When should customers control service delivery? Implications for service design

What do a Mongolian stir-fry restaurant and a medical lab providing home testing solutions have in common? They are both innovative services that base their success on customers controlling part of the service delivery. These providers allow service tasks to be performed by the customers as a means of shaping the overall experience and not strictly as a means of "outsourcing" the service. Motivated by such practices, we explore whether and how should providers allocate the control of different tasks of their service to the customers. We model services as multi-step processes with each step affecting customers' experience at other steps. At certain steps the provider may hold an “expert" role and be more capable of performing than the customers, whereas at other steps she holds an “administrative" role and is less capable of performing than the customers. We distinguish between routine services, where the service outcome must conform to standardized specifications, and non-routine services, where the value of the service outcome relies on subjective dimensions. We show that the optimal design is determined by an economically intuitive rule whereby the provider controls the steps based on the marginal benefit she can derive compared to self-service. For routine services, this rule translates to managing “blocks" of steps because the provider benefits from containing the volatility of the experiences across the service even when this implies the provision of service steps with a negative marginal benefit, i.e., steps which she is less capable of performing than the customers. Instead, in non-routine services providers should focus on the value advantage they can ensure through a "core provision" even if this implies forgoing control of steps for which they are more capable of performing than the customers and from which they can derive positive marginal benefit. This implies that in non-routine services the provider exercises more control up to a certain process length; beyond that she delegates more steps to the customers. When customers differ in their abilities to perform the different steps, the provider may offer a service line. Service lines facilitate better segmentation than a single service offering, but their economic benefit exhibits an inverted “U-shaped" relationship with respect to the number of steps that a service comprises. Finally, we find that competition between two providers who differ in their capabilities to perform a service results in service design differentiation where the more capable provider offers a higher-end "focused service" against a lower-end "super-service" offered from the less capable provider

The Effects of Problem Structure and Team Diversity on Brainstorming Effectiveness

International audienceSince Osborn's Applied Imagination book in 1953 (Osborn, A. F. 1953. Applied Imagination: Principles and Procedures of Creative Thinking. Charles Scribner's Sons, New York), the effectiveness of brainstorming has been widely debated. While some researchers and practitioners consider it the standard idea generation and problem-solving method in organizations, part of the social science literature has argued in favor of nominal groups, i.e., the same number of individuals generating solutions in isolation. In this paper, we revisit this debate, and we explore the implications that the underlying problem structure and the team diversity have on the quality of the best solution as obtained by the different group configurations. We build on the normative search literature of new product development, and we show that no group configuration dominates. Therefore, nominal groups perform better in specialized problems, even when the factors that affect the solution quality exhibit complex interactions (problem complexity). In cross-functional problems, the brainstorming group exploits the competence diversity of its participants to attain better solutions. However, their advantage vanishes for extremely complex problems

Product Quality Choice, Competition, and Supply Chain Design

We explore the interplay between product design choices and their effect on the supply chain transactions. A large number of industrial business-to-business transactions indicates that product design choices, and the definition of the overall product performance (quality), is relying on "off the shelf" standardized components, and it influences the component pricing. We develop a normative model that highlights the drivers for the different industrial settings and we consider end product markets with quality sensitive heterogenous consumers (vertical differentiation). We find that depending on the industry concentration at the different tiers of the supply chain, the timing of the product definition by the OEM has a substantial effect on the transacting firms payoff, as well as on other relevant metrics (total supply chain profits, social welfare). By examining the potential action sequences across the transacting firms, we identify the incentives for each firm to accomplish a decision earlier or later in the strategic interaction. Interestingly, the standard notion of the "leader" advantage in the transaction does not hold always, due to the indirect effect of the component cost on the end-product market, through the indirect link between the product performance and the total market served. Therefore, the OEM may benefit more from finalizing the end product specifications based on known component costs. Along similar lines, the supplier may benefit from a "follower" position in the sequence of decisions. Finally, the severity of competition in any of the two tiers may be diluted by a specific sequence, depending on the available nformation at the monopolistic tier

Dynamic Portfolio Selection of NPD Programs Using Marginal Returns

Selecting program portfolios within a budget constraint is an important challenge in the management of new product development (NPD). Optimal portfolios are difficult to define because of the combinatorial complexity of project combinations. However, at the aggregate level of the strategic allocation of resources across product lines, investment in a program is not an all-or-nothing decision, but can be adjusted, resulting in a higher or lower program benefit (e.g., higher or lower quality). In some cases, resources can be adjusted even for individual projects. With this insight, one can use marginal analysis to optimally allocate the scarce budget. This article develops a dynamic model of resource allocation, taking into account multiple interacting factors, such as independent or correlated, uncertain market payoffs that change over time, increasing or decreasing returns from the NPD investment, carry-over of the investment benefit over multiple periods, and interactions across market segments. We characterize optimal policies in closed form and derive qualitative decision rules for managers.new product development, resource allocation, portfolio selection, portfolio investment, dynamic programming, marginal benefits