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University of Liverpool - Business Intelligence



Case study written October 2012.






Business case


An initial Business Case and Options Appraisal for the acquisition of a Management Information System was presented to the University’s decision-making body in 2008.  Although approved in principal, the start of the project was deferred until 2010 when approval to commence was obtained from the University’s Planning Group.  The following is the text of a paper presented to the Planning Group that secured approval for work to start on the project.


The following is the text of a paper presented to the University’s Planning Group in April 2010 that secured approval for the Management Information project. 




There is a clear need for the University to transform its management information capacity and capability.  A proposal has been developed to support this objective, enabling significant improvements to support the delivery of the Strategic Plan and the achievement of Institutional Excellence though better and more devolved decision-making and management.


The overall vision of the project is to ensure that leaders and managers across the University have the right management information to undertake their roles effectively. 


It is proposed that the project will take place in two phases:-


Phase 1: Review of capacity, capability and requirements, in terms of people, data and systems


Phase 2: Implementation of specific system solutions, including training and development of people.


The project will achieve a number of key deliverables including:


  • More effective monitoring and analysis of performance against Strategic Plan key ambitions and, hence, more timely intervention as required to ensure overall delivery of University objectives;
  • Providing the right information in real time to key individuals at all levels of the University to support strategic planning and allow evidence based decision making;
  • Supporting devolution of activity by providing managers with appropriate information and tools to support areas of responsibility (such as financial and budget monitoring);
  • Standardised data and data definitions which will ensure more accurate and reliable reporting of data for internal and external purposes (e.g. statutory returns to HESA and HEFCE);
  • Improved efficiencies by removing duplicate activities across areas/ departments, reducing time focused on data collection activities and utilising data from a single, agreed source.  This will then allow greater focus on data analysis, assessment and interpretation.




The University has invested in best of breed information systems but lacked the tools to generate management information in a consistent and accessible way.  The primary strategic product for all reporting was an early version of Business Objects.  In addition some application systems have their own integrated reporting tools and some end user reports are also accessed from an in-house developed portal.  Significant use is made at local level of spreadsheets and databases to extract and merge data from corporate information systems and manipulate it to meet local information requirements.  This raised serious issues in terms of data accuracy and consistency and constituted an obstacle to the goal of having “one version of the truth.”


Because of the shortcomings noted above, there was a lack of consistent, accessible and reliable MI to inform strategic decision-making.

Management Information did not have a high profile in the institution, as evidenced by a lack of prominence or consistency in the way in which MI was reflected in individual’s role descriptions and included in personal development plans.


A number of issues had been identified regarding data, particularly a lack of formal and consistent data definitions and a lack of clarity concerning ownership.


Key drivers


The University has an ambitious 5-year Strategic Plan with Key Performance Indicators requiring accessible management information to monitor progress towards their achievement.


The University has also recently undergone a comprehensive organisational restructuring.  This has resulted in management, planning and financial responsibility and accountability being devolved to three academic Faculties, each having subordinate reporting layers of Schools and Departments and a Professional Services function which collectively comprises the University’s administration and support departments.


The above factors, coupled with developments affecting funding in the Higher Education sector, have placed a strong focus on the need for robust, comprehensive and accessible management information.   


Project approach


The project is being managed according to PRINCE2 methodology and was formally initiated with approval of the Project Initiation Document in September 2010.  Work is being undertaken in two phases as noted in the project mandate.  Phase 1 (Definition and Planning) included the following steps:


  • Internal consultation with stakeholders throughout the University to gain an understanding of current issues and requirements.  This involved a series of one-to-one meetings and workshops using checklists of questions designed to elicit information and opinions from MI users and providers
  •  A review of the approach taken and solutions chosen by other universities, using a purpose-designed questionnaire.
  •  An assessment of the market availability and approximate costs of appropriate software tools and related services.  This was undertaken by issuing a Request for Information to a several supplier organisations.


Phase 1 concluded with a report recommending a programme of work in Phase 2 (Development and Implementation) to address the key findings and lay the ground for the implementation of a technical solution to satisfy the identified need for improved quality and accessibility of management information.  Both full and summary versions of the Phase 1 report were produced to satisfy the needs of different stakeholders.


