Analysing and Improving Processes


Research related processes obviously have an important effect on the quality and productivity of research. What are the key processes to consider and how can they be improved?


Research processes were considered in a wide context initially and then ones that were particularly relevant to the project’s work identified and concentrated on, with particular emphasis on information related areas. Key issues addressed included:

  • What is the information support provided for research processes?
  • What are the key data needs and how are they met?
  • What systems are used and how reliable are they?

Information about research related processes was obtained partly through the general user requirements work but also through interviews with specific stakeholders. Preliminary analysis based on this was then fed back to special Focus Groups organised for this purpose, which allowed suitable models to be derived and refined.

Important findings about research related processes and the information they were based on were:

  • There was often no universal agreement about master sources of critical data elements. Even when master sources were agreed, processes for ensuring they were up to date and accurate were inadequate.
  • Different data sets often did not include consistent common key fields that could be used to connect the information together.

Data quality was thus a problem with detrimental efficiency and cost consequences. In relation to the work of the Brain project, these issues were apparent in relation to requirements it had identified to answer questions such as: Who knows what?; Who is available to work on opportunities?;  What work can we re-use, or use as a model?;  Where are the documents/ publications relating to a project? Without adequate processes relating to information and other areas, in practice answers to these questions would not be consistent, accurate or sustainable.

Key conclusions drawn from this were:

  • Processes need to be mapped and documented, using models at different levels and building target models for efficient management of data. Research related processes, particularly those associated with data quality and integration, need to be analysed and optimised to enable the provision of reliable information to help create and support communities.
  • The relevant core system issues relating to these processes need to be considered and measures implemented to improve them if necessary. Key areas would include: Identity management – to have consistent and unambiguous information about individuals and their roles and Interoperability and Service Orientation – to have a standards-based infrastructure to support the reliable interchange of data. Based on this underlying framework, core services could provide and maintain accurate and up-to-date information for tools and facilities.

Although the ability of the project to change and improve research related processes was limited, it nevertheless could carry out an analysis and make suggestions. A broad process simplification exercise using a Lean Sigma approach was used. This focused on the overall goals of the processes and sought to eliminate unnecessary or inefficient steps and system components. Where there was conflict, root cause analysis was used to determine what needed to be done to support the goals. A further aim was to identify responsibilities and deliverables and ensure successful handoff between steps and that the necessary flow of information took place.