Menu

University business intelligence strategy

3 Comments

university business intelligence strategy

CIO Nov 5, 7: Rensselaer Polytechnic Institute needed a better way to make admissions and financial decisions. Like many organizations, systems and processes for collecting and analyzing business data were fragmented. Executive meetings to discuss strategy too often stalled over the accuracy of reported numbers. For example, how many faculty members or students did the university really have? Nobody agreed on a single set of terms to define them. Instead, different departments used their own definitions and different ways of looking at the data. On top of that, financial reports did not always contain the most up-to-date information. Furthermore, university researchers often kept track of their grants using shadow systems, requiring double the effort to get the university's ledgers to match the researchers'. Finally, the admissions staff needed more timely demographic information about its applicants to inform student selection decisions. Getting a handle on the data has been critical because higher education today is a tough arena. Government funding is down, requests for financial aid are up and admitting a diverse student body—in terms of gender, geography, ethnicity and academic achievement—has become more challenging. All these factors make balancing the supply of enrollment acceptances and financial aid with the demand from student applicants more challenging than in business past. The better Rensselaer could optimize its administrative resources and time, the more revenue it would have for courses and scholarships to attract the best and the brightest. The answer was a business intelligence and intelligence data warehouse implementation. BI tools have helped Rensselaer to refine its recruitment strategies and save time doing so. But getting the ROI for such projects can be tricky due to the changes in data reporting and usage they require. CIO John Kolb and his team had to establish cross-functional support for the project at multiple levels within the university; develop a vision for the project that could be built out in steps; create enterprisewide processes for collecting and using data; and support end users with communication and training. Once university leaders identified the need for the BI system, President Shirley Ann Jackson created business committee of top-level executives to sponsor it. The sponsoring committee was cochaired by Kolb and the vice president of finance. This group set strategy for the project. These business heads appointed representatives to a steering committee, which developed the overall implementation plan and controlled the scope and budget of the project. In addition, a number of implementation groups were formed including a data warehouse group that housed both technical and business staff to execute specific pieces of the project. Of course, creating cross-functional strategy and planning teams is important for any enterprise IT project, says John Hagerty, an analyst at AMR Research. But it's especially strategy for enterprise data warehouse and business intelligence projects because their success depends on broad user support and because consequential business decisions are made on the faith that information is accurate. When it came time university deploy the BI tools at Rensselaer, that top-down and cross-functional support was crucial. For example, Jackson made clear that she only wanted to see numbers that came from the data warehouse. Strict data governance was enabled through multi-committee support. And creating new processes for data reporting—such as how to divvy financial credit in multi-disciplinary research efforts—was aided by the cross-functional relationships and understanding university had been built up during the development phase. Once Rensselaer decided to deploy BI, the first six months of work focused on laying a business foundation. The grand vision for the project university that eventually, all business data would be filtered using the BI tools. And so, the university developed an overarching data policy and procedures that could be used by any intelligence created to define, cleanse and manage information on an ongoing basis. At the same time, Kolb's group created a systems architecture based on an Oracle data warehouse, Informatica's PowerCenter data integration platform and Hyperion business intelligence technology. For its first set of reports, the university chose financial information, unveiling a data mart a collection of data about a specific subject and reporting tools in November The finance group, like IT, works with everyone. And its success with the application made the group a powerful advocate. Hagerty of AMR Research says focusing on quick gains is a key to success in any BI project. This first project exposed a lot of dirty data contained within the ERP system, which provided a powerful reality check for users. Those mistakes—say a missing zero—may have originated with an inattentive employee. With the improved reporting system, the finance manager was able to suss out those mistakes more quickly. As a result, finance became a vocal advocate of clean data, and helped to enforce the new enterprise data policies. Another early project, which aimed to assist admissions, fed current applicants' data into the data warehouse. Assessing applications—who was applying, how desirable candidates were in comparison to others, who had accepted and so on—had been a matter of looking at outdated information. Through business intelligence reporting, decision makers can see daily changes to the application mix. This has enabled the school to choose more selectively based on the right combination of students they want to admit according to such factors as academic excellence, leadership, diversity of experience, geography, gender and ethnicity. Rensselaer created cross-functional groups to establish data accuracy, including teams which created common data definitions. Such activity, no matter how difficult it may be to get agreement, is crucial for the success of a business intelligence project. Kolb lists "one version of the truth" as strategy top reason why the effort has borne fruit. Colin White, founder and president of BI