Following approval of the Phase 1 findings and recommendations, Phase 2 began in January 2011 and is scheduled to continue until 31 May 2012, at which point MI will cease to have “project” status and will become business-as-usual.  A project Working Group was established with formal terms of reference to undertake the various tasks in Phase 2, which comprised the following work streams:


·         Short term improvements

·         Improvements to KPI reporting

·         Data definitions

·         Personnel aspects and creation of the Management Information Competency Centre

·         Procurement and installation of software tools

·         Pilot implementation

·         Roll-out planning


The principal outcomes of each of the above work streams are reported in section 2.


The Working Group comprised representatives from all Faculties, Schools, Institutes and Professional Services Departments.  Sub-groups were created to undertake specific tasks, comprising those who were in a position to effect the improvements and those who would benefit most from the outcome.  Having completed its assigned tasks through to the implementation of the technical solution in the pilot application area, the Working Group was disbanded in December 2011 and ongoing responsibility for the development of MI was assumed by the newly-formed Management Information Competency Centre.   




The scope of MI provision using the data warehouse and dashboard tools will eventually address the reporting needs of the whole University and will be subject to a continuous process of ongoing development and refinement.


For the purposes of the JISC project, the scope comprises the defined Phase 2 activities up to and including:


  • implementation of the technical solution in the pilot application areas
  • a period of assessment and appraisal, including presentations and demonstrations to key stakeholders to gather feedback and take on board lessons learned
  • definition of priorities for the roll-out programme




A robust governance structure was put in place at the beginning of the project.  This was subject to slight modification as the project progressed, e.g. changes in membership of oversight bodies, creation of the MICC, etc.  The current governance structure appears in this chart.  


Technologies and standards used


The technical solution comprises the following software tools from the SAP Business Objects product suite:


·         Data Integrator data warehouse and ETL (Extract, Transform, Load) tools

·         Xcelsius dashboard development tools

·         Explorer search and exploration tool

·         Business Objects Widgets


The software tools were specified to be enterprise scalable, web based and conforming to recognised industry standards for deployment and architecture.  The following are the relevant technical standards in place in the University:


  • XML – Preferred method of data exchange
  • PDF – Preferred method of static report distribution
  • WSDL – Web services description language; a machine-readable descriptor of web service metadata. This is a component of SAP Business Objects Data Services Integration as well as a standard in general use for web services
  • SOAP – Communication protocol
  • Flash – Multimedia platform to add animation, video and interactivity to web pages


Establishing and maintaining senior management buy-in


Senior management buy-in and support has been vital to the success of the project.  This has been established and maintained in a number of ways:


  • The approval of the initial Business Case by the Business & Information Systems Committee
  • Approval to initiate the project from the University’s Planning Group
  • The Governance Structure includes the prominent involvement of senior Academic and Professional Services staff in the oversight and direction of the project
  • Senior Academic and Professional Services stakeholders were included in the detailed consultation and requirements gathering exercise in Phase 1 of the project
  • The outputs from the project, particularly the newly-designed dashboards, are presented to senior management from all parts of the University and their feedback is taken into account when finalising the content and design
  • MI project progress reports are included as a standing item on the agenda of the University’s principal decision-making and oversight bodies




The following is an assessment of the outcomes of the project in the context of the BI implementation issues.


Process improvement


Process improvement is a discrete work stream in the project.  The aim is to ensure that processes are optimised in order that maximum advantage can be taken of the new technology that underpins the delivery of efficient and effective management information.  This work stream is being undertaken by the University’s Process Improvement Programme Manager.  The work began with analysing the processes associated with producing the University’s quarterly Planning & Performance reports, with particular emphasis on research income, as this was part of the MI pilot application.  The principal outcome of this exercise was a greater understanding of the flow of research income data and the number and nature of manual interventions required to convert the raw data into useable MI.  As a result, process improvements have been put in place to reduce the requirement for manual adjustments and to automate the creation of certain MI reports using the functionality of the newly-acquired software tools.


The process improvement programme will continue in parallel with the development and implementation of dashboards for additional application areas, beginning with student data.


System implementation


The analysis of requirements undertaken in Phase 1 strongly indicated the need for a technical solution comprising a data warehouse to serve as a repository of data required for MI reporting and dashboards to display information in a variety of formats.  Information on products available on the market and their indicative prices was obtained by issuing a Request for Information to several known suppliers. Concurrently, research was undertaken into the solutions adopted by other universities.  At the end of this exercise, the decision was taken to procure a solution based on the SAP Business Objects product suite.  The rationale for this decision was based on a combination of feedback from other universities, the strong user base of SAP Business Objects products in the Higher Education sector and the fact that the University is an existing Business Objects customer. 


