Lori Smith Vice President Business Intelligence Universal Technical Institute Chosen by Industry. Ready to Work.™

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Presentation transcript:

Lori Smith Vice President Business Intelligence Universal Technical Institute Chosen by Industry. Ready to Work.™

... a set of methodologies, processes, architectures, and technologies that transform raw data into meaningful and useful information used to enable more effective strategic, tactical, and operational insights and decision-making Business Intelligence defined (Wikipedia): 2

Lack of funding Business requirements not clearly defined 60% - 80% Failure Rate 3 ➞ Lack of user involvement/ownership ➞ No executive sponsorship ➞ Lack of planning ➞ Culture doesn’t value quantitative data ➞ Lack of data understanding ➞ Tackling too much ➞ Benefits not understood ➞ Too complicated ➞ Poor communication ➞ No definition of success ➞ “Forgetting the business”

What business problem(s) are you solving? Why BI? 4

Define the Vision (Success) 5 KPIs are clearly defined and consistent across all functional areas (i.e. the definition of a start is the same for marketing, admissions, operations, finance, etc.) All sources of critical data are documented, and there is a process to collect, transform and normalize the data from various sources, retaining historical data, in order to accommodate reporting and analytics. UTI’s “master data” is defined and managed so that there is only “one version of the truth”. Data marts exist to provide reporting and analytical capabilities for specific business processes and functional areas. These data marts are unioned together to create a comprehensive data warehouse. Users have access to, and are trained to use, various tools to access and analyze data. Business leaders can quickly identify and respond to business changes and opportunities and resources can be leveraged and allocated based on proactive, data driven decisions.

Maturity Model 6

Strategy 7 Exec Support Leadership Technical Expertise Business Champions People Align Deliver Architect Collaborate Process Roadmap Data Warehouse BI Applications Optimization Technology

Initiative leader from the “business”, with strong business and data knowledge Sole focus Champions - worth their weight in gold! BI Readiness – focus on data driven decisions Business/Data Analysts WERE the existing single version of the truth – get them on board early No “analysis” – dumping, scrubbing, compiling data They would validate (or refute) the “success” of the BI initiative. Strong technical expertise to architect for the future Continual progress People “Keys to Success” 8

Align and Deliver! Understand and ensure alignment with organizational strategic priorities Stay connected to your champions and senior leaders Deliver often Don’t wait for someone to ask – offer solutions Deliver what they need, not necessarily what they ask for Progress, not perfection Process “Keys to Success” 9

Collaboration vs Requirements 10 Focus on understanding.... Discovery process Troubleshooting process Decision making process Business process Deliver solutions to support those processes, rather than building a list of requirements and delivering against those.

Foundation Architecture Avoid more chaos – long term vision Performance considerations Data Accuracy/Completeness Sanity – business rules Information (not just data) Dashboards Ad hoc analysis Information delivery Technology “Keys to Success” 11

BI Applications 12 Adoption is key Keep it simple Number of different applications/tools Design Understand what tools best suited to what purpose Keep close to your business partners What are they buying and implementing on their own? Training, training and more training Follow up; new features; power users (create own visualizations) Get creative

Qlikview Dashboard as workflow tool 13

Qlikview Dashboard as workflow tool 14

Results 15 Employment outcomes Focus in FY2012 resulted in improved workflows, visibility, standardized metrics and employment rates Marketing Completely redefined how we measure marketing effectiveness – improved accuracy/visibility Predictive Model In Feb 2013, cancelled contract with external vendor to move to internal model (annual savings approx $200k) Other departments funded BI positions within IT Growth from 2 to 7 team members since 2009 With the right information, can do more with less

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