Innovation and Knowledge Management

Innovation is the core process that results in the success of any organization. Innovation is of two types. They are

  • Closed Innovation
  • Open Innovation

Closed innovation is concerned with the development of new products through research and development process that is conducted within the firm. Closed Innovation is restricted within an organization. It concentrates on Knowledge Transfer within organizations.

Open innovation, controversially is concerned with the development of new products through research and development process that is conducted outside the firm. Open Innovation neither have restrictions within an organization, nor has geographical barriers. It concentrates on Knowledge Transfer across boundaries.

Though open and closed innovation may seem similar, there is a lot of difference between both of them. The following table illustrates the difference between both of them. This table was proposed by the management guru Henry Chesbrough, who is considered to be the founder of the term, “Open Innovation”.

Closed Innovation Principles

Open Innovation Principles

The smart people in the field work for us. Not all the smart people in the field work for us. We need to work with smart people inside and outside the company.
To profit from R&D, we must discover it, develop it, and ship it ourselves External R&D can create significant value: internal R&D is needed to claim some portion of that value.
If we discover it ourselves, we will get it to the market first We don’t have to originate the research to profit from it.
The company that gets an innovation to the market first will win. Building a better business model is better than getting to the market first.
If we create the most and the best ideas in the industry, we will win. If we make the best use of internal and external ideas, we will win.
We should control our IP, so that our competitors don’t profit from our ideas. We should profit from others’ use of our IP, and we should buy others’ IP whenever it advances our business model.

Table 1: Closed Innovation v/s. Open Innovation

Source: Chesbrough, H. (2006, pp xxvi)

Relating Innovation to Knowledge Management

Innovation Acceleration

Innovation acceleration is one of the hottest topics that are prevalent in all the organizations today. Innovation acceleration is nothing but enabling or promoting innovation process through efficient knowledge management. Innovation is vital to any organization and it is that knowledge management which makes innovation possible within any organization. It is for that reason, Knowledge Management is also known as Innovation Management.

Effective Knowledge Management ultimately results in effective Innovation. The following figure shows the relationship between Innovation and Knowledge Management.

Relationship between Innovation and Knowledge Management (Source: Mothe, J. (2001))

Relationship between Innovation and Knowledge Management (Source: Mothe, J. (2001))

It can be inferred from the figure that, Innovation could be achieved by connecting the ideas generated in human minds and that connection and coordination of ideas could be done only by efficient knowledge Management. As seen from the figure Innovation could be achieved from Knowledge management by incorporating the following steps:

  • Connecting the right people
  • Making collaboration easier among the right people
  • Stimulating meaningful conversion among the identified right people.

Thus innovation and knowledge management are closely related to each other and result in efficient functioning of an organization.

References:

  • Henry William Chesbrough, Open innovation: the new imperative for creating and profiting from technology, Harvard Business Press, 2006, pp xxvi
  • John De la Mothe, Dominique Foray, Knowledge management in the innovation process, Springer, 2001

 

Priya Chetty

Partner at Project Guru
Priya is a master in business administration with majors in marketing and finance. She is fluent with data modelling, time series analysis, various regression models, forecasting and interpretation of the data. She has assisted data scientists, corporates, scholars in the field of finance, banking, economics and marketing.

Related articles

Discuss

We are looking for candidates who have completed their master's degree or Ph.D. Click here to know more about our vacancies.