The procurement of the technical solution was divided into two parts.  The data warehouse tools to extract, transform and load data from existing sources into the data warehouse were purchased from one of the University’s existing Business Objects suppliers, IT Performs Ltd.  Technical training was provided and implementation commenced in May 2011.


Procurement of the dashboard tools was managed by competition between known SAP Business Objects re-sellers.  Four such companies were issued with an Invitation to Tender and technical specification, which set out the essential and desirable features of the required solution and provided relevant background information, including the technical environment.  Those tendering were also required to state their approach to working in partnership for the provision of services including training, implementation support and knowledge transfer.  Four companies were invited to tender.  Two companies declined, one citing other commitments and the other expressing concerns about their perception of the adequacy of the budget.


Tenders were received from two suppliers, IT Performs Ltd and Maven Solutions Ltd. Evaluation was a two-stage process.  Written tenders and responses to the requirements in the Functional Specification were evaluated by the project management team.  The suppliers were also required to formally present their proposals and these were evaluated against pre-established criteria by members of the Core Project Team and Working Group.  The outcome of the evaluation was the appointment of Maven Solutions to supply a suite of products and services comprising:


·         “Xcelsius” dashboard design tools and interactive viewer

·         “Explorer” search and exploration tool

·         “Live Office” Microsoft embedded data access tool

·         Training and implementation support


Contracts were signed and work began with Maven in September 2011. 


It was agreed that the initial application for the dashboards, to be implemented on a pilot basis, would be research-related statistics within the Faculty of Health & Life Sciences.  The first pilot dashboards were developed and presented to the Pilot Implementation Planning Group in November 2011. 


Training in Xcelsius dashboard development was provided to 12 University nominees during November and December 2011.


Dashboard development is proceeding according to a roll-out programme involving additional research-related dashboards and a range of dashboards relating to student statistics.  For every report that is considered for dashboard development, proforma Requirements SheetsData Dictionary Forms must be completed by the requester and ratified by Computing Services. 


Change management


The focus of the change management work stream is on the “development of people” objective in the Business Case.  This is aimed at ensuring that roles and responsibilities in respect of management information are appropriately reflected in Job Descriptions and included in personal development plans.  The first step to achieving this was to review the Job Descriptions of individuals in all Faculties, Schools and Professional Services Departments whose roles involved a focus on MI, either as user or provider.  The wording of clauses reflecting MI-related responsibilities was assessed and where appropriate, additional standard clauses were recommended at the level of either MI Lead or MI User/Provider.  These proposed changes were reviewed and agreed with Human Resources and the line managers of the employees concerned.


It was recommended in Phase 1 that a Management Information Competency Centre (MICC) be created as a virtual cross-functional team with defined tasks, roles and responsibilities for supporting and promoting the effective use of management information across the University.  It was recommended that the MICC should consist of individuals who were identified as having lead MI responsibility following the review of Job Descriptions.  The recommended nominations were agreed with the respective heads of department, as a result of which approximately 35 individuals were confirmed as MICC members, comprising at least one person from each Faculty, School and Professional Services Department. 


The MICC officially came into being at its first meeting on 6 December 2011, at which point the project Working Group was disbanded.  Approximately two thirds of membership of the MICC are former members of the Working Group, thereby providing a good balance between continuity and fresh ideas.


The terms of reference for the MICC were drawn up in consultation with the membership.


Data usage


Prior to the MI project, the University possessed a wealth of data but lacked the tools and processes to convert raw data into useful management information.  The creation of the data warehouse has facilitated the integration of data across existing business systems to a consistent set of definitions and standards.  Data dictionaries have been created which capture the data definitions, data owners, frequency of reporting, etc., and these are used as the basis for building the data warehouse. 


From the common information layer provided by the data warehouse, other tools can be made available to users to access and analyse the data to meet their needs. These include dashboard tools and drill reporting tools, which have been acquired as part of the project, and a planning tool, the acquisition and integration of which is a longer term aim. 


