Furthermore, social software will only increase in importance in helping organizations maintain and manage their domains of knowledge and information. When networks are enabled and flourish, their value to all users and to the organization increases as well. That increase in value is typically nonlinear, where some additions yield more than proportionate values to the organization (McCluskey and Korobow, 2009). Some of the key characteristics of social software applications as they apply to crowdsourcing techniques are listed below.
1. Personal profile information (“personal brand”) to build user-driven skills taxonomy;
2. Knowledge sharing, creation, organization, storage, and retrieval;
3. Really simple syndication (RSS) content feeds replace or restructure the e-mail in-box;
4. Content rating to rank value of contributions by others;
5. Practitioners can self-identify as subject matter experts;
6. Social and professional interaction around hard problems, like practitioners, communities of practice and interest;
7. Business intelligence (BI) dashboard or analytics portal captures the interactions and transactions taking place across a social network;
8. Extranet capabilities-glean content (wikis, blogs, and micro-blogs) and selectively make available to the public or to clients;
9. Team coordination and communication, including people search (expertise location);
10. Enterprise skilling to track individual and collective knowledge and skills;
11. Metadata tagging; and,
12. Reputation management and alerting (McCluskey & Korobow, 2009).
The open source software movement proved that a network of passionate, geeky volunteers could write code just as well as the highly paid developers at Microsoft or Sun Microsystems. Wikipedia showed that the model could be used to create a sprawling and surprisingly comprehensive online encyclopedia. And companies like eBay and MySpace have built profitable businesses that couldnt exist without the contributions of users (Howe, 2006, p. 37). In this article, Howe coined the term “crowdsourcing” – which he defines as “the act of a company or institution taking a function once performed by employees and outsourcing it to an undefined (and generally large) network of people in the form of an open call” (p. 37). Howe (2006) further clarified that “Its only crowdsourcing once a company takes that design, fabricates [it] in mass quantity and sell[s] it.” Companies such as Threadless (https://www.threadless.com), iStockphoto, and InnoCentive (http://www.innocentive.com), as well as user — generated advertising contests, are examples of the crowdsourcing model in action (Brabham, 2008).
Current trends indicate that the use of crowdsourcing will continue to increase in the future, particularly in view of the exponential growth of social networking and open source software initiatives. For instance, West (2008) advises, “Technological progress and the evolution of virtual networks and social vetting-that is, using networks such as Linkedln to establish trust and research peoples backgrounds-will increase workplace flexibility. The trends will increase the use of emerging work structures that involve engaging professional and social networks through means such as “crowd sourcing-when an organization invites the public to help solve a problem” (p. 21).
Likewise, Quart (2007) reports that, “Easy information sharing has led to the birth of “crowd-sourcing”-a new pool of cheap labor in which ordinary people use their “spare cycles to create content, solve problems, even do corporate R & D,” also jargonized as “decentralized horizontal media,” “convergence culture,” or “commons-based peer production” (p. 73).
Crowdsourcing provides a key framework for organizations to capitalize on the wisdom of the crowd, that is, the average of diverse, independent, and decentralized crowds (Surowiecki, 2004). Suroweicki is a proponent of collective intelligence and the ability of a group to solve concrete, well-defined problems and to make decisions that will be intellectually better than those of the isolated individual over time. He makes a solid case for this argument by discussing different types of problems (cognition, coordination, and cooperation) and necessary conditions for the crowd to be wise (diversity, independence, and decentralization) (Shiu, 2007). The groundswell is a social development in which people use modern technologies to get the things they need from one another (Li & Bernoff, 2008). Specifically, the impact of the well-informed crowds on an organizations attempt to develop business strategies and operational efficiencies that allow the organization and its customers to co-develop and co-create value is very promising in the business area of call centers. That said; it is not known to what extent crowdsourcing techniques can be effectively applied in call centers to increase call center performance as measured by established key performance indicators, ultimately resulting in operating efficiencies that fosters an environment where the organization and its customers co-develop value.
The intention of this study is to illuminate and explain the aspects that enable call centers to more effectively assist their organizations main business units in increasing operational efficiencies through the use of crowdsourcing techniques. With this goal in mind, the following research question will be addressed: “What is the relationship between the application of crowdsourcing techniques and call center performance as measured by normal call center key performance indicators and an organizations functional business areas operational efficiencies?”
1. The affective application of crowdsourcing techniques leads to increased call center performance.
a. Crowdsourcing techniques are related to an increase in first call resolution in call centers.
b. Crowdsourcing techniques are related to decreased average call handle time in call centers.
c. Crowdsourcing techniques are related to decreased cost per call in call centers.
d. Crowdsourcing techniques are related to decreased abandonment rates in call centers.
e. Crowdsourcing techniques help to optimize call center agent utilization.
2. The increased performance of call centers, which results from the application of crowdsourcing techniques, are associated with increased operational efficiencies in an organizations major business functional areas.
3. Operational efficiencies, which are the results of increase call center performance due to the affective application crowdsourcing techniques, help foster a business environment where both the organization and its customer co-develop
Scope of Study
Rationale of Study
According to Robinson and Morley (2007) “Call center research has, to date, relied heavily on case studies. The advantages gained from case study research need to be supplemented by well conducted survey research” (p. 250). Likewise, Brabham (2008) emphasizes that, “Coined in the June 2006 issue of Wired, the term crowdsourcing describes a new Web — based business model that harnesses the creative solutions of a distributed network of individuals through what amounts to an open call for proposals” (p. 3). In other words, a company posts a problem online, a vast number of individuals offer solutions to the problem, the winning ideas are awarded some form of a bounty, and the company mass produces the idea for its own gain. While crowdsourcing has proven its worth in for — profit contexts, some have hopes for crowdsourcing as a far — reaching problem — solving model that can harness the collective intelligence of the crowd to benefit government and non-profit projects. No matter the purpose — for business or for the public good — the potential for the crowdsourcing model needs to be tapped (Brabham, 2008).
Overview of Study
This paper used a five-chapter format to achieve the above-stated research purpose. Chapter one is used to introduce the topics under consideration, provide a statement of the problem, the purpose and importance of the study, as well as its scope and rationale. Chapter two provides a critical review of the relevant and peer-reviewed and popular literature concerning crowdsourcing and call centers, and chapter three more fully describes the studys methodology, a description of the study approach, the data-gathering method and the database of study consulted. Chapter four is comprised of an analysis of the data developed during the research process and chapter five presents the studys conclusions, a summary of the research and salient recommendations.
Chapter 2: Review of Related Literature
Crowdsourcing: What is It?
Most likely everyone has heard of outsourcing, but many consumers may not have heard about crowdsourcing. According to Anthony Williams, co-author of Wikinomics: How Mass Collaboration Changed Everything, says examples of crowdsourcing are ubiquitous. Likewise, de Castella (2010) recently observed that, “Open source computer operating systems, such as Linux and Googles Android, the big rival to Apples iPhone, are written and refined by members of the public. Another good example of such collaboration is Wikipedia, which allows users to write and edit entries for its online encyclopaedia” (para. 2). According to Howe (2006), “Technological advances in everything from product design software to digital video cameras are breaking down the cost barriers that once separated amateurs from professionals. Hobbyists, part-timers, and dabblers suddenly have a market for their efforts, as smart companies in industries as disparate as pharmaceuticals and television discover ways to tap the latent talent of the crowd. The labor isnt always free, but it costs a lot less than paying traditional employees. Its not outsourcing; its crowdsourcing” (p. 37). In this regard, Williams adds that, “For the first time millions of people can aggregate their talent and expertise” (para..