Enterprise 2.0 and Social Networking Effects on Collaboration

Introduction and Project Objectives

There continues to be empirically derived evidence that the accumulated effects of social networking technologies on corporate performance contribute to greater levels of collaboration, communication, reduced operating costs, and more efficient orchestration of complex tasks. With value chains across a diverse base of industries continually being consolidated through cost pressure, time-to-market demands, global economic uncertainty, and disruptive innovation, there is an urgent need for businesses competing globally to make collaboration a core competency. The use of social network constructs, frameworks, and collaborative platforms in enterprises to increase collaboration, improve communication, and as a result increase performance and reduce costs was pioneered by Dr. Andrew McAfee. He defined the integration of social networks into enterprises as Enterprise 2.0, and since then this term has become a business standard (McAfee 2006). Since the origination of this concept, further studies have been completed that center on the most challenging aspect of Enterprise 2.0: the attainment of successful change management programs across large-scale organizations (Kuettner, Diehl & Schubert 2013).

Today, organizations vary in their level of Enterprise 2.0 adoption, with many choosing to automate the most outbound aspects of their business models first (McAfee 2006). This focus on externally based integration points further complicates change management, as there are already innate communication differences across the many, often siloed organizational, departmental, distribution, and service channel structures that large-scale enterprises rely on to operate (Kuettner et al. 2013). Given these significant differences in adoption levels — predicated on enabling key members of a company's value chain external to the core business first — there are varying levels of communication and collaboration maturity evident across industries. The aggregate effect of what Dr. McAfee found from his initial studies and subsequent analysis is that in the value chains of businesses that adopted Enterprise 2.0-based approaches to managing communication, a clear experience or network effect occurred throughout their organizations (McAfee 2006). This experience or network effect has also been characterized as varying levels of interprocess and system integration maturity, as exemplified by the accuracy (measured in error reductions), speed, and cost reductions attained (Trimi & Galanxhi 2014).

As large-scale enterprises continue to adopt and propagate Enterprise 2.0-based constructs and frameworks throughout their organizations, industries and classes of companies within them are starting to exhibit unique, differentiated characteristics. It was the intent of this analysis to isolate those companies within specific industries and track their maturity along the Enterprise 2.0 continuum, quantifying the value of social network-based communication and collaboration in the process. The contributions of using social networks to further increase communication and collaboration within Enterprise 2.0-based frameworks continue to transition from nascent to mainstream adoption, with these technologies playing a supporting role in global business performance (Trimi & Galanxhi 2014). In sum, the intent of this study was to isolate and examine these dynamics as described further below.

Project Objectives

The initial objectives for this project were as follows:

1. To quantify through secondary research the contributions of social networks to the collaborative performance of organizations across their value chains.

2. To classify performance results reported in empirical studies according to a quartile system that provides an easily understood framework for comparing results across studies.

3. Through the use of secondary research, to quantify the contribution of social networking technologies and Enterprise 2.0-based applications at an industry level of analysis.

4. To combine the empirically derived performance results by quartile across industries and create an Enterprise 2.0-based maturity model based on the accumulated research and analysis.

Based on the inclusion of primary research, the following additional objectives were also added:

1. Based on interviews with industry experts in the field of social collaboration and adoption of social networking technologies in enterprises, quantify the breakout levels of each layer of the maturity model.

2. Define the characteristics of fast- and slow-adopting industries with respect to core Enterprise 2.0 concepts, and define a spectrum of their relative levels of maturity. This constitutes a more horizontal view across industries of Enterprise 2.0 adoption, including a focus on which factors most and least contribute to success in change management strategies. Previous studies indicate how critical change management planning and orchestration are overall, making this a critical factor for the success of the overall program (Kuettner et al. 2013).