As well as providing a foundation upon which management information can be generated and displayed to users, the structured approach to data usage that the project has engendered has a number of additional benefits, including:


  • Ensuring that the same data sources are used for the same reports, thereby supporting the objective of having “one version of the truth” and consistency of data definitions and locations for all reporting throughout the University
  • Identifying the relative usefulness of data currently maintained to serve as a basis for possible future rationalisation
  • Identifying where additional data is needed to meet current and future reporting requirements


Data definition and management


Implementation of the data warehouse and dashboards has necessitated a stringent approach to data definitions and management.  This begins with the completion of Data Requirements Sheets and Data Dictionary Forms as noted above.  The former sets out details of the reason why the report is required, stakeholder information, ownership, etc.  The latter itemises each item of data contained in the report, its description and relevant additional information including source and quality assurance methodology.


Maturity exemplars


As part of the project, periodic soundings are taken to assess the University’s evolving position on the BI Maturity Model.  At the inception of the Development and Implementation Phase at the beginning of 2011, the University was largely in a position corresponding to Stage 1, in terms defined under “context” above.  As the project has progressed, the University has moved up through the stages and now has comparatively little evidence of Stage 1.  The maturity status currently sits in levels 2, 3 and 4 with the beginnings of encroachment into Level 5 as the new MI environment is rolled out.  The following are examples of where the BI implementation issues have been successfully applied to support the University’s transition into the higher maturity levels.


Process improvement:


Has supported the transition into Stage 2 by:


·         Making staff aware of their responsibilities regarding data

·         Encouraging the use of central systems by developing processes that maximise the use of their reporting capabilities


Is beginning to support transition into Stages 4 and 5 by:


·         Developing processes that facilitate access to MI

·         Identifying opportunities for increased automation to reduce manual intervention


System implementation


The acquisition and implementation of the technical solution fulfills the University’s positioning in Stage 3 (as defined by JISC InfoNet) and underpins the transition into levels 4 and 5 via the system roll-out programme.  It also retrospectively supports the University’s positioning in Stage 2 by:


·         Making better use of corporate systems and their data (having taken the decision not to replace them)

·         Drawing data from central systems to ensure a single version of “the truth”


Change management


Has supported the transition into Stage 2 by:


·         Building and implementing a governance structure

·         Embedding clauses in Job Descriptions of relevant staff members to reflect their roles in relation to MI


Is supporting the transition to the higher levels of the maturity model via the creation of a Management Information Competency Centre as the vehicle for the ongoing promotion and development of MI. 




Data usage, definition and management are inter-related topics that have been and continue to be addressed as a pre-requisite to the implementation of MI dashboards. Improvements in these aspects of data have supported the University’s journey through the maturity levels in the following ways:


Stage 2


  • Clarification of responsibilities and ownership of data

  • Identifying and addressing data quality issues


Stages 3 and 4


Ensuring that data requirements for each set of MI dashboard reports are correctly defined and that data is of the required quality

Developing automated links to appropriate data sources and performing extract, transform and load operations to consolidate the data in the data warehouse for dashboard reporting


Other outcomes


Short term improvements


A review of requirements and issues undertaken during the Phase 1 consultation exercise identified a total of 15 items as targets for short-term improvement in that they were potentially worth doing, did not involve disproportionate effort and did not require the technical solution to be in place.  Two short term improvements were withdrawn when it was determined that the requirements could only be met when the technical solution was in place.  The remaining improvements have been put in place and include:


·           A portal showing what information is available and how to access it

·           An on-line resource explaining what the various information systems do and how to access training

·           Information on research performance with comparison of costs against income

·           An expansion of the information available through the HR dashboard to meet additional reporting needs identified by the Faculties

·           A monthly snapshot of student census data


Key Performance Indicators 


The Key Performance Indicators reflect the 12 Key Ambitions in the University’s Strategic Plan.  Some of the Key Ambitions have more than one KPI measure, resulting in a total of 16 KPIs for the purposes of this exercise.  For each KPI, a number of potential obstacles to accurate reporting were identified.  Satisfactory completion has been achieved on most KPI-related issues including:


·         Capturing data on staff on overseas placements and exchanges

·         More detailed reporting on the proportion of taught and research post graduate students

·         Development of targets for student satisfaction levels

·         Improved reporting of the market share of student applications

·         Agreement on a number of data definitions, including student retention and progression


The remaining KPI issues are being taken forward through the Management Information Competency Centre.


report detailing the status of both the Short Term Improvements and KPI work streams was prepared at the end of 2011.


