Wilkerson- Business Intelligence.pptx
Transcription
Wilkerson- Business Intelligence.pptx
From Data to Insight: The Value of Business Intelligence at ORNL Ramie Wilkerson Institutional Planning and Performance Management Business Planning and Process Improvement November 2012 A strong assurance system… – demonstrates responsible and accountable leadership – sets clear expectations – promotes the right behaviors – focuses on outcomes – manages risk appropriately – executes reliable operations – pursues continual improvement – communicates openly with transparency – strengthens “ Shared Learning” 2 Managed by UT-Battelle for the U.S. Department of Energy S&T Committee_1105 Business Analytics: Understanding performance data is critical What will happen next? What should we do? Improving performance INTELLIGENCE Why did it happen? INSIGHT What does it mean? INFORMATION What happened? DATA Value Extracted from Information 3 Managed by UT-Battelle for the U.S. Department of Energy S&T Committee_1105 Business Intelligence … Communicating performance information thru analysis and visualization • Enables analysis and decision making • Facilitates understanding and communication of performance • Fosters a culture of transparency, learning and continuous improvement 4 Managed by UT-Battelle for the U.S. Department of Energy S&T Committee_1105 What makes up Business Intelligence? Data Reports: how data is communicated Data Warehouse: how data is stored Criteria • Zero Learning Curve – Simple, intuitive structure Data Cubes: how data is organized User Interface: how data is accessed • Select critical key performance indicators thoughtfully – What indicators best measure the health of the lab? Critical Components Data Analytics: how data is analyzed – Easy to Navigate Data Visualization: how data is displayed • Data Integrity – Is the data complete? validated? data owner identified? • Standard layouts to best display data patterns, trends, outliers, etc • User training to use tools efficiently for data analysis • Gather feedback from user community 5 Managed by UT-Battelle for the U.S. Department of Energy Presentation_name What are we trying to achieve? • Create an asset of value § Assists R&D and Support staff in getting their job done § Assists leadership in “managing” the laboratory • Offer capability to view, monitor and interact with performance data § § § § Central portal to access information “Standard” way to view data Central data warehouse Way to view data from iPad to the Desktop to the Big Screen • Provide tools to functional owners to enhance data analysis § Capability to interact with data § “Standard” way to extract data from various data sources § User training 6 Managed by UT-Battelle for the U.S. Department of Energy S&T Committee_1105 Overview 2010: Chose Microsoft BI tool • • • 7 2011: OIP BI Project Lab-‐wide interest in BI • Develop requirements for capability; 9 Directorates SNS User Facility Dashboard Market Analysis of • Developed prototype in industry leaders in Business Intelligence QA – SAP; Microso@; • Lessons Learned: Oracle – Management support Microso@ selected – IdenBfy how these tool – BI suite opBmal for can/will be used by the ORNL environment InsBtuBon – Excel is the – Partnership between foundaBon for user project team and data interacBon with the owners/business data analysts – Training on tool and technical processes needed Managed by UT-Battelle for the U.S. Department of Energy Presentation_name 2012: Project endorsed • • • • • FY12 operaBonal focus: Enhancing funcBonal support for R&D – enabling informaBon systems Challenge: Reproduce current KPIs using BI tool Proof of concept presented to OperaBons Council Endorsement to begin project Learning begins… Benchmarking…continuing to learn • National laboratories • Universities • Private Industry • Users Groups Business Intelligence Users Group (Local) 8 Managed by UT-Battelle for the U.S. Department of Energy Presentation_name NaBonal Laboratory InformaBon Technology Getting started… Resources Technical: 1.5 FTEs FuncBonal: 1 FTEs Cost of Entry: Hardware Ini/al challenges…a few • • • • • • • • 9 Establishing technical and funcBonal processes Learning Curve of tools for project team and user community Buy-‐in from organizaBons – Value Thoughbul selecBon of key performance indicators Data Sources