Flinders demands a new beginning Building a Business Analytics capability using a blended approach with a small team.

Transcription

1 Flinders demands a new beginning Building a Business Analytics capability using a blended approach with a small team. Presenter: Andrea Matulick, Business Analytics Manager Planning Service Unit Office of the Vice-President (Strategy & Planning)

2 Acknowledgements Flinders University David De Bellis Head, Planning Services Unit Luke Rowett Senior Information Analyst (Business Analytics) Ben Stevens Information Analyst (Business Analytics) Bronwyn Simondson Vice-President (Strategy and Planning) (retired) The BA Strategy Altis Consulting - Data Warehouse and BI Shaune Rolfe James Cooper The Pilot 2011 Neodata Australia - Oracle partner Tas Osianlis Gergo Bacskai

3 Presenter s background Adelaide University Data Warehouse Business Analyst Oracle Discoverer, Oracle Warehouse Builder University of South Australia Enterprise Data Warehouse Project Officer Kimball, Oracle Warehouse Builder, Cognos University of South Australia Cognos 8 Migration Project Manager IBM Cognos 8, 600 reports, 60 cubes, 7 business units, 25 developers, 3 yrs Whereis Flinders University? 2012 Flinders University Business Analytics Manager implement BA Strategy and Roadmap Strategic Performance Management Oracle BI Enterprise Edition, ODI, OBIEE, Essbase,

4 Overview Introduction What is Business Analytics? What s included in the Business Analytics Strategy and Roadmap? Roadmap and Streams of Work, Timelines Governance and Resources Requirements from Stakeholders Tool Selection, Infrastructure and Architecture How is the implementation going? Issues Achievements Benefits - are we there yet?

5 Why demand a new beginning? Development of the strategy found: Lack of broad business processes to support strategic reporting around University KPIs Restricted ability for evidence based decision making and managing performance in line with strategic agenda Flinders does not have a centralised BA platform to integrate student, research, admissions, human resources, finance and survey source data Planning Services Unit (PSU) provides significant amount of data to various areas of the University and external stakeholders. Some data comes from other areas e.g. Research, Finance Trend toward evidence based decision making placing an increasing ad-hoc load on the PSU and current approach considered unsustainable Time spent gathering and collating information means reporting is potentially reactive and non-exploratory in nature not much time for analysis

6 What does Building an Analytic Capability mean? A BA platform will facilitate meeting the priorities of the University and significantly benefit Senior Executive, Deans, Managers, and Analysts by: Ensuring alignment between the University s strategic information needs and the Business Analytics capability Enabling generation of insightful information to support strategic analyses Engaging the people and processes to support the delivery of information Getting the business focussed on the same strategic goals Only 5% of employees understand their company's strategy - this makes successful execution nearly impossible Source: Balanced Scorecard, Robert Kaplan and David Norton, 1996

7 What does Building an Analytic Capability look like? To end users? To Senior Management?

8 What does Building an Analytic Capability look like? To Senior Management?

9 Contents of the Strategy: What s in the Roadmap? 1. Executive Summary 2. Stakeholder Requirements 3. Current State assessment -> Future State -> Roadmap Governance Infrastructure Subject Areas Business Analytics and Reporting 4. Benefits Appendicies 1. Approach and Timelines 2. Requirements -> Subject Areas -> Prioritisation -> Phases 3. KPI mapping to Subject Areas

10 Roadmap and Streams of Work

11 Strategy Development 3/11 Timelines SBPF Pilot /11 Tool Selection 5/11 Phase A Strategy Implementation 1/12 Phase CPhase B Phase D to H Complete Stage 1 12/14 ' 11 Mar 2011 Sep Mar 2012 Sep Mar 2013 Sep Mar 2014 Sep ' 15 Today Strategy Dev 30/6/11 Tool Selection 1/5/11 30/8/11 SBPR Pilot /9/11 30/11/11 Strategy Implementation 1/1/12 30/12/14

12 Governance Business Analytics Steering Committee (BASC) Member of Senior Executive as chair and sponsor Main governing body to determine priority of ongoing BA developments Extend the breadth of data and functionality available Business Analytics Competency Group (BACG) Provide advice and recommendations to Steering committee Establish and oversee procedures, standards, data management Provide expertise in Source System applications and databases Business Analytics Team Located in Planning Service Unit (PSU) Works with representatives from BASC, BACG and business units Works with Information Technology team for infrastructure support Set up User Group