Access and visualisation




Simplifying access to Management Information is at the core of the project, and involved several streams including:

·         Development of the MI web site to focus on the project outcomes

·         Development of an MI portal, ensuring  a single point of access to key information

·         Development of interactive dashboards to reduce reliance on heavy static documents such as excel spreadsheets and PDFs


Website Development 


As dashboards are being developed in line with the University’s 5-year Strategic Plan, we aimed to ensure that the links were obvious at all levels.  The website used graphics from the plan to act as links to the key areas being reported on.




From the website, end users are able to navigate directly to the plan, or to the different dashboard documentation and links.


MI Portal


As accessibility will inevitably be bound by confidentiality issues, we needed to host the dashboards on a platform where we could most easily control this.  Our existing staff portal ‘TULIP’ (The University of Liverpool Information Portal) was deemed to be most appropriate. A section was developed within TULIP to allow easy access to dashboards.  The menu system within TULIP was written to reflect the key areas of the Strategic Plan, thus maintaining continuity.


Visualisation of Data




Making information accessible was at the heart of the project.   Use of Xcelsius to develop performance monitoring dashboards which allowed users to change the view of the data to their preferred style was vital to this element.  In the two diagrams below the same information is displayed in different formats depending on the selected view:



Interactive features were introduced, such as dials to show how much growth is required to achieve performance targets.



Dashboards were developed after extensive consultation to ensure the highest impact at all levels.  Access to the current dashboards within the University is open to all staff who can access TULIP.  Their use is widespread within the University including the following key uses:


·         At Department Meetings with Heads of Departments and senior staff to monitor performance against targets

·         At all levels to help inform the University’s 3-year planning processes

·         For quarterly reports to Senior Management within the University (replacing previously word heavy reports)


Current dashboards include:


·         Research Income

·         Research Applications and Awards

·         Student Population Analysis

·         Conversion Rates

·         Students on overseas placements

·         Student Satisfaction Levels






For key milestones in the University calendar, desktop widgets are being developed to allow managers to monitor rapidly-changing statistics.  These mini dashboards are accessed through an icon on the desktop that provides the user with an instant display of automatically refreshed data in a topic area relevant to their area of interest. The first desktop widget has been developed to monitor undergraduate conversion rates for 2013 entry.



As with the dashboards, the data on the widget is refreshed regularly throughout the day, giving Managers the most up to date information on progress without having to leave their desk.




One of the complaints within the University prior to the project was the need for key users to go through many departments to gather the information they needed to do their job.  To ease individual reporting of this level, the University has introduced the SAP Business Objects product ‘Explorer’.


Explorer is a drag and drop reporting tool which shows key sets of information within an easy to use graphical interface. 


Each Explorer space concentrates on a key information topic from the Data Warehouse.  For example, in the view above we are looking at responses to the NSS survey within one Faculty.  Users are able to look at responses at three organisational levels simply by changing the view on the screen. 





Diverse data sources


The project did not impact on the main business systems within the University but recognised that data from each system needed to be combined to create a fuller picture for reporting purposes.  For example, previously reports on financial systems were delivered separately from research activity reports.  This resulted in large elements of manual intervention to deliver quarterly reports within the University, while Faculty Heads often felt that this key performance information was too complex to use effectively.


By using SAP Business Objects Data Services, data has been pulled to a central data warehouse from all major university systems:


·         AGRESSO (Finance System)

·         IRIS (Research Information System)

·         JASPER (HR System)

·         SPIDER (Student System)

·         Spreadsheets (Target Information)



In the workflow shown above, data is being pulled from AGRESSO, IRIS and JASPER into common tables within the data warehouse.   These data jobs are scheduled to run depending on the frequency of expected data update within the live systems.  For example the finance data is run quarterly in line with the University’s financial reporting periods, while HR data is run daily.


The University information strategy over previous years stood the project in good stead for bringing together data systems, as common codes were used throughout the systems.   This meant that table linking through Data Services was simple and allowed developers time to consider wider issues such as building complex data rules into the system.  A key example of this involved calculation of staff FTE in line with HESA rules.  Previously this was calculated annually for the HESA return, but made it complex for the University to predict performance on this measure.  Within Data Services developers wrote a procedure to take a view of the likely annual FTE figure based on current staff, and staff who had left within the year. 


