Data Analysis

In the technology roadmapping methods identified in chapter two, the data analysis stage of the process is initially carried out with participants. This requires a time commitment, such as attendance at several workshops that participants to the FV technology roadmapping process could not guarantee. An added issue to be taken into consideration when designing the data analysis process was that it was envisaged that version three of the FV roadmap would be generated using Vision Strategist™ software and that this indicated a considerable time commitment and knowledge of the software from the researcher that could not be expected, or was required of participants in the roadmapping process.

3.5.1 Data Input

Quantitative data from the workshops and questionnaires was entered into Excel® from February to June 2008. As the technology focus of each workshop was specific to particular issues which would also be reflected in the roadmap representation, for

the purpose of analysis the output from each workshop and the questionnaire was kept in individual Excel® files which could be imported into the Vision Strategist™ software using the online tool ‘powergrid’.

3.5.2 Data Analysis Method

For the purpose of developing a comprehensive roadmap that could be compared with versions one and two it was critical to analyse the data in such a way that the

technology issues and opportunities could be extracted as stand alone data but could also be analysed in relation to the associated data collected. Data analysis included the production of descriptive statistics to describe the elements of the technology issues including range and mean.

In order to ascertain that the UK automotive sector could have confidence that the information represented within the roadmap focused on technology issues, PESTLE (Political, Economic, Social, Technical, Legal and Environmental) analysis of all the technology issues generated from each workshop was required.

3.5.3 Information Representation

Using dedicated roadmapping software created an issue relating to the time taken to input all the relevant data and associated elements that would support the generation of specific roadmapping views and the updating process. The following data fields were seen as essential to the roadmapping management process:

• Colours – list of colours used to describe a particular technology statement

• Currency – date when data was collected

• Date of data entry – important element in terms of updating

• Origin – source of information

• Priority level – headline item or sub item

• Relevance – used for information that is either core to the roadmap or information generated elsewhere

• Research findings – indicates level of activity and potentially maturity levels

• Technology readiness levels – numerate levels to indicate maturity

Incorporation of the above data fields in the data representation process will allow a richer picture to be developed. They will also become key elements of the validation process.

3.6 Summary

Critical to the success of developing a successful methodology to support the technology roadmapping process is the individuals who are willing to engage in the process. Examples of participatory research can be utilised to provide a framework for designing a robust data collection methodology with the focus on individual participation and as the process develops moving towards group consensus. Existing methods of data collection that have been used in technology roadmapping such as Delphi, focus groups, interviews all have strengths and weaknesses, therefore it is suggested that a mixed method approach utilising workshops, questionnaires and investigation of documents and resources deemed to be suitable to support the generation of the FV (v.3) technology roadmap and ultimately influence the development of an information protocol based on an ontological framework. The research study will contribute to the continuous developing science of technology roadmapping by providing an insight into the relationships between what may appear to be disparate items of information and the discovery of how they interrelate.

Chapter Four: Findings

4.1 Introduction

The aim of this chapter is to present an overview of the data collected from workshops and questionnaires used to inform the development of version 3 of the Foresight Vehicle Technology Roadmap. Analysis of the data gathered will inform the development of an Information Protocol which will be underpinned by the ontological framework, introduced in Chapter 2.

Section 4.2 provides an overview of the results of the Pilot Study as well as results from the first FV workshop. These inform and demonstrate the need to further develop the Methodological framework, which in turn lead to refinements of the Information Protocol. Section 4.3 presents the results of the questionnaire from the FV Engine and Powertrain Thematic Group (EPT). This is followed by Sections 4.4, 4.5 and 4.6 detailing the results of the three FV workshops (DMAP, FASMAT and Stakeholder) are provided in some detail. Here for the first time, the data collected are associated with technology themes; technology opportunities with timescales; TRL’s with barriers to technology development. Section 4.7 presents the results relating to barriers to progress from the three FV workshops using PESTLE analysis. The final section provides a summary of the main findings.