How to Effectively Apply Appreciative Inquiry in Developing Talent in Organizations

How to Effectively Apply Appreciative Inquiry in Developing Talent in Organizations

Mambo Mupepi (Seidman College, USA), Yalonda M. Ross-Davis (Seidman College, USA), Mark Davis (Self-employed Management Consultant, USA) and Thomas S. Vachon (Grand Valley State University, USA)
Copyright: © 2017 |Pages: 11
DOI: 10.4018/978-1-5225-1961-4.ch002
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Abstract

Focusing strictly on negative organizational issues could constitute an obstacle to the improvement of key attributes, products, and or services offered. This chapter suggests that Appreciative Inquiry (AI) can be an effective and efficient strategic tool used to lead positive change and improve the talent of the organization by emphasizing what is successful rather than a deficit. AI is a well-developed methodology of examining, defining, implementing, and executing precise pans of improvement by applying positive psychology which will lead to the revitalization of productivity. Furthermore, available data suggests the employees within the organization can become resistant to change when there is an overemphasizing of the shortcoming areas of weakness. By using the AI assessment and evaluation technology, companies can pin-point and materialize desirable change.
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Introduction

Business entities in the 21st century are continuously faced with complex challenges that affect nearly every aspect within their organizations. In order to thrive in this modern environment, businesses are required to build the capacity necessary to progress the operations. Cooperrider (2012) provided an updated review of what Appreciated Inquiry (AI) can do when he asserted that the methodology is an innovative technique useful at building capacity in organizations. This paper considers an alternative change management technique hinged on the pragmatic ontology of AI with the goal of developing talent in organizations. All companies are designed around specific goals, where entities strive to hire talented individuals to play exact roles in the production of goods and services valued most by customers. In addition, they understand social constructs (such as AI) as techniques that can be applied to pin-point the exact change needed to operate successful organizations. AI seeks to identify sources of change that will build on past successes and core organizational values. This identification happens through a process of recognizing positive attributes and sources of pride within the organization, rather than problems or challenges (Elsbach, Kayes & Kayes, 2016).

Background

AI has been used successfully world-wide to introduce and manage change. Leading consulting organizations such as Tim Rowe Price, and Booze Allan, among many others, have employed AI to grow the wealth for their clients. Leading business schools incorporating change management curricula have also adopted positive psychology in their curricula to build their students’ capacity in the real world. Moreover, AI can help enhance understanding in many ways and enable organizations to build better futures.

What is Appreciative Inquiry?

What’s working well? What isn’t working? Although these two questions are often difficult to answer, they ultimately underline the difference between traditional Change Management Theory and Appreciative Inquiry (AI). Traditionally, in American Business conventional wisdom has led us to believe that improvement is the product of a series of identifying a problem, applying a diagnosis and developing a solution. The fundamental error of this theory is that problems are inevitable and that exposing them may lead to an overemphasis and amplification of them, hence having a negative impact on the mental processing on the talent within the organization. AI on the other hand seeks to identify sources of change that will build on past successes and core organizational values. This identification happens through a process of recognizing positive attributes and sources of pride within the organization, rather than the problems or challenges (Elsbach, Kayes & Kayes, 2016).

AI’s inventors, Cooperrider & Srivastva (1987), suggested that AI is a universal (for all types of entities) model for analysis, decision-making, and the creation of strategic change. The technique at Case Western Reserve University by Cooperrider and Srivastva who felt that the overuse of “problem solving” as a model often held back essential analysis and understanding focusing on problems and limiting the discussion of new organizational models.

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