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This blog post is based upon the work undertaken with with a global FMCG organisation.

‘Kaizen’ is a Japanese word term for continuous improvement. In order to maintain a healthy, business aligned and valuable knowledge platform, there is a need to have clear alignment across all knowledge sources on an on-going basis, for a typical large organisation this can be spread across:

• Knowledge
• Collaboration
• Enterprise Social.

For the purpose of this blog post, let’s assume that these services will be delivered by SharePoint (knowledge and collaboration) and Yammer (Enterprise Social) and yes I know that there is cross-over between those platforms.

Experience shows that the area that will reap most value from continuous improvement is:

• Search
• Meta Data.

For the purpose of this post we will be looking at Knowledge from an Information Governance perspective and focus the scope on proactive management and maintenance of meta data.

Conceptually, knowledge kaizen is all about monitoring and taking appropriate actions on emergent behaviour and meta data within the solution.

In this case we have multiple technical solutions and knowledge classifications which need to be aligned in order maintain an element of consistency across the multiple platforms, support user adoption and maximise business value.

In the diagram above, we can see at the lower levels, we have a mix of open, ad-hoc collaboration predominantly through Yammer, elements of SharePoint and other solutions such as perhaps an ideation platform or other social business tools.

At this level there exists a multitude of loosely coupled knowledge ‘things’:

• Technology solutions
• Thoughts
• Ideas
• Ad-hoc collaborations
• Information
• Social interactions
• Data
• Innovations
• Knowledge assets.

A subset of these will move on to be collaborated on, within the collaboration platform, involving more people and further evolving the knowledge ‘thing’ until it becomes usable and actionable knowledge that has clear value.

At this point the knowledge artefact becomes more structured.

Finally, for those items where there is significant value, they will emerge to become formal knowledge items and are ‘promoted’ into the formal knowledge solution and proactively managed within this context.

Across all these three layers there is should be a recognised value for the information, data and knowledge held within them.

This value can be categorised in three ways:

1. Formal knowledge
2. Informal knowledge
3. Emergent knowledge.

All of this knowledge can be consumed from two primary viewpoints:

• Standalone Knowledge – Knowledge that is navigated to or retrieved by search and is considered valuable knowledge on its own.
• Contextual knowledge – Knowledge that is automatically surfaced (system) or retrieved by search (user) that supports, adds context or adds further value to a piece of Standalone Knowledge.

In order to maximise the value of knowledge across all the layers we will require a process to ensure that the knowledge is:

• Appropriate
• Valuable
• Fresh
• Business Aligned.

This process must be appropriate to continually align the knowledge across the three very different areas and an emerging set of technologies.

This knowledge kaizen is represented in the context of the following:

• Content Types
• Enterprise Content Types
• Enterprise Keywords
• Meta Data
• Managed Meta Data.

Emergent behaviours should be proactively managed and applied “up” from Enterprise Social and the Collaboration layers and into the formal Knowledge layer.

Likewise, more formal concepts are applied at the knowledge and even the collaboration layers, driven by:

• Governance boards
• Business requirements
• Knowledge and organisational Vision.

These should in turn be proactively applied, where appropriate (conceptually and technically) down through to the Enterprise Social layer.

Fundamentally this process facilitates platform alignment from both a business and technology implementation perspective.

On-going internal continuous improvement should also happen at each specific level to maintain and/or remove content types and meta data that are no longer appropriate or require adjustment in line with business requirements and vision.

This is a complex and emergent process that is best articulated with a sketch:

As can be seen in the diagram above kaizen is achieved by the following process:

1.       Seeding the Enterprise Social ‘Topics’ within Yammer

2.       Influence from existing Governance (Boards, content etc.) within Yammer and SharePoint

3.       Providing in-line guidance across all three knowledge areas within Yammer and SharePoint

4.       Proactive manual mapping and maintenance activities within Yammer

5.       Community activities (community managers, emergent behaviour etc.) within Yammer and SharePoint

6.       Reporting and Analytics within Yammer and SharePoint.

Practically, we can start to facilitate continuous improvement, at each of the information and technology layers in the following ways:

Knowledge (SharePoint)

• Proactive maintenance and engagement from a Knowledge Centre of Excellence
• Changes distilled via the Knowledge Governance Boards
• New business requirements
• Changes to the Vision
• Emergent behaviours (Suggestions, Search analytics, Open Term Sets, Enterprise keywords)

Collaboration (SharePoint)

• Proactive maintenance from a Knowledge Centre of Excellence
• Changes distilled via the Knowledge Governance Boards
• On-going Community Management
• New business requirements
• Changes to the Vision
• Emergent behaviours (Suggestions, Search analytics, Open Term Sets, Enterprise keywords)
• Adding emergent meta data from the ‘Enterprise Social’ platforms as synonyms to the formal meta data
• Maintaining Content Types to support business requirements, changes in vision and facilitating the creation of formal knowledge.

Enterprise Social (Yammer)

• Renaming ‘Topics’ to be in-line with the meta data contained within both Knowledge and Collaboration areas (SharePoint)
• Seeding Enterprise Social ‘Topics’ by the addition and on-going proactive maintenance of a Master ‘document’ with all recommended ‘Topics’ (i.e. key meta data tags) driven down, as appropriate, from the Collaboration and Knowledge platforms (SharePoint)
• Creation of guidance (socialised) for the ‘types of content’ (including visibility, templates etc.) that are recommended to be used within Enterprise Social
• Mapping and proactively managing terms by extracting to Excel from Yammer, adjusting and aligning appropriately with the enterprise meta data from Collaboration and Knowledge platforms (SharePoint)
• Maintaining Content Types to support business requirements, changes in vision and facilitating collaboration
• On-going Community Management.

Care must be taken when ‘manually’ aligning meta data and content types across technology platforms and knowledge layers to ensure that the correct and valid context and meaning is assumed.

It has not gone without due consideration that the above activities are time consuming, fairly manual, infinite and a pretty rough approach to knowledge kaizen, across information types and technology platforms.

But if you don’t do this then you will be delivering SharePoint Celery, platforms and information types, will become very divergent and the inherent value and purpose of knowledge management will ultimately be lost. 

I hope that future releases, integrations or even 3^rd party tools for SharePoint and Yammer will start to automate these alignment principles, but for now it’s up to you, I’m trusting you not to ignore this and be proactive…

Go Kaizen your Knowledge!