13 Resources a small blended team

14 Requirements from Stakeholders Interviews were conducted with key stakeholders across the university A questionnaire was provided by the consultants to elicit the requirements Main consumers were to be the Vice-Chancellor, Executives, Faculties & Schools Vice-Chancellor and President Deputy Vice-Chancellors (Academic, Research, International, Vice Presidents (Strategy & Planning, Strategic Finance and Resources) Pro Vice-Chancellor (Information Services) and CIO Faculty Executive Deans (Health Science, Science and Engineering, Education, Humanities and Law, Social & Behavioural Sciences) Deans of School, Faculty and School Managers Administrative Units (Marketing, Planning, HR, Finance, Research, International, Student, Management Information Systems) A list of Subject Areas was compiled, a prioritisation session was held with the Business Analytics Steering committee to determine relative business impact, relative feasibility of each subject area any interdependence between subject areas

15 Priority Matrix Subject Areas Key Subject Area 1 Admissions 2 Students 3 Student Performance 4 Research Performance 5 HDR Supervision 6 Surveys 7 Space Management 8 Financial Performance 9 HR Performance 10 School-Based Performance Reporting 11 Integrated Load Modelling 12 Mission Based Compacts Equity Analysis 13 Academic Staff Performance 14 Attrition Reporting Framework 15 First Year Analysis 16 Reviews 17 High School Report Card

16 Tool Selection key requirements Highly visual display of scorecards, dashboards, targets Ad-hoc analysis and reporting similar to cubes or pivot tables Drill down, across, through Ability for forecasting and scenario modelling User friendly, Training, Education, Communication facilities Data profiling, data quality, data lineage (metadata) functionality Data integration and ETL functionality, workflow, testing Security, Connectivity, Scalability, Virtualisation, Support Compatible with existing platforms and Flinders standards Cost, Vendor reputation And the winner is... Oracle Business Intelligence Foundation Suite + Oracle Data Integrator 11g, OBIEE, Essbase, SmartView, ODI

17 Infrastructure and Architecture Performance, Scalability, Flexibility, Usability, Reliability

18 Issues: 1. Organisational Structure most systems use different codes and structures 2. History & Culture ownership of data, access to data, identify and confirm key source system data owners and custodians 3. History & Culture lack of business processes to support performance management KPI review and target setting, responsibility and accountability for KPIs 4. Resources especially in the Business Units for defining requirements, confirming business rules, considering and correcting data quality issues, etc. 5. Infrastructure room for improvement 6., 7., 8... Data Quality

19 Achievements so far: Strategy and Roadmap completed and approved see acknowledgements Pilot 2011 School based Performance Reporting dashboard see Luke and Ben s presentation tomorrow ad-hoc analysis, target setting Governance: BASC (Steering Committee) Membership Vice-President, Strategy and Planning (Chair) Vice-President, Strategic Finance and Resources Pro Vice-Chancellor (Information Services) and CIO Data Ownership: Matrix identifies and confirms key source system data owners and custodians and levels of responsibility Organisational Structure: policies are being reviewed and updated BACG (Competency Group) Data Custodians tackling some major issues Regular meetings with Business Units - regarding understanding and use of data, changes over time, known issues etc.

20 Infrastructure: Achievements so far: Data Warehouse central connectivity agreement overnight copies of each major source system made available for the data warehouse to integrate Subject Areas: Majority of work this year has been on establishing business process, liaising with technical staff in the core systems, and developing the ETL processes. Working on dimensional models and expect to have 3 or 4 core models released by the end of the year whilst advancing cubing and reporting mechanisms Data Sources available: DIISRTE data (Load, Enrol), daily loads of SET Survey data, live Student data, live HR data, live Finance data, live Research data Soon to tackle: Load Modelling initially based on current model using Access and Excel Need to do more of: Communication and feedback

21 Building the Analytic Organisation Efficiency stage 1 get current and past performance into the decision makers hands (data warehouse, data quality, metadata, BI presentation) Effectiveness stage 2 analytics becomes a core competency (scorecards, dashboards, alerts, scenario planning, data mining, predictive analysis) Analytical stage 3 the organisation adds value by having analytics serve as a function not just a competency a group of analytic experts lead the adoption of analytics to become part of the culture Source: Building the Analytic Organisation, Peter Graham, 2007

22 Conclusion - Benefits A Business Analytics capability based on our Strategy and Roadmap will facilitate meeting the priorities of the University and significantly benefit Senior Executive, Deans, Managers, and Analysts by providing: Integrated information from key source systems, presented in interactive scorecards and dashboards for monitoring and managing business performance thru carefully chosen KPIs Access to scenario-driven modelling capabilities, allowing strategic what-if analyses to optimise performance Self-service access to information for exploratory ad-hoc analysis to support strategic and tactical decision making Opportunity for staff to be more efficient and add value through analysis of quality information, instead of spending time collecting, correcting, consolidating and manipulating data to produce reports or findings Are we there yet? No, but we know where the road is taking us.