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Data & Intelligence

Beyond the BI Strategy: 4 Steps to ROI

In a recent issue of PC Today (www.pctoday.com), there was a quote by Cindi Howson of BI Scorecard that really stuck in my mind: “There are far too many cases of companies having good data, good tools, but a culture that’s a barrier to using that data for action.” Frequently, outside Beyond the BI Strategy: 4 Steps to ROIconsultants are brought into an organization, especially in healthcare, to pull data out of silo’ed applications, cleanse it and land it in an enterprise data warehouse (EDW). Then the real fun begins as the organization tries to determine what their expectations are from this treasure trove of data. More importantly, this struggle to determine the value of the integration of clinical, operational and financial data can stall the return on investment for this important and difficult effort.

In conducting a business intelligence (BI) strategy, it is very important to investigate those silo’ed data sources to determine which elements can benefit which part of the organization and to notify internal groups of the new resources. In other words, the Enterprise Data Warehouse needs exploration and promotion to the key stakeholders or by the key stakeholders to gain new insights and derive the new value. Matching data to the right people is fundamental to success and deserves its own tracking mechanism in data governance. Moving beyond the original stakeholders and their requirements in a BI strategy and getting down to who really will use the data and how it is used helps drive stronger outcomes for the use of the integrated data. It truly isn’t just start with the end in mind, but exploring how the new integrated views of information can drive improved operational processes and solve daily problems in a real-time manner.

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It is often frustrating to data warehouse builders because they understand the value stored inside but don’t know who needs the information to take action. It is worth educating and promoting this big investment! If a key data source is overlooked for real improvements in an important corporate process, then find it and add it. If data has moved past its useful life, then it should be moved to an archive to keep the enterprise data warehouse relevant and in step with the organization. Many organizations set up BI Competency Centers to help govern and develop the enterprise data warehouse, but my suggestion would be to make those centers a place for brainstorming, exploring and deriving value on an ongoing basis.

In healthcare, as we strive to lower costs and adopt a lean process improvement methodology, our process of using high-quality data should help identify new revenue opportunities, serve our communities more effectively and encourage us to explore possibilities. That exploration should start with the data that we work hard to acquire, extract, transform and load in our enterprise view. As data comes in faster, we need to respond quickly by connecting the data with the right users.

To summarize, in moving beyond the build stage of an enterprise data warehouse and gaining the return on investment, there are four key steps:

  1. Identify the “new” stakeholders that will use the EDW in their daily jobs
  2. Help the new stakeholders explore and learn what data is available to streamline clinical, operational or financial processes, possibly in a BI Competency Center to master tools
  3. Promote the success stories to create action from all parts of the organization
  4. Realize the return on investment from your EDW – celebrate!

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Martin Sizemore

Enterprise Architect with specialized skills in Enterprise Application Integration (EAI) and Service Oriented Architecture (SOA). Consultant and a trusted advisor to Chief Executive Officers, COOs, CIOs and senior managers for global multi-national companies and healthcare organizations. Deep industry experience as a consultant in manufacturing, healthcare and financial services industries. Broad knowledge of IBM hardware and software offerings with numerous certifications and recognitions from IBM including On-Demand Computing and SOA Advisor. Experienced with Microsoft general software products and architecture, including Sharepoint and SQL Server. Deep technical skills in system integration, system and software selection, data architecture, data warehousing and infrastructure design including virtualization.

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