It is essential to invest in assessment to provide robust evidence that can inform policy and programming decisions. Evaluation helps in decision-making and policy formation by offering feedback based on evidence. An evaluation may be defined as the systematic assessment of a project, program, or policy to give feedback for programmatic improvement. It helps determine what works well for whom and in what context, and what can be enhanced or scaled up. In addition to the definition and aim, several assessment procedures may be used; this blog will focus on one of these evaluation approaches termed appreciative inquiry.
An evaluation method is a philosophical or conceptual strategy for evaluating. It specifies the ideals and concepts the assessment should conform to and may also be viewed as the lens through which evaluators view a project.
Appreciative Inquiry (AI) is both a concept and a method for utilizing the skills and experiences of everyone in a project or a system to create the desired feature of a project or system. It is especially effective in instilling energy and hope while recognizing the need for change. It focuses the attention on essential questions, such as where we wish to go and how we will get there. Positive, contextualized, and pragmatic AI allows the institution to evaluate its working environment using a basic, outcome-based process. This strategy is advantageous since it can be implemented in every aspect of the workplace, from team meetings to large-scale initiatives. Hence, AI serves as both an implementation and evaluation approach.
For AI to be effective and produce substantial change, it must consist of many phases. Even with individuals you have never met, it is essential to establish a vision and consider the larger picture early on. Even a large group would quickly learn they have a lot in common.
Next, people should be gathered to determine what has worked in the past and the factors that led to its success. It helps contributors discover beneficial accomplishments and techniques for working for the future. This information is transferred from discovery.
The dream phase is then used as a platform for guessing likely or desired futures and translating major motifs into declarations of strategic and social purpose. The significance of this phase, sometimes known as the dream phase, rests in the links between where individuals wish to go and what they wish to bring with them. Then, participants co-construct a new reality based on the dream phase utilizing direction principles and a strategic framework
During the design phase, we ask what would be ideal, how we might make it work, and what conceptual or operational modifications would be necessary to ease the process. The accomplishments of the process are validated by monitoring the journey on the team’s program. Using observational data to feed the process constantly, the provisioning phase describes how the change will be delivered and how it will spark a cultural revolution within the organization.
In addition, it is essential to note that stakeholder participation and two-way communication are key to the success of a program’s development phase. Assessing progress against the initial objectives and any possible changes that may occur along the road, we identify and assess results to maximize advancement opportunities while solidifying the foundation upon which transformational change happens.
Utilizing AI offers the medium for organizational growth by building a continuous maturity model that places culture at the centre of performance enhancement. It is a resilient and adaptable approach to companies that places individuals at the change process’s centre. It implies that AI praises humanity in all its splendor. Our emotional nature and various experiences and origins are genuinely recognized and cherished.
AI is a truly people-centered organizational development methodology and is effective because it is founded on psychological knowledge of people, group relationships, and how individuals construct their operating environment. It is referred to as social constructionism, which states that through our interactions and conversations with one another, we form the social reality in which we live. As an approach to organizational change, AI offers various advantages since it focuses on the people inside the business and helps everyone to feel that they are a part of the change and have helped co-create its ideas. It is also incredibly motivating since employees are involved from the very beginning in recognizing the best of what’s occurring right now and the organization’s true resources.
As an evaluative strategy, AI also has potential drawbacks, such as the possibility of losing focus on design and execution failures. In addition, because it is predominantly qualitative, it may not be able to address the question of casualty.
On the other hand, AI can be explored further since it works well with other methods, such as quantitative approaches. It can also be applied to a specific program component when the objective is to identify the factors that contributed to the successful implementation of the program.
Bushe, G. (2007). Appreciative Inquiry is not about the positive. OD practitioner, 39(4), 33-38.
Coghlan, A. T., Preskill, H., & Tzavaras Catsambas, T. (2003). An overview of appreciative Inquiry in evaluation. New directions for evaluation, 2003(100), 5-22.
Cram, F. (2010). Appreciative Inquiry. Mai Review, 3(1), 1-13.
Reed, J. (2006). Appreciative Inquiry: Research for change. Sage publications.
Kultar Singh – Chief Executive Officer, Sambodhi