Benefits (tangible)


The tangible benefits from the project can be categorised according to the three target improvement areas (people, data and systems) and summarised as follows.




Individuals have been identified in all Faculties, Schools/Institutes and Professional Services Departments whose roles include responsibility for MI.  With agreement from management and HR, these employees have had their MI responsibilities formalised by:


·         The addition of new standard clauses in their Job Descriptions at two levels: 

o   MI Lead

o   MI User/provider 

·         Inclusion of MI as a topic in personal development reviews


Employees having lead MI responsibility have been nominated as members of the virtual Management Information Competency Centre, thus ensuring that their MI knowledge and skills will be applied and developed for the benefit both of the University and their own professional development.


The previous fragmented knowledge and skill base in the application of MI tools and the provision of MI reports is being formalised by ensuring that individuals in provider and user departments receive training in the skills to use the new software tools.  In addition, information on what the various systems do and how to receive training in their use has been widely publicised.




The nature and extent of issues associated with the University’s data have been recognised and quantified.  Steps are being taken to ensure consistency and accuracy of data definitions and agreement on ownership and stewardship.  Formalised procedures, using standard proforma, have been developed and implemented for capturing data requirements and definitions for all reporting requirements.




The University’s requirements for a technical solution to its MI requirements have been met by the procurement and implementation of the following SAP Business Objects products:


·         Data Integrator data warehouse and ETL (Extract, Transform, Load) tools

·         Xcelsius dashboard development tools

·         Explorer search and exploration tool

·         Business Objects Widgets


These tools have been procured through a partnership arrangement with a competent local supplier who has also provided implementation support, training and knowledge transfer to allow Computing Services staff to become self-sufficient in building the data warehouse and creating dashboards.


Benefits (intangible)


A major intangible benefit from LUMIS has been to elevate the status and profile of management information from a side issue to a driving force behind the achievement of the University’s ambitions. 


The outputs from the project have begun to create a sense of community amongst Professional Services personnel by bringing them together in a way and in fora that would not previously have existed.


The availability of MI tools to selected users has enhanced their job satisfaction and created a more positive attitude towards MI. 


The outcomes of the project and the next steps are also shown through a short video, which can be accessed from the link below;




Key lessons learned 




The significance of data, particular data definitions, as a factor in the project was first identified in Phase 1.  During the consultation exercise, lack of common and consistent definitions emerged as the most frequently raised problem.  The original approach to tackling this issue was to create a “data improvement” work stream in which members of the project Working Group would be assigned the task of defining the data required for a particular report and creating the data dictionary.  This proved difficult to implement, largely due to the Working Group members having other work priorities and being inexperienced in tasks of this nature.  It was therefore decided to change the approach from running a blanket data improvement work stream to tackling data issues on a piecemeal basis in tandem with the development of individual dashboards, managed by Computing Services in consultation with relevant stakeholders.  However, in applying this approach for the pilot dashboards, it was found that significantly more iterations than expected were required in order to achieve consensus agreement on data definitions.


Lesson 1:  Recognise the limitations of inexperienced individuals with other work commitments when assigning relatively complex or specialised project tasks


Lesson 2:  Do not underestimate the work involved and time required to achieve agreement on data definitions


Lesson 3:  Identify a small number of key individuals to agree data definitions rather than attempting to reach agreement through wide consultation




The proposal to amend Job Descriptions to include MI-related clauses caused disquiet to some individuals who perceived it more as a fundamental change to their roles than a move to standardise and raise the profile of the way that MI-related responsibilities are described.  Plans to create the MICC also caused concern to individuals who wrongly believed that it was a new organisation unit to which they were to be assigned.


Lesson 4:  Sensitivity is required in dealing with matters relating to employees’ Job Descriptions and there is a need for several layers of consultation and approval prior to implementing changes.


Lesson 5:  Ensure that plans that affect or could be perceived as affecting employees’ jobs are communicated accurately and thoroughly, attempting where possible to preempt any misunderstandings. 




It was initially believed that a full EU procurement exercise would be necessary and plans were made accordingly.  However, it was later determined that, due to the strength and fit of the Business Objects product suite and the fact that the University is an existing Business Objects user, procurement could be simplified by purchasing partly from an existing supplier and partly by competition between Business Objects re-sellers, while remaining within procurement regulations.  This change of approach resulted in nugatory work in terms of drafting unneeded EU procurement documents and although no delay was caused to the project, the opportunity for accelerating the process was lost.


