KPIs and their properties defined with the EXTREME method

Key Performance Indicators (KPIs) are the main instruments of Business Performance Management. KPIs are the measures that are translated to both the strategy and the business process. These measures are often designed for an industry sector with the assumptions about business processes in organizations. However, the assumptions can be too incomplete to guarantee the required properties of KPIs. This raises the need to validate the properties of KPIs prior to their application to performance measurement. This paper applies the method called EXecutable Requirements Engineering Management and Evolution (EXTREME) for validation of the KPI definitions. EXTREME semantically relates the goal modeling, conceptual modeling and protocol modeling techniques into one methodology. The synchronous composition built into protocol modeling enables raceability of goals in protocol models and constructive definitions of a KPI. The application of the method clarifies the meaning of KPI properties and procedures of their assessment and validation.

The business case development process in the delivery of NHS infrastructure

There is a lack of knowledge base in relation to experiences gained and lessons learnt from previously executed National Health Service (NHS) infrastructure projects in the UK. This is in part a feature of one-off construction projects, which typify healthcare infrastructure, and in part due to the absence of a suitable method for conveying such information. The complexity of infrastructure delivery process in the NHS makes the construction of healthcare buildings a formidable task. This is particularly the case for the NHS trusts who have little or no experience of construction projects. To facilitate understanding a most important aspect of the delivery process, which is the preparation of a capital investment proposal; steps taken in developing the business case for an NHS healthcare facility are examined. The context for such examination is provided by the planning process of a healthcare project, studied retrospectively. The process is analysed using a social science based method called ‘building stories’, developed at the University of California-Berkeley. By applying this method, stories or narratives are constructed around the data captured on the case study. The findings indicate that the business case process may be used to justify, rather than identify, trusts’ requirements. The study is useful for UK public sector clients as well as consultants and professionals who aim to participate in the delivery of healthcare infrastructure projects in the UK.

Modelling requirements of supplier selection for benchmarking service provision

Supplier selection has a great impact on supply chain management. The quality of supplier selection also affects profitability of organisations which work in the supply chain. As suppliers can provide variety of services and customers demand higher quality of service provision, the organisation is facing challenges for making the right choice of supplier for the right needs. The existing methods for supplier selection, such as data envelopment analysis (DEA) and analytical hierarchy process (AHP) can automatically perform selection of competitive suppliers and further decide winning supplier(s). However, these methods are not capable of determining the right selection criteria which should be derived from the business strategy. An ontology model described in this paper integrates the strengths of DEA and AHP with new mechanisms which ensure the right supplier to be selected by the right criteria for the right customer's needs.

Integrative workflow-embedded support for process automation and management

This paper presents the on-going research performed in order to integrate process automation and process management support in the context of media production. This has been addressed on the basis of a holistic approach to software engineering applied to media production modelling to ensure design correctness, completeness and effectiveness. The focus of the research and development has been to enhance the metadata management throughout the process in a similar fashion to that achieved in Decision Support Systems (DSS) to facilitate well-grounded business decisions. The paper sets out the aims and objectives and the methodology deployed. The paper describes the solution in some detail and sets out some preliminary conclusions and the planned future work.

Generic unified modelling process for developing semantically rich, dynamic and temporal models

Models play a vital role in supporting a range of activities in numerous domains. We rely on models to support the design, visualisation, analysis and representation of parts of the world around us, and as such significant research effort has been invested into numerous areas of modelling; including support for model semantics, dynamic states and behaviour, temporal data storage and visualisation. Whilst these efforts have increased our capabilities and allowed us to create increasingly powerful software-based models, the process of developing models, supporting tools and /or data structures remains difficult, expensive and error-prone. In this paper we define from literature the key factors in assessing a model’s quality and usefulness: semantic richness, support for dynamic states and object behaviour, temporal data storage and visualisation. We also identify a number of shortcomings in both existing modelling standards and model development processes and propose a unified generic process to guide users through the development of semantically rich, dynamic and temporal models.

Assessing the business risk of technology obsolescence through enterprise modelling

The problem of technology obsolescence in information intensive businesses (software and hardware no longer being supported and replaced by improved and different solutions) and a cost constrained market can severely increase costs and operational, and ultimately reputation risk. Although many businesses recognise technological obsolescence, the pervasive nature of technology often means they have little information to identify the risk and location of pending obsolescence and little money to apply to the solution. This paper presents a low cost structured method to identify obsolete software and the risk of their obsolescence where the structure of a business and its supporting IT resources can be captured, modelled, analysed and the risk to the business of technology obsolescence identified to enable remedial action using qualified obsolescence information. The technique is based on a structured modelling approach using enterprise architecture models and a heatmap algorithm to highlight high risk obsolescent elements. The method has been tested and applied in practice in two consulting studies carried out by Capgemini involving three UK police forces. However the generic technique could be applied to any industry based on plans to improve it using ontology framework methods. This paper contains details of enterprise architecture meta-models and related modelling.