We need the engagement platform for translating big data learning

Knowledge BuildingBig Data is knocking very loudly on our door, how are you going to let it in and manage it?

How can we liberate that creative energy we have within our organizations, how can we achieve higher engagement?

How can we learn, share and transform the knowledge that is all around us, simply flooding in? How can we translate the data flowing in with the knowledge insights and innovation outcomes expected? How are we going to unleash the creativity that goes with new knowledge?

We need to actively encourage connected minds for value-creating opportunities and knowledge sharing for innovation to flow right across the organization. All the raw data needs connected and engaged minds.

“For this, we need to think about installing a modern engagement platform that has the knowledge and learning as its beating heart”


Why do we need to build this modern engagement platform? Big Data is knocking on your door.

We need increased capacity to ‘listen and capture’ understanding. We need to deploy some filtering and analytics as ‘big data’ becomes increasingly part of our organization’s lives. We need to go beyond analytics.

“We urgently need a system of absorbing and translating data’s raw power to turn these into measurable innovation outcomes”.

We need a structured system where we manage any absorption of data through its different stages of translation into valuable knowledge, to see its potential and then to realize the (new) value out of it for new innovation outcomes.

With all this new data flowing in, you need to turn it into valuable knowledge by capturing all the interactions, offering search and discovery services, organising different events and scenario management and be able to retrace the interaction history. We need to think beyond just data discovery.

“We need to equally build a knowledge-sharing system and this will require as much a robust technology solution as at the raw data front end structured on a scalable learning approach”.

We need to find ways to merge data and information to turn this into ‘actionable’ knowledge and eventual valuable new innovation. We do need to think harder about building beyond analytics into these engagement platforms.

It is here you actually mine the raw knowledge and transform it. We need to absorb in our organization’s capabilities or we will simply overload them with just data.

We need to shift from scalable efficiency to scalable learning.

Firstly and most important for me, is our need to understand the building of learning and experiences through the Absorptive Capacity framework as I think it will have an increasingly valuable part to play in managing data, information and knowledge going forward.

A fair time back two researchers, Cohen and Levinthal (1990) pioneered the concept of absorptive capacity, further defined as the ability of an organization to identify, value, assimilate, and apply new knowledge.

Since their 1990 publication, the concept has been further developed and given rise to many thousands of published papers on this subject.

The Absorptive Capacity Components
The Absorptive Capacity Components

The value of absorptive capacity is that when organizations have some prior knowledge and awareness they are more receptive to adding new understandings and new ideas. They can build better value from not just the knowledge but the structured application of it.

“As ‘big data’ grows we need to move from potential to realized outcomes”

Organizations that encourage and set about learning consciously and consistently will set about the search for the new ideas coming from all the incoming sources by having this already established learning structure in place. They are far more likely to better recognize new ideas that might lead to innovation.

Exploiting our learning requires framing

I would suggest those organizations that exploit the Adaptive Capacity framework are more likely to develop a deeper understanding of integrating, exploiting and experimenting with any new knowledge. Then they are in that ‘better’ shape to set about placing the data and knowledge gained into a new setting, framing new concepts or hypotheses, to push this knowledge forward into new innovation.

“We need a structure where we are constantly, consciously advancing learning, extracting its value, turning this into valuable new potential and successful innovation outcomes.”

Adoption Capacity 1
This gaining of continuous knowledge encourages constant learning and this has a positive feedback cycle as it builds the capacities and capabilities for future innovation activity for the increased potential for new value.

Absorptive capacity, once recognized and established as a system, promotes the search for new knowledge that greatly increases the capacity to make the necessary new connections for new innovation to happen.

The ability within our knowledge gathering needs a continuous focus and methodology of approach.

For this to happen, it does need continuous focus, we need to build greater absorption capacity. If organizations take the alternative route of wanting to squeeze every last drop out of the existing innovation activity or research department, organizations over time develop as bad learners, they begin to ignore, assume they have the knowledge and get fixed in their mindsets.

They totally rely on data and don’t apply their knowledge and they fail to translate this into meaningful outcomes.

Those that fail to seek out and absorb, will certainly tend to reject faster and increasingly adopt the “not invented here” syndrome. That can only last for a limited time before ‘innovation decay’ and ‘data overload’ do set in, people become frustrated and finally give up and leave, and when they do just remember all their knowledge goes with them also.

“There is a real risk that all the incoming data can be totally overwhelming, we need to structure a learning system to absorb, exploit and translate for measurable innovation outcomes”

In managing new innovation outcomes we need to apply absorptive capacity as a learning framework

We certainly understand that today innovation is not confined to the walls of one particular company. The world ‘absorbs’ more innovation than we can turn into greater value but we need to attempt to capture this and see if and where its value might lie.

If we agree that most innovations happen outside often self-imposed boundaries then we have to extend outside all our existing boundaries and go beyond. We have to open up our organizations and collective minds to draw in the knowledge so as to allow it to reside, circulate and be translated into new forms of understanding.

Absorptive capacities give us the system on which we can encourage the gathering, understanding and translation of knowledge. It underpins engagement and also helps manage the ‘raw knowledge data’ that needs transforming. We all need to be able to have ‘syncing’ capabilities of learning.

We need a system to capture and allow knowledge to flow, and a strong absorptive capacity has three main outputs which result from the flow of external or distributed knowledge that is allowed to flow internally.

“With the creation of new knowledge and insights, these can create new innovation that then leads to new economic and social value”

Achieving a clear engagement platform for all to gain from

So in our need to achieve a greater engagement from everyone within our organizations we need to recognize the importance of having a ‘modern’ engagement platform available, a central place for scalable learning to take place so we can structure the new knowledge and insights coming into the organization.

As we increasingly need to engage, where outside knowledge combines with our internal understanding and needs, then we do need to think about scalable learning to anchor and then diffuse new knowledge into potentially more valuable innovation outcomes that are measurable and linked back through the learning cycle.

Share

2 thoughts on “We need the engagement platform for translating big data learning”

Comments are closed.