A process for managing benefits of mobile enterprise applications in the insurance industry

Knoesen, Henri

A process for managing benefits of mobile enterprise applications in the insurance industry

Doctoral Thesis

2018

Abstract

Mobile enterprise applications (MEAs) are found in increasing numbers in organisations as smart-devices become an everyday necessity amongst employees and customers. Large amounts are invested in these applications, so it is important to see the value in improved business processes and the consequential improvement in business performance. Realising the benefits from their use is important to obtain the value from these investments. Yet, benefits management (BM) is poorly implemented in companies and a first step to improve this situation is to improve the visibility of the benefits that can be achieved by using MEAs. Hence the primary question asked in this study is “How can MEA benefits be successfully realised?” The strategy used to answer the question was action research in a single organisation using three MEAs in two different action research cycles. The study was conducted in a short-term insurance company in the Western Cape of South Africa with an established IT and project capability. Globally, the short-term insurance industry is under a significant threat from disruption by market entrants who don’t have to navigate legacy systems and who are more agile with their product offerings. Traditional insurers are looking for innovative solutions to transform the way in which insurance is sold and serviced. A BM process, which was modified from the literature, was refined through action cycles in three MEA projects to improve benefits realisation. The result showed that for MEA projects, which are not very large investments relative to other IT projects, a lighter, less cumbersome process was more practical and acceptable in the organisation. The creation of a benefits and risks template, during the action cycles, helped the organisation to build stronger business cases for MEA projects and also allowed for more comprehensive benefit identification, measurement and tracking, ultimately realising business performance improvements. The study also used a survey amongst 88 brokers and assessors to determine the factors which influence their adoption of these MEAs. The most significant factors influencing user adoption were the company’s willingness to fund the smart-devices, the ease of use of the MEA, job relevance and location dependence. A limitation of this study is that the organisation has a particular approach to project funding whereby the importance of BM is weighed against the cost of the project, hence BM is more important for very expensive projects. While the model prescribed in this study was sufficient in this context, it may not be suitable for organisations that are more conscientious about BM. This model would need to be tested in other contexts for transferability. A further limitation was the duration of time available for conducting this study because this was a PhD research project. Further action cycles might have refined the process further. The findings from this study are relevant to researchers and to organisations wanting to deploy MEAs. The BM process defined in this study can be used in MEA projects as a process to manage the identified benefits and ensure that they are realised. The benefits template can be used as a first step in the BM process to build the business case and the risks template can be used to identify potential problems that could hinder benefits realisation and can used to put mitigating actions in place to prevent problems to benefits realisation. The identification of factors influencing adoption of MEA can help organisations focus on these factors to ensure that their MEAs are used and they thereby derive benefits. The theoretical contributions of this study are a process model for the BM body of knowledge and a model explaining the factors influencing symbolic adoption of MEA. The identification and description of benefits and risks extends the body of knowledge for mobile applications research. These specific issues in the context of MEAs in the short-term insurance industry are understudied.