Month: May 2020

The great digital pioneer Dr Douglas Engelbart coined the term ‘Collective IQ’*. He identified five key concepts behind raising Collective IQ – Networked Improvement Community (NIC), Dynamic Knowledge Repository (DKR), Concurrent Development Integration and Application of Knowledge (CoDIAK), Open Hyperdocument System (OpHys), and Bootstrap. In his vision, the application of these concepts enhances society’s ability to solve complex, large-scale problems. In an organisation, the value of these concepts is their potential to enhance the organisation’s capabilities to deliver quality products and services to customers, to support innovation and adaptation, and to enrich employees’ work experience.

Networked Improvement Community (NIC)

Engelbart’s concept of a Networked Improvement Community or NIC is one in which a group of electronically connected people with a common purpose use technology cooperatively to tackle the complex problems that they jointly face. They work together to better understand their problem-space, to unearth the best candidate solutions, to decide how best to deploy operational resources and capabilities, to monitor progress, and to adapt effectively to unforeseen complications.
For organisations, the NIC concept is an evolution of the ‘team’. It raises a team’s profile from one in which the members are focused on cooperatively performing a fixed set of tasks to one in which they are also focused on sustaining and improving both how the team works and its outcomes.

Dynamic Knowledge Repository (DKR)

A Dynamic Knowledge Repository or DKR is an online location or ‘container’ in which knowledge is stored, utilised, and developed through direct user interaction. By ‘knowledge’ here is meant codified knowledge, that is, information held in discrete, human-viewable, files that contain text, pictures, diagrams, illustrations, sound recordings, video recordings, etc., or some combination of these.
It is dynamic in the sense that its content is constantly updated by the members of a NIC, who ensure that at all times it is comprehensive, accurate, coherent, authorised, accessible in multiple ways as to the purposes it serves, and linked and marked up in ways that make it explorable in meaningful and useful ways.

CoDIAK

CoDIAK stands for Concurrent Development Integration and Application of Knowledge. It is the concept that you do not ‘stop in order to learn’. The processes used to improve capability should be integrated with, or even identical to, those used to support current action. This has the double benefit of fuelling learning via immediate feedback, and quickly implementing newly devised improvements. DKRs, when properly implemented, are key mechanisms for integrating and applying new knowledge. They also provide the base on which new knowledge can be developed.

Open HyperDocument System

Open Hyperdocument System or OpHys is an ambitious technical challenge set by Doug Engelbart to create a new electronic document format and associated application systems for recording, sharing, retrieving and linking information in a much more effective and collaborative way.
As a general rule, enterprises at the moment tend to manage the documents that contain their corporate knowledge in a fragmented and ad-hoc way. In addition, existing technologies, which are inexpensive and ubiquitous, tend to be underutilised. This is mainly because of a continuing ‘paper bias’ in the way documents are stored and managed.

Bootstrap

Bootstrap or Bootstrapping is the notion that raising Collective IQ potentially operates on three levels, with the upper two levels aimed at boosting or accelerating learning capacity. On the first level (level A), raising Collective IQ increases the capacity to solve specific real-world problems and carry out complex tasks. For example, the problem or task might be how to design and produce a new model car.
The second level (level B) focuses on improving the methods and processes used to improve level A processes. To continue our example, this might involve looking at the way new model cars are designed and produced in general to come up with a better overall approach.
The third level (Level C) focuses on methods and processes used to improve Level B processes. In our example, this might involve improving the way manufactured goods in general, not just cars, are designed and produced.
These levels have implications for the nature of the NICs involved. For our examples above, level A would be addressed by a NIC comprising people working in a motor vehicle company’s design and engineering function. Level B, on the other hand, would require a NIC with representatives from all the motor vehicle company’s key functions (manufacturing, inventory, finance, sales, etc.). For Level C, a NIC involving people from multiple manufacturing companies, academia, and professional societies, not just motor vehicle manufacturers, would be required.
The latter also highlights one of the key aspects of Collective IQ in Engelbart’s view and that is to address complex problems at a societal level that transcend the interests of individual organisations. In the case of our example, working together on improving general new model design and production methodologies benefits all manufacturing companies without impacting their relative competitiveness.
In Engelbart’s words, the essence of bootstrap is “The better we get at getting better, the better and faster we’ll get better.”

