Harnessing Anomalous Preferences of Anonymous Users for Lean Information Systems Development

When features are added to an existing Information Systems (IS) product in response to market demands it is important to assess their business value before implementing them into the product. But how does one estimate the true value of a new feature? Is it sufficient to consider only the consumer reward for including a feature into the product or is it also useful to evaluate the consumer penalty for not building the feature into the product? The current methods for feature selection capture only the consumer inputs for building a feature into the product. The implications of not building the feature are not captured. This study investigates the adequacy of such an approach and discovers that additional business information can be extracted by considering both, the reward as well as the penalty perspective of the user. This information can be utilized by producers in developing lean IS products, thereby providing salutary benefits to both provider and consumer.