Anyone responsible for managing knowledge in an organization needs to develop a game plan or strategy for doing so. This provide guidance on what needs to be done and why it is necessary. Without a business strategy, a business cannot grow as intended. Likewise, without a knowledge management strategy, attempts to optimize knowledge cannot proceed as intended.
We may be clear of what a business strategy entails. However, a lot of uncertainty surrounds the development of a knowledge management strategy. What should such a strategy comprise of? How do we begin developing one? Who should be involved in its development?
How can we get funding for such a strategy? These are very pertinent questions that need to be addressed.
Answering these questions maybe done systematically through the adoption of a simple three step approach that involves;
The 4th Industrial Revolution has revolutionized the way society functions and the nature of work itself. We witness staggering changes it has brought and are left wondering how to deal with this new phenomena. This article provides a glimpse of what has transpired and how to navigate around this bewildering episode called the 4th Industrial Revolution.
This revolution has brought in its wake, a blistering array of new technologies such as artificial intelligence (AI), automation, Big Data, and the Internet of Things (IoT). These technologies have indeed to a large extent improved the quality, speed, or price at which value is produced. We have new discoveries made in the field of genetics and a huge vista of business opportunities opened to people who have ventured to capitalize on the new value propositions available.
Communication is the process of sharing knowledge. Effective communication requires an understanding of how knowledge should be shared across various knowledge boundaries that exist when silo-based mentalities manifest.
Essentially, three knowledge boundaries exist in any organisation: syntactic, semantic and pragmatic. These three boundaries are explained through increasing magnitude of difference, dependence and novelty. Understanding these concepts allows an organisation to better manage knowledge sharing specifically in the new product development process and, arguably, in any circumstance. This saves time and money while ensuring accuracy and satisfaction.
At each boundary, there is some level of difference, dependence and novelty. The 'difference' here refers to a difference in the amount of knowledge and/or type of knowledge. Dependence is the connection of different knowledge to accomplish a task. Novelty is how different the knowledge is from what is currently known. For example, a front-end and back-end engineer will have a difference in what programming languages they know, their knowledge is dependent on each other to create a website and there will be some novelty as they move between different projects that have different requirements. These three parameters would change in magnitude were we looking at a back-end engineer and marketer.
The first major boundary is syntactic. In short, this is the language (defined broadly) that each person speaks. Every role in an organisation has its own jargon and common lexicon, even more if cultural differences are
involved. Syntactic boundaries make knowledge transfer difficult as there is no common lexicon. Thus, to solve syntactic boundaries, a common lexicon must be developed. This is not to be underestimated; it may take more effort than it initially may seem. For our engineer and marketer, they need to develop a common set of words to communicate with each other.
This leads us to the next boundary: semantic. Having a common lexicon is a great first step but now there must be a common, shared understanding to avoid misinterpretation. Semantic boundaries focus on translating knowledge. Here it is crucial to make implicit knowledge explicit. “It is not just a matter of translating different meanings, but of negotiating interests and making trade-offs between actors”. To solve semantic boundaries, common meanings and interpretations must be developed. The engineer and marketer must develop a common understanding of their lexicon – this can require making new agreements. Essentially, this is exploring meaning. Boundary spanners can act to mediate people in conflict here – spanners can be people, activities, or processes.
Lastly, the pragmatic boundary. Sometimes a common lexicon and understanding are still not enough because of conflicting interests between people. Pragmatic boundaries look at how shared meaning is transformed into the actual product/service. To solve pragmatic boundaries practical and political effort is needed. Here the engineer and marketer must work through their specific interests in the project to create a common interest. Boundary objects such as prototypes, drawings and wikis can be helpful because they are malleable enough to change but solid enough to define a direction.
Any activity in an organisation with more than one person has these knowledge boundaries. A clear understanding of and attempts to minimize syntactic, semantic and pragmatic knowledge boundaries allows for effective knowledge sharing, correct outcomes and satisfied people; this is an iterative process that will get better the more a team works together.
In our previous article, we explored how optimizing knowledge processes enables organizational transformation from a culture of blaming towards a culture of accountability. A key lesson learned was that only with active involvement of all parties involved, facilitated through knowledge management practices, can such a situation come to fruition.
Recently, we have been discussing an idea suggested by Forbes that Knowledge Management facilitates decision making, enables the building of a learning organization, as well as creates a culture of knowledge sharing and innovation. In this segment, we focus on the intimate relationship between better decision making by leaders and knowledge management at a personal level.
In order to make high-quality better decisions in volatile and highly uncertain and complex business environments, three requirements need to be fulfilled. The first is the ability to undertake assumptions analysis. The second is the ability to suspend unilateral perspectives in favour of multiple perspectives when attempting to understand the situation and complication being faced. The third is the ability to make a decision that meets the short-term, as well as long-term, aspirations of all stakeholders involved.