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*
Engelbart, Douglas C (1995) “’Toward augmenting the human intellect and boosting our Collective IQ” Doug Engelbart Institute (http://dougengelbart.org/pubs/books/augment-133150.pdf)

When a person looks for knowledge to support their work, they do it in response to their circumstances and the problems or difficulties facing them. This means that knowledge needs to respond to questions such as, “What do I do if (a certain situation arises)”, “What do I do when (a certain event occurs)”, “How do I (complete a certain task)”, “How can I understand how (a certain set of activities inter-relate)”. Consequently, knowledge needs to be classified and presented in a way that provides direct answers to these sorts of questions.
The common characteristic of these ‘knowledge-seeking’ questions is that they relate to people’s activity. They relate to what they are trying to achieve in their jobs and, by extension, for the organisation. The most useful basis then on which to classify knowledge is around the way the enterprise is structured to achieve its purpose – in other words, its ‘business model’.
This begs the question as to whether the organisation has clearly identified and articulated what its ‘business model’ is. It needs to do this first before it can provide a useful context in which to develop and utilise knowledge.
The essential theoretical groundwork for this task was thoroughly prepared by Michael E Porter with his concept of a “value chain”*. Porter’s analysis was focussed on the means by which organisations secure competitive advantage. We can apply the concept to managing the knowledge that supports, maintains, and improves this competitive advantage. By applying this value chain model as the conceptual context for developing and utilising organisational knowledge it is possible to link knowledge directly to the task of maximising value. This approach has the additional advantages that the value chain’s primary and support function categories:

• define the areas of the organisation that need to be covered by knowledge
• align with the way many organisations naturally divide their activity into specialised functions – this allows employees to locate relevant knowledge through their familiarity with its work context
• align broadly with the way management responsibility is allocated within an organisation – this makes it easier to identify who needs to take responsibility for curating the knowledge concerned

Porter’s value chain provides an effective overall context in which to develop and utilise knowledge. It provides the foundation for a dynamic taxonomy for organisational knowledge that ties directly to the organisation’s purpose. As a component of Collective IQ, this is the framework in which ‘atomic units of knowledge’ can be both developed and deployed.

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*
Porter, Michael E (1985) “’Competitive advantage: Creating and sustaining superior performance’, The Free Press

The idea of knowledge packaged as an ‘atomic unit’ was first suggested by Michael H. Zack*, who stated “… knowledge-as-object becomes knowledge-as-process. The basic structural element is the knowledge unit, a formally defined, atomic packet of knowledge content that can be labelled, indexed, stored, retrieved and manipulated.”
This ‘atomic unit of information’ needs a name or label to support its use as a fresh form of information currency. For this, organisations can leverage a concept developed and refined by the technical communication profession. As part of their transition to increasing digital distribution and management of technical information, they coined the term ‘topic’, which is defined as “a title and content that is short enough to be specific to a single subject or answer a single question, but long enough to make sense on its own and be authored as a unit”. Qualifying this concept to cover just information about organisational activity, gives us the term “Business Information Topic” or BIT.
Replacing policies, procedures, and work instructions with BITs not only breaks down out-dated cultural influences, but knowledge resources can be built so that they are much better suited to digital communication and interaction.
Individual managers can begin to raise the Collective IQ of their teams immediately simply by abandoning conventional approaches to writing policies and procedures and, instead, use a topic-based approach. As a manager, this means:

• changing your mindset from ‘command-and-control’ to ‘knowledge sharing’
• writing to address specific tasks or circumstances and how best to handle them (by combining all the relevant elements of policy, procedure, and instruction)
• employing a writing style that is easy to understand and engage with (this means using the active voice and other ‘plain English’ techniques, as well as following the Behavioural Insights* precepts of ‘simplify’ and ‘personalise’)
• developing the content collaboratively with team members
• enabling and actively encouraging team members to provide feedback, criticism, and improvement ideas
• using the documented information as a basis for common understanding, coordinated action, and collective improvement

Making these changes immediately improves the capacity for written information to bind and focus a team.

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*
Zack, M. (1999) “Managing Codified Knowledge” Sloan Management Review, Volume 40, Number 4, Summer, 1999, pp. 45-58

Nudging the world toward smarter public policy: An interview with Richard Thaler McKinsey Quarterly June 2011