Data Quality to Optimize Supply Chain & Asset Management
Industry: Utility & Transmission
Country/Region: Canada, USA, Australia
Business Needs: Supply Chain Optimization, Data Consistency, Reporting, Visibility
IT Issues: Data Quality Management, Automation, ETL, SAP Business Objects
Background
Our client is a large power generator and marketer of electricity and renewable energy with approximately $3 billion in annual revenue, more than $9 billion in assets, and power plants in Canada, the United States and Australia.
Challenges
Prior to Groundswell’s engagement, the client made previous efforts to implement a data quality strategy. A manual process was required to identify inconsistent or poor quality data, which was a reactive and inefficient response to their data challenges. On previous implementations, instead of following a business approach, the client tried a technology-focused approach which required business users to learn new technology and data quality principles in attempts to make business decisions, which created waste and loss. Additional challenges included lack of senior management’s visibility into the value of data quality. This resulted in limited adoption, and thus, ineffective governance surrounding the use of the tool across the organization.
Goals
- Automation of manual processes directly associated with monitoring data quality throughout the organization.
- Support and further optimization of existing supply chain and asset management processes.
- Reduction of rework associated with inconsistent and/or poor data quality in the client’s respective systems.
- Production of a consistent process for data quality adoption throughout the enterprise.
Solutions & Results
Groundswell’s approach was business-focused. Our team’s main goal was to limit the technical complexity and illustrate the value of data quality to business users, technical teams and senior management. We helped our client define an appropriate data quality management process that could be easily adopted as part of their existing and over-arching corporate governance strategy. Our goal was to enable the business to make timely decisions based on clear, consistent and trusted data with a single location to monitor data using the client’s existing technical assets and knowledge. This approach enabled us to deliver on-time and on budget. By providing our client with the right tools, understanding and process, the organization has successfully enabled the business, management and technical users to adopt data quality initiatives enterprise-wide, and realize the value of their investment.
Technical Details
As part of the project Groundswell successfully delivered on:
- Data quality initiatives across seven business domain areas utilizing an agile methodology.
- Four tailored user interfaces for business users and IT.
- Development of ETL processes to manage the data, execute and automate business and/or technical rules.
- Development of reports in SAP BusinessObjects to provide business and senior management visibility.
What are the Top Three Business Requirements when Building an Information Management Strategy?
By Jakki Geiger, Informatica
Assets are mission-critical in industries such as Utilities, Oil & Gas and Transportation industries, to name a few. Organizations must do a good job managing assets in these industries in order to pinpoint problems, fix them quickly and report on them accurately. Often, there’s a huge gap between what employees know about assets and what they should know about assets, because asset data is scattered across multiple applications such as Vendors and Suppliers, GIS, Finance and Maintenance Operations.
Some companies recognize the value in shifting from an application-centric to an asset-centric view of their operations. They use a combination of Data Integration, Data Quality and Master Data Management (MDM) to manage and master their mission-critical asset information in a central location on an ongoing basis and share it with operational and analytical applications so they can take the next best action and make next best decision.
Business leaders in supply chain and procurement, marketing, sales and customer service have never been more involved in the decision-making process. They recognize the huge cost bad data has on their operations. They want their teams to not only have world-class applications, but world class data so they can do their jobs better and innovate faster.
