Sharing Knowledge – The Power Of The Collective

First, it’s important to understand how knowledge operates, so that we can set up the right context for sharing it. 

Tacit knowledge (TK) encompasses the knowledge that we find difficult to explain and is usually gained from personal experience. Tacit knowledge in the workplace is what we often lose when a long-term team member leaves without some form of knowledge offload. It’s about the unspoken, the infrequent, the nuanced, and the short cuts that we learn cognitively. It is built upon context and familiarity.  

Explicit knowledge (EK) on the other hand is easy to record and hand over. It refers to sets of instructions or any information that is objective, logical, technical and codifiable. EK can usually be clearly documented. 

Unsurprisingly, sharing tacit knowledge presents the biggest challenge for organisations.  

Knowledge sharing has been defined as the “exchange, transfer and dissemination of knowledge between and among individuals, teams, departments and organizations.” This can include identifying problems and their potential solutions. Knowledge sharing is typified by certain kinds of behaviours: listening and asking questions, sharing ideas, and problem solving.  

Knowledge management systems and transfer processes are ways of formalising the flow of this sharing and can shine a light on any knowledge hoarding or withholding. Historically, knowledge hoarding has been a behaviour that is underpinned by the belief that “knowledge is power”, and that limiting who has access to it will in some way increase that power. It fits with dated and reductive mechanistic thinking and siloed practices that operate through the scarcity lens of old power paradigms. 

Associated, but not the same, is the rather more unintentional issue of dark data. Dark data refers to the unused, unknown, and untapped data generated by an organisation’s user interactions. It can be a vastly wasted resource that falls outside the vision of the big data managers.  

So how do we harness our understanding of knowledge and knowledge transfer to build a richer, more efficient knowledge sharing culture? To begin with, organisations could benefit from becoming more intentional about their knowledge sharing spaces. We know, for example, that ‘tacit’ knowledge transfer benefits from several spatial approaches: 

1. Physically shared spaces – proximity and visibility provide a sense of belonging and facilitates the “stickiness” of tacit knowledge. We know this implicitly and empirically about human communication, so where possible, we should optimise it. 
2. Technically shared spaces – because virtual meeting and groupings (Zoom, Skype, Teams) or conference spaces (Gather, etc.) can bring geographically separate colleagues together, it contributes to the potential volume of explicit and tacit knowledge sharing. If curated thoughtfully, these spaces will remain an important factor in a knowledge sharing culture.  
3. Cognitively shared spaces – these spaces exist when we share language and common understandings. They are non-hierarchical, dynamic, and innovative, and are “critical for converting tacit knowledge into explicit knowledge.” 

The anatomy of knowledge sharing is destined to reshape in the future in response to the evolving way people learn. We can already see shifts in this over the last decades. According to futurists, recent generations exhibit these differences: 

• Baby Boomers – are verbal and like to be told how to do things 
• Gen X – are visual learners who prefer the idea of “niche” everything 
• Gen Y – are capable of toggling between visual and verbal. They want everything to be democratised, collaborative and experiential  
• Gen Z and Alpha – are the “natural healthy hackers” who simply want to “do.” They learn through the use of symbols and haptic (physical) experiences. Hashtags are instinctively their language 

As leaders of younger teams, how we package (our language and symbols) and present (which modality we use) knowledge will impact the success of how that knowledge is shared, retained, and actioned. By developing an understanding of how this might need to vary depending on the age and background of our team members, we can proactively support the process. 

This may also include the possibility of incentivising knowledge sharing. Importantly though, research suggests that incentivisation is only successful if the team members receiving the knowledge help determine the reward. If the reward is decided by a leader separate to those involved in the transfer dynamic, the incentive does not appear to carry. This suggests that trust is central to the transfer exchange. So, “giving employees a say in who gets rewarded, and how, is key to incentivizing the sharing of knowledge.” 

By becoming curious about knowledge sharing, we can become more strategic. Start by asking: 

• Who should be involved in the knowledge transformation process? 
• How do we best present that knowledge for optimal learning/exchange? 
• How could we incentivise it?  
• How do we encourage knowledge management participation? 

And for leaders looking to farther horizons, consider the impending data storage crisis. Science is currently looking for storage alternatives that are ethical and sustainable such as DNA data storage. What implications would such a radical information storage option have on how we extract and exchange knowledge? 

Our ways of knowledge transfer are set to revolutionise, and this can’t help but impact not only how we share it, but also how we apply wisdom to what we know, and operationalise all this knowledge?