Conference Agenda

Session
12-04: Ting Yu
Time:
Saturday, 20/Jul/2019:
3:45pm - 4:10pm

Seminar Room 2-4

Chair: Bart Lariviere


Abstract

Service–Sales Ambidexterity: Past, Present, and Future

Authors: Ko de Ruyter (King’s College), Debbie Keeling (University of Sussex), Ting Yu (University of New South Wales, Australia)

The notion of organizational performance has moved beyond simply attaining sales targets, service quality thresholds, or efficient average handling times as distinct, key indicators. A broadened key performance indicator palette acknowledges that consumers expect an engaging experience across multiple touchpoints and solution offerings that cater to their needs. This paper extends current knowledge about the resulting need for service–sales ambidexterity in three ways. First, we offer a synopsis of current scholarly insights into how to blend service delivery with sales and identify contextual conditions that foster effective service–sales ambidexterity. In relation to the simultaneous pursuit of service and sales goals, several gaps emerge. For example, scant theorizing addresses the common ground for service and sales activities and its potential for combining service and sales activities as an interface, at individual and collective (organizational) levels. Previous research conceptualizes service–sales ambidexterity primarily in relation to employee orientations (e.g., service vs. sales) and shared beliefs (e.g., climate perceptions). In contrast with this general attitudinal perspective, elements of service–sales aptitude, such as feasible blending practices and behaviors at individual and team levels, have received insufficient research attention. Furthermore, it is not clear whether the servicing and selling interface should be interpreted as a capability outcome or a capability implementation practice. In addition to equipping frontline employees and channel partners with knowledge and skills, another research gap arises due to the rapid advances in artificial intelligence (AI)-based technologies and machine learning, which hold the promise of building service–sales ambidexterity capacity. That is, AI and human labor might work together to facilitate the service–sales interface, but insufficient research details how such collaborations might function. Second, turning to current practice, we use an empirical case study to demonstrate how a multinational company strategically deploys online learning to bridge structural knowledge and skills gaps within its reseller network to achieve ambidextrous capacity in its channels and thus support solution selling. Complementing this human learning approach, we explore recent advances in machine learning and their impact on the service–sales interface. Third, we blend the academic and practice perspectives to establish a service–sales interface agenda that identifies directions for research. We call for the further theoretical development of ambidexterity concepts, as well as for novel insights into how to blend technologies effectively at the service–sales interface to enable ambidexterity in practice.