varied – “MeeBng data owners where they are” Speed of delivery SharePoint 2010 MigraBon – troubleshooBng MulBple phase project Managed by UT-Battelle for the U.S. Department of Energy Presentation_name Phased approach – statistics to date… FY10 FY11 FY12 FY13 FY14 Institutional Interest BI OIP Project Project Phase 1 Project Phase 2 Master Data Warehouse • Procedures to extract data: 110 • Data staging tables: 338 • Fact tables (Measures): 199 • Dimension tables (Ways to view measures): 314 • Cubes (computer mechanisms to interact with MDW): 21 10 Managed by UT-Battelle for the U.S. Department of Energy Dashboards • S&T Performance Areas: 5 • Operations Performance Areas: 14 • Data Sources: 49 • Metrics visualized: 152 • Functional Owners: 17 • Business Analysts: 29 S&T Committee_1105 Technology 11 Managed by UT-Battelle for the U.S. Department of Energy S&T Committee_1105 Process Data sources Collect data Data staging Data warehouse Deliver data Data analysis Data reports Extract Transfer Load Internal External Desktop 12 Security Managed by UT-Battelle for the U.S. Department of Energy Normalize and consolidate data Central repository Presentation_name Charts Drilldown Graphs Comparisons Scorecards Slice and CombinaBon dice of data Dashboards Reports Scorecards Workbooks Structure 13 Managed by UT-Battelle for the U.S. Department of Energy Presentation_name Demonstration 14 Managed by UT-Battelle for the U.S. Department of Energy S&T Committee_1105 Planned improvements 15 Managed by UT-Battelle for the U.S. Department of Energy User Interface new design; better functions S&T Committee_1105 Planned improvements 16 Managed by UT-Battelle for the U.S. Department of Energy Visualization and Data Interaction right tools; user training S&T Committee_1105 Excel Power Pivot Power View IT Advisory Council AIM Project: [Business Intelligence - CMPS] Project Status Definitions Green = No significant issues jeopardize the project Yellow = Significant risk to schedule and budget Red = Clear roadblocks prevent successful completion Objectives! Date: 11/29/2012 State the primary technical objectives of the project." Establish a master data warehouse" Project Status: Green Build data cubes of functional areas" Delivery of Information" User/Data Interaction" Stakeholders " Project Sponsor: Jeff Smith" Functional Project Manager: Ramie Wilkerson" IT Technical Lead: Rick Short" MSO Advisor: Shaun Gleason/Mike Baker " " " "" Phase 2: 10/1/12 – 3/15/13 Milestone ! 1. User Facilities 2. Information Security" 3. Publications" 4. High Hazard" " 5. Worker Safety" 6. Environmental Stewardship " 7. Human Resources" " !Orig.! Timeline Completion! Rev. Actual !! "10/1/12" 10/2/12 " 10/31/12 11/26/12 " 12/21/12 "1/4/13 " 1/11/13 " On Track At Risk Off Track 11/29/12" 12/3/12 "" 12/24/12" "1/23/13 2/8/13"" 2/21/13 Planned Duration Progress 3/15/13 1Q13! 17 Managed by UT-Battelle for the U.S. Department of Energy Not Started On Hold Completed 2Q12! 2Q13! S&T Committee_1105 3Q13! 4Q13! IT Advisory Council AIM Project: [Business Intelligence - CMPS] Accomplishments to Date" Issues/Risks" Changes" List major tasks/accomplishments that have been completed and/or milestones achieved since the last status was prepared..! List key issues and/or risks that may affect the project budget, schedule or general objectives. ! Describe any changes to the project objectives, schedule, budget or any other aspects that have significantly impacted the project over the past month. Also documents major baseline changes.! " Established processes: technical and functional" Stats to date: see below " CMPS – In production but not deployed" Institutional support and buy-in " Learning curve of tools" Selection of KPIs" User/Data interaction – training needed" " " Master Data Warehouse! • Procedures to extract data: 110 " • Data staging tables: 338 " • Fact tables (Measures): 199 " • Dimension tables (Ways to view measures): 314 " • Cubes (computer mechanisms to interact with MDW): 21" Dashboards! • S&T Performance Areas: 5" • Operations Performance Areas: 14" • Data Sources: 49" • Metrics visualized: 152" • Functional Owners: 17" • Business Analysts: 29" Cost! " Budget: " Spent: " %Budget Spent: "%Project Period Complete: " " 18 Managed by UT-Battelle for the U.S. Department of Energy S&T Committee_1105 "$175K" "$37K" "21%" "30%"