"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."
University of Liverpool
BI initiatives are often aimed specifically at improving decision making within the organisation.
However, a positive by-product can also be that such projects find that the implementation of their systems lead directly to improved business processes within the organisation, as demonstrated by the following examples:
1. By making the data available to senior managers in an easy to understand format their engagement with any underlying data quality issues is likely to be automatically increased
The Universities of Liverpool, East London (UEL) and Central Lancashire (UCLan) all developed dashboards to support senior management and inform strategic decision making. By deploying highly graphical displays they hoped that the data would be more readily available to senior managers who would both access it more frequently and base medium to long-term plans on readily available factual data.
In addition UCLan were hoping for a virtuous circle so that by putting in place more efficient and automated data collection mechanisms they would free staff resource for more BI development. Both Liverpool and UCLan discovered that as a result of the project, processes that underpin many of their respective university’s key performance indicators (KPIs) are now much better understood and have been questioned and challenged by senior managers. Consequently the data that is used to compile them had to be shown to be robust and is now trusted by the data users, including senior management.
2. BI can highlight unexpected synergies in an organisation’s areas of expertise
Prior to the University of Glasgow’s project the identification of research clusters had been a manual process either based on personal knowledge or intuition. By providing facilities for collecting the relevant information for this activity the project has given a framework in which this process can be developed and awareness of the potential for interdisciplinary cooperation has been greatly enhanced. This will aid widening the scope of research and support of the University’s stated aim of broadening its research activity.
3. A BI project can highlight inefficiencies in existing systems and processes
For the University of Bolton the key point was to identify where the pinch points were in the processes that were used to gather information for statutory returns and address those. Also, given the volatile environment that the project was working in, they understood that it was important to ensure that the way in which the management structures of the university were represented in the data structures were consistently implemented in a flexible manner that could accommodate changes without major upheaval.
4. Developing BI systems can eliminate periodic ‘stocktaking’ upheavals
Previously, much of the development of the University of Huddersfield’s research system had, understandably, been driven by the Research Excellence Framework. Their BI project will now allow academic managers to routinely monitor progress in key areas, such as publication data, rather than suffer periodic upheavals when the data is gathered for a specific point in time survey. As a result, there is the potential for such reporting requirements to become less disruptive and costly in terms of time and resources and, instead, to become just another facet of ‘business as usual’.
5. BI projects can refine existing data and make it more easily available and understandable
For the University of Bedfordshire the emphasis of the project was on process improvement as they were building on a pre-existing system which was widely perceived to have more potential than it was delivering. By carrying out detailed requirements analysis with the users the project was able to identify which were the most valuable gains and work to implement them. In some ways this project shows the value of incremental development as the users were able to state their needs in the context of existing facilities.
6. The use of predictive models can lead to significant gains in productivity and increased effectiveness
For the Open University (OU) with its very limited face to face contact with its learners, the challenge of detecting changes in student behaviour and interpreting them presents a significant challenge. By analysing past activity on the virtual learning environment (VLE) and matching the behaviour to known outcomes the project was able to develop an innovative predictive model which could be used by university administrators and associate lecturers to make appropriate interventions and reduce attrition. This project was, in part, responsible for a move by the OU towards a larger and wider scoped data warehouse which will provide more extensive business intelligence.