In highly complex and uncertain business environments, leaders have to rely on their gut feel and intuition to decide on the best way forward. They are forced to decide based on limited, changing information and make assumptions on what other issues impact their proposed decisions. This was an acceptable practice in the past but is not the case anymore. Today, the volatility and extremely complex interrelationship between different elements of the business environment renders the tendency to assume a very risky option to undertake.
To minimize the risks associated with making incorrect assumptions, leaders need to identify and acquire critical information either through the association of people who have relevant experience or be able to intelligently analyze data to guide and assess the assumptions they make. As a result, the knowledge acquisition process needs to be optimized through enhancing the ability to connect with people who have the necessary expertise at short notice and the expertise to analyze information intelligently.
Rapid and significant changes have become commonplace occurrences these days. There have been cases where what appeared to be the “obvious” decision to make from a leadership standpoint, led to a nightmarish outcome. A case in point is the decision by Nokia to downplay the advent of Apple’s iPhone. According to Nokia leaders at that time “such a phone will not go far” in 2007, led to the demise of Nokia’s leading position as a cell phone retailer.
With the complexity and interdependency of technological start-ups, including the advent of artificial intelligence and advanced robotics, boundaries of technological developments are becoming increasingly blurred. Under these circumstances, where leaders are limited to their current level of superficial understanding, within the confines of a limited point-of-view, when making critical decisions. Given their limited comprehension of the unprecedented evolution of technology that is unfolding before them, we clearly need a more effective means of making such critical decisions.
The only way to make better decisions in such situations is through the production of knowledge that broadens the understanding of the emerging business environment. This requires the involvement of all stakeholders in terms of sharing and producing knowledge on a regular basis. This will over time, enable development of a more holistic and multi-perspective view of issues. These perspectives shared and discussed amicably through dialogue using Knowledge Management techniques such as the Knowledge Café will go a long way in extending options available to leaders in dealing with issues that are ambiguous in nature.
Balancing short and long-term needs of stakeholders
In general, the thinking process of people involves perceiving what is happening, and from that perception, developing an understanding of how what is happening, affects the well-being of the person, followed by making a decision on what to do, based on the level of understanding the individual has achieved.
When this is done by one person, such as a leader who has to decide on the next course of action, his or her perception may be clouded by inaccurate or incomplete information that could lead to a superficial understanding of the situation and complication inherent within it. Consequently, the decision made may be suboptimal and at times disastrous. This is by virtue of the fact that all stakeholder considerations were not made and the decision most often is based on good short-term returns without considering long-term implications of these decisions.
To mitigate the negative outcomes of a wrong decision and to minimize the possibility that sub-optimal decisions are made, leaders need to develop a knowledge management capability that optimises the process of acquiring the correct knowledge from the right stakeholders at the right time, producing a holistic, shared understanding of the situations and complications involved from all relevant stakeholders and based on such an understanding be in a better position to make better decisions.
Making a reasoned, well thought out decision that can affect stakeholders wellbeing is dependent to a large extent on minimizing the consideration of unverified assumptions and adopting a unilateral, superficial understanding of issues. Such a decision has to be premised on the need for internalizing concerns and welfare of stakeholders involved both in the short and long term.
If this is done as a matter of routine, then such an approach to decision-making is deemed to have been integrated into the decision-making process adopted by leaders in the organization. Developing and maintaining a well-oiled and thought out knowledge management approach as a catalyst for making the right decisions is certainly a step in the right direction.
You may have heard of brainstorming, but questionstorming?? Well this is apparently a new term being bandied around in knowledge management based circles. Let me share with you why this approach is gaining ground fast as a tool for acquiring knowledge that is required, when it is required.
Knowledge broadly refers to what is known. On a personal level, it refers to a fluid
mix of framed experiences, values, contextual information, and intuition that a
person has. This knowledge provides an environment for evaluating and
incorporating new experiences and information. Previously acquired knowledge is
the basis for learning. Learning in turn leads to acquisition of more knowledge.
We are truly now in the Knowledge Age, way past the Information Age. Faster information processing
has become less important compared to developing intelligence systems that will shape our future.
The technological advancement in robotics has been phenomenal and so has the advent of artificial
intelligence which has been spurred on by the concept of advanced robotics as well as the “Internet
of Everything”. These are exciting times where we are witnessing phenomenal growth in human
capability and expertise.
Knowledge broadly refers to what is known. On a personal level, it refers to a fluid mix of framed experiences, values, contextual information, and intuition that a person has. This knowledge provides an environment for evaluating and incorporating new experiences and information. Previously acquired knowledge is the basis for learning. Learning, in turn, leads to the acquisition of more knowledge.