Luigi Buglione

A multidimensional performance model for consolidating balanced scorecards

A Balanced Scorecard (BSC) presents the quantitative goals selected from multiple perspectives for implementing the organizational strategy and vision. However, in most current BSC frameworks, including those developed for the Information and Communication Technology field, each perspective is handled separately. None of these perspectives is integrated automatically into a consolidated view, and so these frameworks do not tackle, either in relative or in absolute terms, the contribution of each goal to the whole BSC. Here, this issue is highlighted, candidate consolidation techniques are reviewed and the preferred technique, the QEST model, is selected; more specifically, three options are presented for incorporating the QEST model into a BSC framework.

QEST nD: n-dimensional extension and generalisation of a software performance measurement model

Abstract Process and product measurement is one of the key topics in the Software Engineering field. There already exists a significant number of one-dimensional (1D) models of performance, which integrate all individual measurements into a single performance index. However, these types of models are too over-simplified to adequately reflect the multi-dimensional nature of performance. Similarly, 1D models do not meet the analytical requirements of management when various ‘viewpoints’ must be taken into account simultaneously. This papers proposes a multi-dimensional measurement model capable of handling, concurrently, distinct but related areas of interest, each representing a dimension of performance. The proposed model is based on an open model called Quality factor+Economic, Social and Technical dimensions (QEST) which had been developed to handle, simultaneously and concurrently, a three-dimensional perspective of performance: • economic dimension—the perspective of managers; • social dimension—the perspective of users; • technical dimension—the perspective of developers. nA more generic form of this model has been developed to handle a greater number of perspectives, as required by, for instance, several Performance Management frameworks such as the Balanced Scorecard, the Intangible Asset Monitor and the Skandia Navigator. This paper presents the generic form derived from the QEST model, referred to as QEST nD, with the ability to handle n possible dimensions. The generic model is also verified for the particular case of three dimensions using sample data previously applied to the original QEST software performance model.

Improvement Opportunities and Suggestions for Benchmarking

During the past 10 years, the amount of effort put on setting up benchmarking repositories has considerably increased at the organizational, national and even at international levels to help software managers to determine the performance of software activities and to make better software estimates. This has enabled a number of studies with an emphasis on the relationship between software product size, effort and cost drivers in order to either measure the average performance for similar software projects or to develop estimation models and then refine them using the collected data. However, despite these efforts, none of those methods are yet deemed to be universally applicable and there is still no agreement on which cost drivers are significant in the estimation process. This study discusses some of the possible reasons why in software engineering, practitioners and researchers have not yet been able to come up with reasonable and well quantified relationships between effort and cost drivers although considerable amounts of data on software projects have been collected. An improved classification of application types in benchmarking repositories is also proposed.

QFD: A Different Way to Measure Software Quality

Quality Function Deployment (QFD) technique has been developed in the context of Total Quality Management, and it has been experimented in the software engineering domain. This paper illustrated how key constructs from QFD contributed to an development of a second version of a Quality Factor (QF) for a qualitative software evaluation, considering three distinctive but connected areas of interest, each of them representing dimension of performance: ○ economic dimension, the perspective is the managers viewpoint; ○ social dimension, the perspective is the users viewpoint; ○ technical dimension, the perspective is the developers viewpoint. This new version of the original QF technique, referred to as QFD (Quality Factor through QFD), has the following features: it can be used for both a priori and a posteriori evaluations of the software product; it makes usage of the set of quality sub-characteristics proposed in the new upcoming ISO/IEC 9126:2000 standard it has a variable number of elements taken into account the three viewpoints for the evaluation; it offers the visual clarity from QFD for external and internal benchmarking. An implementation of this new version of this technique in quality models is also discussed.