Key Stakeholders Value Propositions for Feature Selection in Software-intensive Products: An Industrial Case Study

Numerous software companies are adopting value-based decision making. However, what does value mean for key stakeholders making decisions? How do different stakeholder groups understand value? Without an explicit understanding of what value means, decisions are subject to ambiguity and vagueness, which are likely to bias them. This case study provides an in-depth analysis of key stakeholders’ value propositions when selecting features for a large telecommunications company’s software-intensive product. Stakeholders’ value propositions were elicited via interviews, which were analyzed using Grounded Theory coding techniques (open and selective coding). Thirty-six value propositions were identified and classified into six dimensions: customer value, market competitiveness, economic value/profitability, cost efficiency, technology & architecture, and company strategy. Our results show that although propositions in the customer value dimension were those mentioned the most, the concept of value for feature selection encompasses a wide range of value propositions. Moreover, stakeholder groups focused on different and complementary value dimensions, calling to the importance of involving all key stakeholders in the decision making process. Although our results are particularly relevant to companies similar to the one described herein, they aim to generate a learning process on value-based feature selection for practitioners and researchers in general.

💡 Research Summary

This paper investigates what “value” means for key stakeholders when selecting features for a large telecommunications company’s software‑intensive product. While many firms now claim to adopt value‑based decision making, the concrete criteria that constitute value remain vague, leading to ambiguous and potentially biased choices. To address this gap, the authors conducted an in‑depth case study using grounded‑theory (GT) methods. Ten stakeholders directly involved in feature selection—strategic product managers, product owners, project managers, and technical leaders—were interviewed individually. The interview transcripts were coded through open and selective GT coding, allowing value propositions to emerge from the data rather than being pre‑defined.

The analysis yielded 36 distinct value propositions, which the authors organized into six overarching dimensions: (1) Customer Value (e.g., satisfaction, usability, reliability), (2) Market Competitiveness (e.g., differentiation, market share potential), (3) Economic Value/Profitability (e.g., ROI, revenue impact), (4) Cost Efficiency (e.g., development and maintenance costs), (5) Technology & Architecture (e.g., scalability, technical debt, standards compliance), and (6) Company Strategy (e.g., alignment with long‑term vision, regulatory compliance). Although “Customer Value” was the most frequently mentioned dimension across all participants, each stakeholder group emphasized different subsets of the dimensions, reflecting their specific responsibilities and perspectives. For instance, strategic product managers focused on Strategy and Market Competitiveness, whereas technical leaders prioritized Technology & Architecture and Cost Efficiency. The overlap among groups was limited, underscoring the importance of involving all relevant parties in feature‑selection deliberations to capture a holistic view of value.

The study positions itself against prior work that typically employed top‑down, survey‑based approaches with pre‑constructed checklists, which can miss critical criteria due to anchoring effects, response bias, or limited stakeholder representation. By contrast, the grounded‑theory approach used here captures tacit knowledge directly from stakeholders, provides richer definitions for each proposition, and reveals previously overlooked dimensions such as strategic alignment and architectural considerations. The authors discuss threats to validity, including the single‑company context, potential researcher bias in coding, and the subjective nature of interview data, and they mitigate these through member checking, triangulation, and transparent coding procedures.

Practically, the 36 propositions can be incorporated into decision‑support tools, checklists, or existing release‑planning frameworks (e.g., the VALUE framework) to structure feature‑selection meetings, reduce ambiguity, and facilitate transparent trade‑off analysis. The findings also suggest that organizations should explicitly document and communicate the value dimensions most relevant to each stakeholder group to avoid hidden conflicts and ensure that decisions align with both short‑term operational goals and long‑term strategic objectives.

Academically, the paper contributes to the Value‑Based Software Engineering (VBSE) literature by providing an empirically grounded, multi‑dimensional set of value propositions specific to feature selection. It demonstrates how stakeholder‑specific value lenses can be systematically elicited and categorized, offering a foundation for future theoretical models, quantitative valuation techniques, and tool development. Moreover, the per‑stakeholder analysis enriches our understanding of how value is negotiated in real‑world software development contexts.

In conclusion, the authors successfully translate the abstract notion of “value” into a concrete, actionable taxonomy for feature selection, highlighting the diversity of stakeholder perspectives and the necessity of inclusive, value‑aware decision processes in modern software‑intensive product development.