Background Research

The foundational elements of Enterprise 2.0 have been in existence for decades, albeit far less automated than they are today. Further, the findings of McAfee in defining the concept of Enterprise 2.0 illustrate how the network effect, once accelerated through the use of online social networks, creates an accelerating maturity model as well (McAfee 2006). What emerges from this analysis is a greater appreciation of how social networks, regardless of their origin, all share a common trait of creating maturation curves or levels that can predictably define how and where they are most adept — spanning from simple cooperation and information sharing at the low end to full synchronization of processes and systems at the other.

The research to date also illustrates how critical change management programs and strategies are for ensuring the many ancillary parts of an Enterprise 2.0-based network remain consistent and unified with one another (Kuettner et al. 2013). The integration aspects of these networks can be attributed to the network effect evident in many organizations that are lower on the continuum of the Enterprise 2.0 maturity curve (Trimi & Galanxhi 2014). By isolating the network effect and its role in bringing greater maturation into enterprise networks, each specific factor that drives greater maturity can be defined. Expanding on this approach to research has shown that all successful networks share a common foundation, and the role of technologies within social networks acts as an accelerator, provided trust and transparency have first been firmly established across all system boundaries (Dyer & Nobeoka 2000).

Progress Update

The project's direction shifted from being based on secondary research alone to being focused on a series of expert-level interviews with specialists in Enterprise 2.0 concepts and technology adoption. All experts were contacted, and several work at industry research firms including Gartner, a large American IT consultancy; Forrester; International Data Corporation (IDC); and several smaller consultancies located in the United Kingdom, including Ovum. Gartner and IDC offered to provide academic assistance in the form of responding to short questionnaires and allocating 30 minutes of analyst time. The constraint on these analyst calls was the time zone differences, and the analysts who are experts in Enterprise 2.0 were booked out into mid-December. Appointments were made with each available analyst, notwithstanding the risk that Gartner might cancel if a paying client required a specific time slot. Success was achieved in submitting questionnaires to leading experts at Gartner, IDC, and Forrester. Due to their willingness to participate at a minimum in a survey, the risk of not connecting with these experts was significantly diminished, and eight experts were successfully interviewed in time for their responses to be transcribed and incorporated into the study's findings.

The literature review continued with the goals defined previously. One of the most interesting threads found in empirical data concerns how communication, collaboration, and the use of technologies to accelerate them have long been relied upon in distributed supply chain networks created initially by Japanese and Asian manufacturers. Following the series of referenced studies and research foundations of Dyer and Nobeoka (2000), it is evident that the use of lean production techniques to orchestrate large, geographically dispersed supply chains holds lessons of value for companies attempting to galvanize diverse operations using social networks. The Toyota Production System (TPS) is predicated on a foundation of lean production techniques including Kanban, lean Six Sigma quality, and Just-In-Time production scheduling — all aspects of any manufacturing operation that are highly quantifiable (Dyer & Nobeoka 2000). In researching the foundational elements of how these supply chain networks were formed and continually improved, the catalyst of collaboration and frequent communication over mechanistic processes led to greater results (Dyer & Nobeoka 2000). The focus of this study was therefore on gaining as much insight as possible into how collaboration and communication in the context of proven social networks (supply chains) deliver financial and operational performance efficiently over time.

Appraisal and Reflection

This project demonstrated that only when a specific direction is chosen and committed to can meaningful progress be made. To vacillate is to fail; to be resolute is to succeed. Ironically, this is also the case with many of the most successful social networks that exist today — albeit they are called supply chains or supplier networks. One of the most enlightening aspects of this research is the fact that while social networks are heavily hyped and the subject of much commentary among intellectuals and practitioners, upon deeper reflection they share many of the same attributes as networks that have existed for centuries.

Ethics

The industry experts at each of the consultancies mentioned were contacted with ethical consent forms, and their legal teams reviewed them. Ensuring the ethical integrity of the study by abiding by the research firms' insistence that no specific analyst be singled out as the respondent was critically important. The research firms' primary concern was the confidentiality of their analysts and researchers.

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