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Thinking outside the box: how organisations need to learn

An organisation like GiLE is very interested in the future of education and soft skills training. This is as it should be. However, lifelong learning over a career will often involve contributing to the life of an organisation. Organisations have learning needs, too. But do they really know how to facilitate organisational learning? Is it easier said than done, or is there a knack to it?

 

Whatever stage you are at in your career, this topic matters. Organisational learning can positively influence knowledge creation, innovation and organisational performance (Abukhar et al. (2019) cited by Liu, 2020). When individual or team insights impact on organisational processes and structures, a transformation occurs (Liu, 2020).

 

A project evaluation review meeting

This article will explain how organisational learning takes place through looped learning cycles. Some conclusions will then be drawn.

 

Learning cycles

 

Learning cycles are key to organisational learning. The cycles are iterative, with feedback loops (Medama, Wals & Adamowski (2014) cited by Liu, 2020). Processes, actions, assumptions, values, rules and hypotheses may all be reviewed.

 

We will consider three types of cycle: single loop, double loop and triple loop learning.

 

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organisational learning single loop learning
Figure 1: Single loop learning cycle for Quality Assurance (Source: Liu, 2020 (adapted)).

Single loop learning

 

Single loop learning is a learning cycle in which errors are detected and corrected within an existing set of rules or norms. The underlying values of the system are not examined (Argyris (1978; 1999) cited by Liu, 2020). Once a pattern is established, it is repeated routinely.

 

If things are stable, this approach can be very useful for routine situations at an operational level. Figure 1 provides an illustration.

 

Single loop learning is useful; often organisations are good at it. However, no consideration of the bigger picture is involved. It is an isolated problem-solving cycle, a form of adaptive learning. Individuals adapt to the work to be performed (McClory, Read and Labib (2017), cited by Liu, 2020).

Double loop learning

 

So that is how single loop learning works. What makes double loop learning different?

 

The question is no longer “Are we doing things right?” but rather “Are we doing the right things?”

Double loop learning involves reflection on the organisation’s basic governing variables and if need be, correcting them (Matties and Coners (2018), cited by Liu, 2020). The question is no longer “Are we doing things right?” but rather “Are we doing the right things?” The standards, policies, procedures and objectives of the whole organisation may all fall under the scope of this (Kantamara and Vathanophas (2014), cited by ibid.).

 

Organisational norms and assumptions are reviewed. Double loop learning can have long-term positive effects – but it may involve dealing with considerable complexity and ambiguity. Often, a crisis situation brings it about (Liu, 2020).

 

Figure 2 depicts a simple example.

 

organisational learning double loop learning Global Institute for Lifelong Empowerment
Figure 2: Double loop learning cycle for product sales (Source: Liu, 2020 (adapted))
organisational learning triple loop learning Global Institute for Lifelong Empowerment
Figure 3: Single, double and triple loop learning compared (Source: http://www.infinitasinternational.com/)

Triple loop learning

 

Double loop learning involves critical thinking: issues and problems are reframed. What can triple loop learning add to this?

 

The question now is “How do we decide what is right?”

 

With triple loop learning, new processes and methodologies are introduced to ensure that double loop learning occurs when it should. It involves reflexivity: the question now is “How do we decide what is right?”. It may result in transformation. The organisation’s governance norms, protocols, institutional structures and decision-making procedures may, at times, all change (Madama, Wals and Adamowski (2014), cited by Liu, 2020).

 

Figure 3 illustrates this.

Learning cycles in action

 

A well-run project might implement single loop, double loop and triple loop learning. In single loop learning, outcomes would be measured and evaluated at project milestones or gates. Lessons learned captured at these points would inform management action. At the end of the project, overall lessons learned would be recorded to inform future projects.

 

In double loop learning, the evaluation step would be broadened. Both the outcome and the appropriacy of the value it was meant to be measured against would be checked. If called for, project-level parameters, project processes and even the organisation’s policies might be changed. After that, a fresh comparison of the outcome with the new metric would be made.

 

Triple loop learning would take place at project close-down. At project level, performance data, closing reports and lessons learned logs would be reviewed and reported on. At process level, project targets would be reviewed with sponsors and if need be, revised. Procedures might be updated. Finally, at the organisational level, learning action plans for new projects would be generated. The relevant information would be passed to board level (Liu, 2020).

 

Summary and implications

 

Single loop, double loop and triple loop learning are all crucial to organisational learning. However, the higher levels of learning cannot exist in isolation. They can only co-exist with the corresponding lower levels (Liu, 2020).

 

What does this mean, then, both for organisations and for those who work for them?

 

Leaders in today’s organisations need to create space for debate and double loop learning to occur. They should be ready to be challenged. They should act on “lessons learned” or else escalate them to board attention. Fresh projects should only get the go-ahead once corrective action has taken place.  To achieve triple loop learning, you must close the loop.

 

However, the rest of us also need to take notice. To stay ahead of artificial intelligence, we humans need to concern ourselves with the variables governing our work. We should question processes that do not serve us well and insist that lessons learned be acted on. The appropriate approach is to be process-orientated, take a systems view, and be persistent.

 

References

Liu, S. (2020). Knowledge Management: An Interdisciplinary Approach For Business Decisions. Kogan Page Limited. Chapter 4.3.

Author:

Philip Jeffrey Saxon

Article Writer &  Proofreader/Editor

Philip Saxon GiLE Global Institute for Lifelong Development

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The opinions expressed in this article/publication are those of the authors. They do not necessarily reflect the opinions or views of GiLE or its members.

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