LINQ: Kaizen for Knowledge Manufacturing

Kaizen – Good Change

Kaizen means ‘Good Change’ in Japanese (Kai = Change; Zen = Good) and has come to mean the practice of continuous improvement within an organisation.

Kaizen originated in Japan post second-World War and came to international attention through its application in Japanese car manufacturing in the 1980s and has subsequently been applied to manufacturing in every country, every sector.   The productivity gains have been substantial and obvious.  What is less obvious is the increase in innovation being driven by empowered workers.

From Wikipedia:

Kaizen is a daily process, the purpose of which goes beyond simple productivity improvement. It is also a process that, when done correctly, humanizes the workplace, eliminates overly hard work (“muri”), and teaches people how to perform experiments on their work using the scientific method and how to learn to spot and eliminate waste in business processes. In all, the process suggests a humanized approach to workers and to increasing productivity: “The idea is to nurture the company’s people as much as it is to praise and encourage participation in kaizen activities.”

In the information sector, the use of Kaizen and its Kanban foundation is typically restricted to software development projects.  Even then, implementation has been patchy and is nowhere near as holistic as is seen in the Toyota Production System of car manufacturing for example.

Knowledge Manufacturing

To date, Kaizen has not been seen as a tool to improve Knowledge Manufacturing.  Indeed, the very term Knowledge Manufacturing requires some explanation.  Here at LINQ, we explore the flows of information from source data to decision support knowledge within an organisation.  These have parallels to the supply chains that fuel manufacturing.  We call these information flows “Information Supply Chains” and set them into the context of manufacturing knowledge within an organisation.

An Information Supply Chain starts with the capture of raw data either within our own organisation or by a supplier of information.  That raw data is transformed by processing actions to derive information which is typically transformed several more times before being delivered to the decision support application – potentially in a customer organisation.

Knowledge Manufacturing is something that almost every organisation does; we all need a flow of information to ensure that we are making strategic and operational decisions based on timely and relevant data.

Whether financial services, government department, transport company or property management, every organisation, large or small relies on Information Supply Chains to deliver information to decision makers and yet they don’t know it.  If pushed, they’d perhaps say that they were reliant upon Information Technology (IT) but would struggle if asked to describe that reliance and the impact on their people, customers and suppliers.  That’s mainly because the description of IT would be highly technical and thus inaccessible to most people.

LINQ describes an organisation in terms of Knowledge Manufacturing using an accessible language which allows non-technical leaders and workers to understand the potential for improvement. LINQ helps appreciate the role of Knowledge Workers and Systems in enabling the Information Supply Chains.  We clearly depict the relationships between an organisation and its information suppliers and customers. Typically, there’s a lot of room for improvement in efficiency, effectiveness and engagement.

Improving Knowledge Manufacturing

So why does Knowledge Manufacturing need improvement?  For the same reasons that car manufacturing needed improvement before lean/Kanban/Kaizen revolutionised that industry.  Today, we see Knowledge Manufacturing dominated by command and control styles of hierarchical management, low productivity and unrewarding jobs.  Change is implemented with large projects, poor resource management, bottlenecks and resultant overloading of people.

Indeed, the intangible nature of information makes the pre-Kaizen ‘Knowledge Factory’ a high risk environment.  The consequences of component or even system failure are not always immediately visible but they are impacting the most important resource an organisation has:  the ability to make informed decisions based on facts.  Ironically, the mitigation of the perceived risks through the use of waterfall styles of change management can amplify the hidden risks of poor decision support, poor productivity and limited innovation.  We see the results of change process failure in headlines reporting yet another IT project disaster.

How LINQ Enables Kaizen for Knowledge Manufacturing

LINQ provides a Kaizen framework by doing three key things:

  • Seeing the current state of Knowledge Manufacturing in an organisation quickly, easily and using an accessible language that everyone can understand
  • Solving efficiency and effectiveness challenges in the current state in small, manageable change batches (projects) that lend themselves to Lean / Kanban management approaches
  • Sharing this information across the organisation in order to bring the transparency needed to support innovation and continuous improvement; Kaizen

Kaizen in manufacturing realised tremendous productivity gains; of the order of 50% or more.  But Kaizen also devastated those manufacturers that couldn’t or wouldn’t adopt Kaizen.  From our prototyping of LINQ, we know that Knowledge Manufacturing within your organisation will see similar productivity gains from the use of Kaizen to improve the efficiency and effectiveness of Information Supply Chains.  The corollary of this is that those organisations that fail to adopt LINQ will see their competitive advantage erode rapidly.

If you want to find out more about how LINQ could enable Kaizen in your organisation, please click below to download our white paper.

Download the LINQ White Paper