DSM, a global manufacturing company, achieved the following using DataFlux solution from SAS:
- Transparency necessary for effective spend analysis.
- Reliable and consistent data enriched with industry-standard eCl@ss codes.
- Reusable data quality processes through an SOA-enabled approach.
- Adherence to its data governance strategy, leading to measurable results and more efficient achievement of business goals.
- Ability to correctly assign eCl@ss codes for driving improved spend analysis.
How SAS® Can Help
Through solutions provided by DataFlux, a SAS subsidiary focused on data management, SAS provides the ability to classify and cleanse spend data and analyze and report performance and purchase history quickly, easily and in real time using a Web services framework. The foundation of this offering is a match and classification engine that examines existing data and appropriately assigns the correct taxonomy description and code.
This capability enables:
- Reports designed to uncover and remedy specific purchasing pains.
Reporting by subject area, including:
- Measure progress toward a goal (scorecard metric or KPI).
- Provide breakdowns of progress by organizational units.
- Show detailed information within each organizational unit.
- Suggest actions that help to mitigate supplier risk.
- Trend analysis, in order to proactively target emerging problems.
As a result, you will be able to:
- Reduce costs, mitigate risks and improve profits by defining a process to achieve an enterprisewide view of spending, enabling strategic sourcing and contracting processes.
- Establish consistent supplier performance measurements and procedures.
- Classify and cleanse spend data, and analyze and report on performance and purchasing histories so you can optimize spend, rationalize the supply base and reduce supply chain risk.
How SAS® Is Different
The solution provided by DataFlux is built upon a single data management platform, providing:
- Prebuilt scorecards and dashboards on the health of inventory, item, product or services data that ranks suppliers based on predefined metrics to monitor and manage performance.
- A services-oriented architecture (SOA) framework that simplifies the process of extending business rules throughout the IT environment, resulting in reduced system costs.
- More control of the procurement analysis process vs. an outsourced spending analysis tool.
- Data quality capabilities across databases, including duplicate record removal and the ability to merge current material data with catalog data for the rationalization of inventory data across business units.
- The ability to determine the complete volume of business with a vendor to help rank suppliers in terms of criticality to the supply chain; helps with volume discount negotiations.
- A means to assess compliance with, and results of, past sourcing activities.
- An automated, centralized spend analysis to help identify potential spend savings companywide.
- The ability to provide suppliers with up-do-date performance information.
Related Products and Solutions
SAS® Business Intelligence
SAS Business Intelligence gives you the information you need, when you need it, in the right format. By integrating data from across your enterprise and delivering self-service reporting and analysis, IT spends less time responding to requests and business users spend less time looking for information. SAS Business Intelligence also offers an integrated, robust and flexible presentation layer for the full breadth of SAS Analytics capabilities, including statistics, predictive analytics, data and text mining, forecasting, and optimization – all integrated within the business context for better, faster decision making.
SAS® Visual Analytics
SAS Visual Analytics is a high-performance, in-memory solution for exploring massive amounts of data very quickly. It enables users to spot patterns, identify opportunities for further analysis and convey visual results via Web reports or the iPad®.
A key component is the SAS® LASR™ Analytic Server, which quickly reads data into memory for fast processing and data visualization. Users can then explore all data, execute analytic correlations on billions of rows of data in just minutes or seconds, and visually present results. This helps quickly identify patterns, trends and relationships in data that were not evident before.
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