SUPPLY CHAIN INTELLIGENCE: INITIAL FINDINGS

by Curt Hall

The use of data warehousing and business intelligence (BI) for optimizing supply chain operations is receiving growing interest by the industry. Vendors and IT service providers have introduced new analytical supply chain products and services, and companies are discussing their experiences at conferences and trade shows.

But how many organizations are actually using data warehousing and BI to analyze their supply chain operations, and what are the main issues they are encountering? These are the types of questions Cutter Consortium sought to answer with a recent survey in which we asked 118 companies a variety of questions pertaining to the application of data warehousing and BI for analyzing their supply chain operations. This article outlines some initial findings from this survey.

The Extent to Which Companies Are Practicing SCI

The first question we sought to answer was the extent to which companies are applying data warehousing and BI technology to analyze their supply chain operations. As shown in Figure 1, 31% of organizations surveyed indicate they are currently applying data warehousing and BI to analyze supply chain-related data. Moreover, as shown in Figure 2, 36% of the companies plan to implement supply chain intelligence (SCI) in the next 6-18 months.

Yes: 31%
No: 69%

Figure 1 -- Is your organization currently using data warehousing and business intelligence (BI) to analyze supply chain data?

Yes: 36%
No: 64%

Figure 2 -- Does your organization plan to implement data warehousing/BI applications (i.e., supply chain analytics) to analyze supply chain-related data within the next 6-18 months?

What Domains Are Companies Choosing to Support with Supply Chain Analytics?

Figure 3 highlights the functional areas or domains that companies are currently supporting with supply chain analytics. Note that plan analytics rank highest among respondents. This should come as no real surprise, as companies have been attempting to optimize their supply chain operations with planning and forecasting applications going back to the earliest days of applying supply chain management techniques. Data warehousing and analytics are a natural fit for helping companies integrate multiple data sources, measure and predict supply chain demand, and generate forecasts.

Plan analytics: 31%
Source analytics: 24%
Deliver analytics: 24%
Make analytics: 21%
Return analytics: 17%

Figure 3 -- What functional areas or domains of your supply chain are now supported by supply chain analytics? (Resondents able to select more than one response.)

Tied for second in most popularly supported supply chain domains are source analytics and deliver analytics. Companies are applying analytics to their sourcing operations in an effort to analyze and better manage such inbound supply chain activities as supplier relationships, procurement, inventory levels, and costs. Reasons for applying analytics to "deliver" operations include analyzing and improving such outbound supply chain activities as customer/client delivery costs and optimizing inventory levels.

So-called make analytics represent the third most popular domain that companies have chosen to support with supply chain analytics. Typical uses for applying make analytics include analyzing actual production versus planning and measuring the accuracy of the production plan for a certain period of time or operation.

Somewhat surprising is that return analytics rank last among survey participants. Return analytics are used for such operations as analyzing and measuring customer support performance, quality monitoring, and quality improvement. With all the hype surrounding customer relationship management, I would have expected this domain to rank somewhat higher -- at least somewhere in the middle as opposed to last place.

--Curt Hall, Senior Consultant, Cutter Consortium