The software value map — an exhaustive collection of value aspects for the development of software intensive products

Khurum, Mahvish; Gorschek, Tony; Wilson, Magnus

doi:10.1002/smr.1560

Cited by 84 publications

(104 citation statements)

References 42 publications

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“…When maximizing value is used as a prioritization goal, different perspectives of value need to be considered. Khurum et al (2012) propose a breakdown of software value aspects therefore enabling discussion about different perspectives on value. Lehtola et al (2005) identifies a need for alignment between business and engineering activities in a market-driven setting.…”

Section: Discussionmentioning

confidence: 99%

Software engineering in start-up companies: An analysis of 88 experience reports

2018

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Context Start-up companies have become an important supplier of innovation and softwareintensive products. The flexibility and reactiveness of start-ups enables fast development and launch of innovative products. However, a majority of software start-up companies fail before achieving any success. Among other factors, poor software engineering could be a significant contributor to the challenges experienced by start-ups. However, the state-ofpractice of software engineering in start-ups, as well as the utilization of state-of-the-art is largely an unexplored area. Objective In this study we investigate how software engineering is applied in start-up context with a focus to identify key knowledge areas and opportunities for further research. Method We perform a multi-vocal exploratory study of 88 start-up experience reports. We develop a custom taxonomy to categorize the reported software engineering practices and their interrelation with business aspects, and apply qualitative data analysis to explore influences and dependencies between the knowledge areas. Results We identify the most frequently reported software engineering (requirements engineering, software design and quality) and business aspect (vision and strategy development) knowledge areas, and illustrate their relationships. We also present a summary of how relevant software engineering knowledge areas are implemented in start-ups and identify potentially useful practices for adoption in start-ups. Conclusions The results enable a more focused research on engineering practices in startups. We conclude that most engineering challenges in start-ups stem from inadequacies in requirements engineering. Many promising practices to address specific engineering challenges exists, however more research on adaptation of established practices, and validation of new start-up specific practices is needed.

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Section: Discussionmentioning

confidence: 99%

Software engineering in start-up companies: An analysis of 88 experience reports

2018

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“…At first, software functionality was predominately required in order to support tangible electrical, hardware and mechanical solutions without delivering any other perceptible value for the customers [1]. Today, software functionality is rapidly becoming the main competitive advantage of the product, and what delivers value to the customers [2]. However, the way in which software features are being developed, and how they are prioritized is still a challenge for most organizations.…”

Section: Introductionmentioning

confidence: 99%

Commodity Eats Innovation for Breakfast: A Model for Differentiating Feature Realization

Fabijan

Olsson

Bosch

2016

Product-Focused Software Process Improvement

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Abstract. Once supporting the electrical and mechanical functionality, software today became the main competitive advantage in products. However, in the companies that we study, the way in which software features are developed still reflects the traditional 'requirements over the wall' approach. As a consequence, individual departments prioritize what they believe is the most important and are unable to identify which features are regularly used -'flow', there to be bought -'wow', differentiating and that add value to customers, or which are regarded commodity. In this paper, and based on case study research in three large software-intensive companies, we (1) provide empirical evidence that companies do not distinguish between different types of features, which causes poor allocation of R&D efforts and suppresses innovation, and (2) develop a model in which we depict the activities for differentiating and working with different types of features and stakeholders.

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“…Furthermore, the individual value of a feature is not additive towards the overall release value and offering them in conjunction will provide synergies that are important to be taken into account [17]. A value-map is suggested by Khurum et al [18] by using knowledge from state-of-the-art in software engineering, business, management, and economics, gathered through literature reviews and by interviewing industrial professionals in that the authors studied a broad range of value constructs and classified them as belonging to customer, internal business, financial, as well as innovation and learning perspectives.…”

Section: Information Needs For Release and Service Portfolio Decisionsmentioning

confidence: 99%

Trade-off Service Portfolio Planning – A Case Study on Mining the Android App Market

Nayebi

Ruhe

2015

Preprint

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Service portfolio planning is the process of designing collections of services and deciding on their provision. The problem is highly information intensive, and most of the information required is hard to gather. In this paper, we present a solution approach based on the paradigm of Analytical Open Innovation (AOI). Open innovation is a cheap and low risk problem solving approach which relies on knowledge exchange with outside of company as a competitive advantage. Different forms of open innovation; crowd source, open source and outsource; facilitate the provider and consumer interactions and brings higher customer value. In our proposed AOI approach, open innovation is utilized for elicitation of services from web data, crowdsourcing the service value from potential customers and for the estimation of service implementation effort. For service evaluation, we apply the Kano theory of product development and customer satisfaction. Based on that and as the result from an optimization process, resource-optimized service portfolios are created that constitute trade-offs in balancing between gained value and effort needed. As a proof of concept, the proposed approach is illustrated via a case study project for the composition of Over the Top TV (OTT) services. The atomic services from 241 qualified apps were analyzed from the android app market. We demonstrate that the proposed approach is able to generate optimized trade-off solutions, composing better apps at each capacity level and achieving better customer satisfaction . Abstract.Service portfolio planning is the process of designing collections of services and deciding on their provision. The problem is highly information intensive, and most of the information required is hard to gather. In this paper, we present a solution approach based on the paradigm of Analytical Open Innovation (AOI). Open innovation is a cheap and low risk problem solving approach which relies on knowledge exchange with outside of company as a competitive advantage. Different forms of open innovation; crowd source, open source and outsource; facilitate the provider and consumer interactions and brings higher customer value. In our proposed AOI approach, open innovation is utilized for elicitation of services from web data, crowdsourcing the service value from potential customers and for the estimation of service implementation effort. For service evaluation, we apply the Kano theory of product development and customer satisfaction. Based on that and as the result from an optimization process, resource-optimized service portfolios are created that constitute trade-offs in balancing between gained value and effort needed. As a proof of concept, the proposed approach is illustrated via a case study project for the composition of Over the Top TV (OTT) services. The atomic services from 241 qualified apps were analyzed from the android app market. We demonstrate that the proposed approach is able to generate optimized trade-off solutions, composing better apps at each capacity level and achi...

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The software value map — an exhaustive collection of value aspects for the development of software intensive products

Cited by 84 publications

References 42 publications

Software engineering in start-up companies: An analysis of 88 experience reports

Software engineering in start-up companies: An analysis of 88 experience reports

Commodity Eats Innovation for Breakfast: A Model for Differentiating Feature Realization

Trade-off Service Portfolio Planning – A Case Study on Mining the Android App Market

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