By taking a big data approach to analyzing collaborations with large clients, highly distributed global companies can gain valuable and timely insights into client satisfaction.
Keeping tabs on the health of client relationships is an important activity for any company hoping to promote stability and growth. Knowing how customers feel about your products and services is particularly vital for organizations specializing in “extended-enterprise” services such as back office operations, decision support, and engineering, technology and asset support for large operations. In the last 20 years, the popularity of such so-called “shared services centers,” those shared either internally or externally through outsourcing, has grown exponentially. Shared services centers now employ hundreds of thousands of people worldwide and constitute a ubiquitous backbone across the largest and most complex enterprises. Although this organizational model has created significant economic benefits and is a cornerstone of organizational scalability and cost effectiveness, it also presents significant governance challenges: The large-scale, global nature of the service delivery and the complex, often matrixed client organizations such companies serve make it harder to detect client dissatisfaction. Many companies monitor customer satisfaction through customer satisfaction surveys such as the Net Promoter Score pioneered by management consultant Bain & Co. An NPS score is obtained by (1) asking customers to answer a single question (“How likely is it that you would recommend our company to a friend or colleague?”) on a scale from 0 to 10 (where 10 is “extremely likely” and 0 is “not at all likely”); and (2) subtracting the percentage of “detractors” (scores 0-6) from the percentage of “promoters” (scores 9-10).1 However, such methods are not necessarily timely (because they are survey-based) and often do not enable companies to drill down into detail (because of the size of the sample). Therefore, they are not sufficient for continuous measurement of customer satisfaction or for informing timely and targeted corrective actions. As it turns out, there are two specific challenges to behavior analysis in global organizations such as shared services centers. The impersonal, remote nature of many of the exchanges and the high volume of interactions make it extremely difficult for senior management to document and analyze them using traditional means.
The way people interact with each other and what they say to each other offer an important window into how they feel about each other.