users drill-down capabilities for more detail. Various other analytic interfaces have been developed geared to different types of users. For example, an interface for planning analysis managers is capable of ad hoc query and reporting. Another delivers Web-based distribution of daily flash reports to all employees. This analysis environment not only improved the efficiency of data analysis but also made it possible for a wide range of employees to discuss business strategies based on the integrated data that serves as the common in-house language.

Increasing repeat visits by 20 percent
Once the company began to use the various interfaces to do customer analysis, managers discovered that many people were not returning after using the service for the first time. Qualitative analysis revealed that unclear terms of purchase and a lack of technical information were hindering second-time purchases. So RS Components set out to strengthen its services and bolster areas of inadequacy by placing follow-up calls to first-time purchasers, advising them of the company's technical support services and payment terms.

As a result, the company succeeded in increasing the repeater rate by about 20 percent. Effective follow-up periods and optimal timing were also worked out, further enhancing the effectiveness of this "nursery" program for nurturing first-time users. "With our sales promotion campaigns, we set assessment indicators prior to execution and then analyze the results afterwards using SAS," says Sugiyama. The result is that discussions are based on the results of the analysis, without any emotional charge. "Sales campaigns are often accompanied by failure," he observes. "What's important, though, is to be sure to follow the PDCA (plan-do-check-act) process in order to gain some advantage from that failure next time around."

Three cornerstones for growth: user, data and tools
Armed with all of the elements of BI utilization, including competency (analyst skills), materials (data) and tools (SAS), RS Components is now further reinforcing coordination with the company's CRM program and promoting greater customer satisfaction. "The reasons for the customer's views and actions are concealed in the data," says Fujita. "It is our intention to identify within the data indicators of whether or not our actions are acceptable to the customer. Then we will listen humbly to them and make every effort to ensure that they are more pleased."

Besides perfecting the current business model, the company is currently working on a concept for a broad business expansion during the next five to 10 years. "Whatever the case, our business is based on verification of hypotheses using data," says Sugiyama. "For new services, we will strictly follow the steps of trial runs, analysis of the results and deployment. I have the feeling that that process of building business is gradually reaching perfection."

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