Key Performance Indicators Presented by Cameron Fuller On behalf of Business Intelligence Competency Centre Queensland University of Technology
Presentation Overview Main topics BICC Team Historical and current reporting of KPI s at QUT BICC project for KPI reporting Progress and experiences of KPI project Online presentation of KPI reports
Business Intelligence Competency Centre (BICC) as part of Division of Finance and esource Planning Formed: January 2008 Objective: To deliver a centralised reporting framework for the corporate reporting requirements of QUT The team works in conjunction with the university s data warehouse staff and infrastructure Staff: 2 x Business Intelligence Analysts (Business Objects administrators) Supported Applications: Business Objects XI2 and Enterprise Performance Management
Key Performance Indicators University blueprint defines QUT s broad goals University Blueprint Top level plans underpin the blueprint to set the defined objectives to reach goals Top Level Plans KPI s are the metrics that are created to measure performance of each top level plan
Historically KPI eporting 2005 saw the first round of the quarterly KPI reporting by the Corporate Performance Section to the major university committees. The data supporting these reports was largely produced through the data warehouse in the format of web reports. Continual refinement of the KPI definitions in the early stages made maintenance of data warehouse difficult resulting in a decentralised manual collection process. Collection of KPI s data became dependent on other organisational areas to provide data. The Way Forward for QUT Need for clearly defined KPI Business ules Need to create a centralised reporting framework with the ability to easily adapt to reviews of the KPI process Provide capacity to display KPI data at multiple levels for detailed analysis
Commenced: May 2008 Objective: To centralise KPI reporting into the BICC framework and to build a stable and supported environment for continuing KPI measures using endorsed KPI definitions and consistent calculation methodologies. Major Activities: Identify major KPI stakeholders Create business rules in conjunction with stakeholders Identify the KPI data sources and custodians Develop design and technical specifications for the KPI framework and data collection Undertake ETL process to consolidate KPI data and store KPI values and targets Align online reports with quarterly submissions
Identify major stakeholders Task: Who provides KPI data, what is the data source, what is the reporting process for data Outcomes: Formed the project plan scope of work and the extent of resources required Experiences: Develop relationship with stakeholder and create confidence with stakeholders that the KPI project will increase efficiency of KPI data collection and provide transparency and confidence in data
Create business rules in conjunction with stakeholders and technical staff Task: Develop design and navigation of KPI s, create business rule template and develop data architecture Outcomes: Creation of a KPI template that defined each KPI by three main definition categories 1. Business ule Definition (summary) 2. Technical Definition for data collection and transformation and data warehouse architecture 3. eporting ules: Who, How & When Experiences: ealisation that some university KPI data must be manually collected as no source system exists. How to effectively co-ordinate the cross divisional efforts in achieving an endorsed business rule for each KPI
Develop design and technical specifications for KPI framework Task: Design a reporting framework to support the KPI values. To create a business objects universe and data warehouse design which supports sustainable framework. Outcomes: Collaboration between data warehouse and business objects technical staff Completion of a comprehensive technical specification. Experiences: The technical specification and framework will undergo continual evolution. Having a solid design and technical specifications are critical Critical to ask the question: Is this the most meaningful manner to report the data and Who is my target audience/client
ETL processes and manual and target data Task: To extract data at the granular level required for reporting now, and for drill down Determine what level of reporting is required for each KPI and how manual data can be obtained to facilitate this need Construct an interface to input manual data and to load target values Outcomes: Diverse range of data, recorded at all levels needed to be recorded Use MS Visual Studio to input manual data flat files and target data
Align online reports with quarterly submissions Task: Snapshots of data to reflect the quarterly submissions to committees Outcomes: Create versions that are open for the next due submission, then close that version and retain a snapshot of that data Ensure that data integrity is maintained through comprehensive quality assurance processes of transparent data architecture and that data reported through reports match reports provided on line