Lesson 6:  Decide the procurement route as early as possible in the project to avoid uncertainty at a critical time and possible loss of momentum. 




Because of the data issues noted above, there was pressure to produce the first pilot dashboards within the planned timescale.  As a result, dashboards were being developed while the underlying data issues were still being resolved.  This resulted in the need for a number of iterations before the dashboards were finalised, requiring extra input and flexibility from the supplier, with associated cost implications.


Lesson 7:  Do not begin work on dashboard development before the reports feeding the data are signed off as final.


Lesson 8:  Do not underestimate the time required for building both a data warehouse and a dashboard, especially early in the project and low on the learning curve.




The project has benefited from buy-in and support from the highest levels within the University.  This has been assured partly by the existence of a robust governance structure which involved senior Academic and Professional Services staff in the oversight and direction of the project. The views and input from senior staff have also been actively sought in all stages of the project including the stakeholder consultation exercise and demonstration of prototype dashboards.  


Lesson 9:  Invest sufficient time at the start of the project to create a strong governance structure that includes oversight by appropriate bodies including representatives at the most senior levels.


Lesson 10:  Maintain senior-level engagement by inclusion in consultation exercises and evaluation of project outputs


Stakeholder engagement


The creation of a numerically large project Working Group with representation from across the University in place of a Consultation Group, as originally planned, was a positive step.  It ensured that no parts of the University could feel that they were excluded from appropriate involvement and it facilitated the allocation of tasks in the project to individuals who were best placed to undertake them.  It also facilitated internal communications by serving as a pan-University knowledge base of progress and developments on the project.  The Working Group was formally noted as a good example of cross-University working.  Following the cessation of the Working Group, the approach was perpetuated with the creation of the MICC.


Lesson 11:  Where relevant, consider the benefits of creating a large and representative pool of users to undertake specific project roles and to support the project’s communications activities.


Looking ahead




Although the MI “project” will officially conclude at around the time of submitting this case study, MI will continue to develop within the University indefinitely.  To ensure that this takes place, sustainability has been built into the provision and development of MI by means of the following:


  • The appointment of dedicated Business Intelligence Specialists in the University’s Computing Services Department
  • The creation of the Management Information Competency Centre as a permanent virtual network of individuals within the University to function as the primary agent for MI development and a centre of MI excellence
  • Maintenance of the knowledge base and skill set of the key providers of MI both within the specialist technical functions and the wider user community
  • Ongoing partnership with a competent, specialist supplier to ensure that the technical solution is future proofed against changes and developments in the underpinning technology


Future plans (practical and “blue skies” opportunities)


The implementation of dashboard reporting in the initial application areas is the first step on a journey that will ultimately result in this kind of reporting becoming available for all relevant application areas throughout the University.  Part of the remit of the MICC is to identify and bring to fruition opportunities for new dashboard development as well as improvements in existing provision.  This will include taking soundings of emerging requirements within the institution as well as maintaining an awareness of developments and opportunities within the sector and the industry.


Summary and reflection


LUMIS was an ambitious project, as reflected in the scope of its principal objective:


“to ensure that leaders and managers across the University have the right management information to undertake their roles effectively”


Not only is the ultimate solution intended to be implemented widely throughout the University, but the multi-faceted focus on people, data and systems has introduced a high degree of complexity. 


Thanks to invaluable support from the highest level and the enthusiastic contribution of the Working Group, the project addressed all the actions that needed to be accomplished leading up to its long-standing commitment to having “something to show” (i.e. the first dashboards) by the end of 2011.  Many valuable lessons were learned along the way, particularly not to underestimate issues associated with data. 


Interaction with JISC and with other universities in the BI programme proved to be an interesting and worthwhile aspect of the project.  Although more such interaction would have been welcome it is acknowledged that these activities need to be accommodated within individuals’ day jobs.


At the end of the project stage of our MI work, the project team is gratified by the enthusiastic response to the new dashboards that has been forthcoming from everyone who has seen them.  We are also acutely aware of the task that lies ahead in making dashboard reporting available throughout the University.  To prevent the project becoming a victim of its own success, expectation management will be essential.