Regulations, skilled workforce and knowledge
In this CS4, which represents a case from the railway industry in the United Kingdom, the value flow maps demonstrate how additional big data analytics services offered by Coventry University Group to the Network Rail can create new value delivered to the stakeholder network. The university was not an originator of this network, the initiative was triggered by Network Rail that tries on a daily basis under the Office of Rail and Road’s instructions to reduce its losses. The university’s research unit was hired to deliver the big data analytic services. However, as the model suggests there is close connectedness between the university and the rest of the stakeholders via the knowledge value flows delivered throughout the network. The concentration of interactions is visually presented on the map (see below).
In theory, the monopoly nature of the railway industry predefines the relations between the regulators and the industry’s players. The UK government has set up the framework within which the industry operates. Department for Transport and Transport Scotland transfer its policy directions to the industry’s regulators, which then inform the major actors of the railway sector how to comply with them.
In our particular case, as the offered service in the North-west region of the United Kingdom relates to the exchange plus analysis of data and its sharing with stakeholders, the network’s operations are data-driven and knowledge-intensive. Coventry university transfer scientific and technical knowledge to the rest of the network. All 10-stakeholders benefit from the value created by the exchange of structured and analyzed data, which supports them in offering better and safer railway services in the UK. This in return leads to a better feedback coming from the UK public to the governmental institutions about the public satisfaction of the railway services. As there is a direct interaction between the citizens and the UK government, in CS4 the public plays a crucial role in the delivery of value throughout the stakeholder network.
In this post, the value loop involves only two stakeholders – CUE (Coventry university) and RSSB (the safety regulator). The value loop is very short and the value creation is the highest of all examples discussed in all four cases. The calculation is based on a multiplication of the individual value flow scores within the loop. This is a direct value loop since it involves the central stakeholder (CUE) and another one. In this example, the scientific knowledge and data value flow from CUE to RSSB becomes an exchange on regulations flow from RSSB to CUE.
Science knowledge & data from CUE -> RSSB 0.84
Exchange on regulations from RSSB -> CUE (Coventry university) 0.59
Value loop score = 0.84* 0.59 = 0.4956
The example presents interactions between CUE and the regulators which are highly valuable since the regulatory authorities in the UK enforce the standards for safety and security of the public on the railway network.
Moreover, the ITS innovative network depends on skilled workforce and tech knowledge, therefore the UK stakeholders should train their labour for the future, deriving data and technological innovations from the current knowledge transfers between all actors.