Good enough over optimal: A longitudinal case study on software release planning in digital health
Elmira Onagh, Dennis Johnson, Matthieu Vautrin, Alireza Davoodi, Maleknaz Nayebi · Journal of Systems and Software · 2026
COVID-19 accelerated the digital-health market, resetting user expectations at a pace that makes traditional release planning brittle. In partnership with Curatio, we conducted a 12-month longitudinal case study to evaluate and improve the release process for their flagship app, Stronger Together . First, we mined public app store data to map the product space and quantify the reuse value of 134 candidate features. Next, we formulated a bi-objective optimization that maximizes reuse value while preserving feature cohesion, yielding a data-driven “Plan K” for the next release. Finally, we compared this plan with the two releases Curatio shipped, combining artifact analysis with semi-structured interviews. Five of the seven recommended features were adopted, capturing 80% of the predicted reuse value; two high-impact items were deferred because of technical and regulatory constraints. The evaluation identifies four recurrent “release traps” that explain why theoretically optimal plans can fail in practice and demonstrates how good-enough, continuously replanned roadmaps can deliver most of the benefits with significantly less risk. The study contributes a replicable appraisal method for feature-reuse decisions and offers actionable guidance for industrial teams facing the same balance of legacy maintenance, rapid innovation, and market uncertainty.