With the 43171804 code attached to any PDA in the company's data sources, the organization can more readily understand how much is spent on PDAs. From here, a tool for spend analysis will give them the ability to determine which types of PDAs they are buying, from whom they are buying them, and how much they are spending with each vendor or for each type of PDA. However, if a company's groups were limited to a more generic category like "Computer Hardware," all computer hardware would be part of the same group. Everything from an inkjet printer to a high-end server might fall into the same category.
Today, most commodity classification is done as a service, usually through an off-site services engagement. Corporate information is sent in bulk to these services on a regular basis to have an industry-standard code attached to product records. This approach has several risks:
- Accuracy: The staff at these service firms often does not know the client's business and may not know the correct code for an item.
- Inconsistency: Two people may code the same item in different ways, or an individual can inadvertently apply different codes to the same item.
- Expense: These engagements are typically priced on a per-record basis, creating a costly recurring expense.
- Timeliness: Coding services usually take weeks to complete, which means the organization continues to use questionable data while the data are being analyzed offsite.
By contrast, automated coding by a data quality system can be less risky. Rules are built into the system by product specialists or procurement professionals – the people who know the parts and the business. The resulting output from data quality technology is consistent and offers higher degrees of accuracy. It is easy to modify the rules and make the system more intelligent. The process can be run at any time, on any data and as often as the company needs to run it. Answers are available in minutes, not weeks. And since companies can process these files internally, however many times they need, the per-record coding expense is eliminated.
The current business climate is putting pressure on every facet of the organization. For procurement managers, the pressure is only going to increase as companies look for ways to increase efficiencies and save money. The procurement organization must make tough decisions, and the health of those decisions is entirely contingent upon the use of reliable, accurate data.
While many companies have invested in various procurement systems in an effort to improve their spend analysis practices, such systems often fail to address the most pressing need of all – to create and implement the best possible sourcing strategies.
To successfully exercise control over corporate spending, companies need:
- Accurate information about items purchased, including supplier quality, timeliness, performance, price and technological advancement.
- A method to rank suppliers based on the criteria most important to them.
- Flexible, business-focused strategies designed to deliver continual cost savings.
About the About: Daniel Teachey is director of corporate communications with DataFlux Corporation, a provider of end-to-end data quality integration solutions to analyze, improve and control data. Previously Teachey held positions with IBM, MicroMass Communications and Datastream Systems. DataFlux is a wholly owned subsidiary of SAS. More information on DataFlux is available at www.dataflux.com.