The Decision Maker

Existence of Information Silos May Reveal How You Value Data: Top 5 Reasons to Remove Data Silos

Posted by Chuck Gulledge, CPA on Feb 17, 2014 12:59:59 PM

1.Enhance Data Quality and Consistency – Integrated data provides a common data model to allow standardization from the various departments. So you can have more confidence in the accuracy of your data. Accurate data is the basis for strong business decisions. Without integrated data, a credit union runs the risk of making critical decisions based on insufficient or inaccurate information. Making decisions based on "gut feel" with the mountains of data that exists no longer works. Data retrieval is no longer a full time position when data silos are removed. Easy access to a single source of truth will move you from data gathers to data analysts.

2. Supports Enterprise Reporting – Decision are made both on a departmental level and enterprise level. Data silo’s make reporting at the enterprise level very cumbersome. Spreadsheet reporting is still the dominant reporting solution in credit unions. Some have moved to dashboard reporting, but these dashboards are not intuitive and do not allow for drilling in to the detail. We have seen how effective dashboard reporting at the branch level has helped to increase sales and productivity.

3. Supports Enterprise Analytics – Understanding member behavior is no longer just mere buzz words. Companies outside of the credit union space use predictive modeling to not only retain customers, but to increase sales with those customers. Target used customer information to predict which customers would be future mothers. Amazon uses data as a competitive advantage. They sale more online than its next 12 largest competitors combined.

4. Improved Marketing Efforts and Success

A.) “Half the money I spend on advertising is wasted; the trouble is I don’t know which half.” - John Wanamaker, US department store merchant (1838 – 1922)

B.) “Marketing today is not about silos, Marketing is about a full integration of analytics, to brand, to the actual execution,” adding that having a wealth of data can be great, but “if we can’t change the customer experience, it’s all of no use.” John Wallis, global head of marketing and brand strategy at Hyatt Hotels Corp. www.forbes.com.

5. Moves you Beyond Relevant – Credit unions have stayed relevant by adding online and mobile technologies, and in some cases are on the 2nd generation of technologies. So what’s next? Use integrated information to grow wallet share and promote cross selling opportunities, use BI to develop a turnkey member rewards program, or use data to predict who will default on a loan. (Joe Breeden of Prescient Models (http://www.prescientmodels.com/aboutus.html) describes in his book, Reinventing Retail Lending Analytics, the algorithms, problem designs, and validation techniques that provide the most robust solutions for these loan portfolio).

So, how do you eliminate the information silos? A data warehouse (DW) is the foundation of any data integration and business intelligence platform. A DW allows your credit union to create a central location and permanent storage space for the various data sources needed to support your analysis, reporting and other BI functions. When researching vendors and potential technology partners, first and foremost they need to understand credit union data. They need to be experts in credit union core and ancillary systems. Other considerations in implementing a DW is the data structure, performance capabilities, and overall project costs. Performance relates to the ability to access data and to develop reports that are drillable to the transaction level in seconds.

Credit Unions must view data as a strategic objective and another project. They need to eliminate the information silos and create a BI platform that allows them to use data as a strategic objective.

 

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Topics: Analytic Data Model, Data Analytics