Research, agrees. End-user-facing business intelligence tools and dashboards may seem to be the sexier aspects university BI, but data warehouses and the data governance to ensure clean and consistent data are the foundation of successful business intelligence. Unless you've got accurate data you don't get the benefits," he says. Deploying an enterprise data warehouse is often the one way you can guarantee clean and consistent data. To ensure that data stays intelligence, you must put processes in place to make sure people find mistakes and correct them, says Ora Fish, project manager of data warehouse and business intelligence for Rensselaer. The university designated "data stewards" and "data experts" early in the project and made them accountable for the cleanliness of the data. Functionally, the data stewards are associate vice presidents and are responsible for setting procedures and policies for data management. Data experts are typically senior managers who report to the stewards. The data experts meet to set campuswide data definitions and take responsibility for any necessary cleanup of existing information. In addition, Rensselaer has other ways to enforce data cleanliness. One way is to define business rules for the data warehouse so that erroneous data is rejected for example, if an expenditure is submitted against a fund that is not active or if a student is given two acceptances and an e-mail is sent to the owner to correct it. Another is to mark nonstandard data such as a grant that is submitted without a code, with permission from a key business user. A third is to intelligence reports and queries analyzed regularly by data experts. Finally, end users are held accountable for what they enter into the data strategy. Knowing that, for example, the vice president of enrollment will look at a dashboard of student demographic data and see that some students' ethnicities aren't coded is a powerful motivator for that vice president's staff, notes Fish. It was clear that such big changes—no more reliance on shadow systems and the move to a new system—needed nurturing to take root, especially in an academic environment where strategy people pride themselves on individualism and freedom. To help ensure success, the data warehouse team collaborated with HR to write goals for using the data warehouse and business intelligence tools into the performance evaluations business some managers. In addition, executives and faculty were given mandatory training on business intelligence tools, data models and operations. Beyond that, the data warehouse group offered study halls and other support sessions, as well as newsletters filled with tips. Project leaders also set up a web page of BI informationwhich outlines participants, committees, project presentations and includes user-friendly sections on data warehouse terms and functions. It has also helped optimize expenses. Because financial information is available in near real-time, financial aid and budgets can be more closely monitored, improving budgetary management. And better historic data enables better forecasting. The Rensselaer university agrees. That success requires fundamental changes at multiple levels, which is only possible, she says, with executive-level commitment and sponsorship and close collaboration between the IT and the business side. The BI and data warehouse project "has allowed Rensselaer to significantly improve consistency and just-in-time access to institute information," concludes Kolb. The successful implementation of the project illustrates the transformative nature of IT. Whether you think your company uses the information or not, self-evaluations are a necessary device for Are you worried about relying on a third-party online service provider to store your business data? From alternatives to Microsoft Office to full-blown ERP systems, open source software can provide free From cost containment to hybrid strategies, CIOs are getting more creative in taking advantage of the From telling everyone they're your customer to establishing a cloud strategy, these "industry best Looking for a leg up in your IT career? IT certifications remain a proven way to quickly gain valuable Rapid shifts in technologies—and evolving business needs—make career reinvention a matter of survival This ad will close in 20 seconds. Here are the latest Insider stories. More Insider Sign Out. Thank you Your message has been sent. Sorry There was an error emailing this page. By Diann Daniel CIO Nov 5, 7: Why Is Getting It Strategy So Difficult? The Brain Behind The Big, Bad Burger And Other Tales Of Business Intelligence. Keys to BI Strategy The Impact of SAP's Deal With Business Objects Three Business Intelligence Weaknesses An Introduction to Intelligence Intelligence For example, how many faculty members or students did the university really have? Here's how they did it: Think big, start small, deliver quickly. Create one version of data truth. Provide support for new behaviors. IT jobs bound for extinction. Business Intelligence BI Data Warehousing. Your guide to top tech conferences Potential Oracle acquisition of Accenture brings new digital twist. Sign up and receive the latest news, reviews and trends on your favorite technology topics. How to run your small business with free open source software. Emerging Trends in Vulnerability Management. Tricks, Threats, and Triumph. Data Breaches and Business Great Security Disconnect. Digital Transformation Calls for New Data Center Solutions. The 13 most valuable IT certifications today. About CIO Ad Choices Advertising Careers at IDG Contact Us E-commerce Affiliate Relationships Privacy Policy Terms of Service Site Map. Explore the IDG Network descend. university business intelligence strategy

3 thoughts on “University business intelligence strategy”

  1. Afigenskij says:

    The grown Krishna later returned to Mathura where he killed Kansa and put an end to his evil deeds.

  2. andreyzubrilov says:

    Place all received Damage Cards beneath the Adaptation Token Reference Card for easy reference.

  3. alabolite says:

    He took up studies in philosophy, mathematics, and natural sciences.

Leave a Reply

Your email address will not be published. Required fields are marked *

inserted by FC2 system