Data Journey Modelling: Predicting Risk for IT Developments
Information sharing is a vital element of a successful business. However, technological, organisational and human challenges obstruct the effective movement of data. In this paper, we analyse a collection of case studies from healthcare describing failing
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Abstract. Information sharing is a vital element of a successful business. However, technological, organisational and human challenges obstruct the effective movement of data. In this paper, we analyse a collection of case studies from healthcare describing failing information systems developments. A set of 32 failing factors were extracted showing that data movement, either between systems, people or organisations, is a key indicator of IT failure. From this examination, we derived antipatterns for data movement in which some key differences between the source and target location of the movement caused high costs to the developments. Finally, we propose data journey modelling as a lightweight technique that captures the movement of data through complex networks of people and systems, with the aim of improve go/no-go decision making for new IT developments, based on the anti-patterns we have identified. Keywords: Information sharing · Data movement modelling journey · Socio-technical challenges
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Introduction
While software has the capability to bring many benefits to organisations, it can be a mixed blessing [5]. New software developments can be unexpectedly costly to develop and run. It may be necessary to employ new personnel or retrain existing staff. New ways of working may need to be devised, to fit with the constraints of the new software and the technical infrastructure on which it runs. One does not need to spend long looking through newspaper headlines or the Risks List digest1 to know that new software developments can sometimes result in costs that far outweigh the value they propose to create. Clearly, a lightweight and reliable means is needed of helping us to make good go/no go decisions regarding new software developments. Current approaches to managing risk and estimating the cost of software development are principally focused on creating detailed predictions based on substantial models of 1
www.risks.org.
c IFIP International Federation for Information Processing 2016 Published by Springer International Publishing Switzerland 2016. All Rights Reserved J. Horkoff et al. (Eds.): PoEM 2016, LNBIP 267, pp. 72–86, 2016. DOI: 10.1007/978-3-319-48393-1 6
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the planned development [2]. They are aimed at supporting project managers throughout the development process itself, rather than giving a low-cost indicator for use in early-stage decision making. What is needed is a lightweight approach, that can be completed in the course of a small number of days, and that gives reliable predictions of the likely success of a planned IT development. And since the reasons for software failure are rarely technical in nature, the indicator must take account of social and organisational factors, as well as the technologies to be used. We set out to design an indicator of this kind for use in large complex organisations. As a starting point, we analysed a set of 18 case studies of new software developments in the UK’s National Health Service (NHS). The case studies were written by N
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