The Impact of Technology Insertion on Organisations

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HFIDTC/2/12.2.1/1 Version 3 / 21 November 2007 Figure 9: ASRM Screenshot This approach allows absolute percentage risk decrease and relative percentage risk decrease to be calculated when; • there are no technology insertions; • following the insertion <strong>of</strong> all relevant technologies; • when new technologies are introduced separately. This model is designed to depict causal factors, by combining statistical data with judgement <strong>of</strong> subject matter experts to obtain estimates <strong>of</strong> probabilities. <strong>The</strong> authors state that the ‘Air Ontario 1363 case study demonstrates the importance <strong>of</strong> considering not only errors made by pilots and the cabin crew but also situational (e.g. weather), supervisory, and organisational factors’. 10.2.1.5 Socio-technical Team-working for OR Modelling (STORM) STORM is an algorithm developed by DSTL which combines Tuckman’s team maturity process [219] with Noble’s [220] theory <strong>of</strong> knowledge enablers to create a model <strong>of</strong> the social and cultural characteristics <strong>of</strong> teams. STORM is described as an ‘attempt to use modelling and simulation to examine some <strong>of</strong> the human issues that may emerge in the implementation <strong>of</strong> the concept <strong>of</strong> agile mission grouping’. 59
HFIDTC/2/12.2.1/1 Version 3 / 21 November 2007 STORM integrates Noble’s and Tuckman’s processes to model the dynamic development <strong>of</strong> teams from first formation to full maturity. As a representation <strong>of</strong> the impacts <strong>of</strong> social and cultural factors on team performance in a coalition NEC context, STORM allows informal team relationships to be modelled and can provide insight into how NEC can influence team behaviour. This tool was developed in response to a need for a model capable <strong>of</strong> dealing with agile, ad hoc team formation associated with Agile Mission Grouping [221], [222]. This model focuses on team performance based on team composition, context and maturity. STORM currently does not model the influences <strong>of</strong> technology directly; however, aspects <strong>of</strong> co-location versus remote computer mediated communication are modelled. Work is currently being undertaken to try to model team acceptance <strong>of</strong> technology and this will be an interesting development. <strong>The</strong>re is potential to develop a similar model, or collaborate with DSTL to look at how technology influences interact. Figure 10: Interacting Nodes in the ‘STORM’ Model 10.3 Summary <strong>of</strong> the Extant TI Tools A number <strong>of</strong> tools, methods and techniques have been, or are being, developed to support practitioners during the technology insertion process. Whilst these options are worth considering, many <strong>of</strong> them are either not fully developed, or are narrow in their scope. This is especially true <strong>of</strong> the cited s<strong>of</strong>tware tools and models that focus exclusively on engineering and cost-based aspects <strong>of</strong> TI decision making. Whilst this is undoubtedly a valuable goal, there are far fewer tools for supporting practitioners in understanding and measuring organisational implications <strong>of</strong> technology decisions. OSTA and POINTS may be valuable methodologies, however, it appears that there are no discrete tools to guide the novice practitioner. Such guidance may be particularly relevant given that these methods rely upon the skills and experience <strong>of</strong> the implementer in order to be successful. 60
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