In many industries, innovation is the only way to capture market share, and innovation means using existing knowledge to the organization’s benefit. In the subsequent article, originally published on KM Review (Vol 8 Sept. / Oct. 2005) and adapted from her book Managing Innovation, Design and Creativity, Bettina von Stamm explains how KM contributes to innovation through informal networks, experts databases and idea management. The article is part of our series from the archives. We hope to reinforce the discourse on leadership and innovation and to reflect on what has changed since the first publication of the article in 2005. You can download the PDF version here.
- Networks are important for innovative projects because it is often not possible to identify what kind of skills will be needed in the course of the project at the outset.
- Informal networks are “owned” by individuals, and when these individuals move on, so does their knowledge. Downsizing and restructuring can severely disrupt informal networks.
- Minimizing the impact of the destruction of informal networks through redundancies and retirement is one reason why managers engage in knowledge management.
- Keeping track of ideas, what happens to them, why a certain idea is selected, and why others are rejected can provide a powerful trail that helps understand an organization’s innovation projectory
Informal networks are part of the jigsaw that makes an innovative organization. It’s about knowing who to go to when you need a particular bit of information or a particular skill, who can do a particular job for you – or who is the right person to influence decision-makers. At the BBC, it was Mike Milne’s web-based discussion groups that helped to find people with the right skills and attitude. At Black & Decker it was Lawrie Cunningham knowing that Nigel Robson would take a design task and turn it into something really exciting. Here we will look at the role of informal networks for innovation and the way managers attempt to formalize such information networks; this is where we enter the territory of knowledge management.
The reason why informal networks are so important for innovative projects is that it is often not possible to identify what kind of skills will be needed in the course of the project at the outset. Therefore, being able to find the right skills if and when required can be essential.
There is one issue in particular that affects informal networks: they are “owned” by individuals, and when these individuals move on, so does their knowledge. In the past, informal networks have been severely disrupted when round after round of downsizing and restructuring has taken out layers of middle management – those people who often know who knows what in the organization – and has allowed experts to leave. People close to retirement with a vast body of tacit knowledge acquired over their working life, and those who can easily find new jobs elsewhere – specialists and experts – are the ones most likely to take up redundancy and early retirement offers, leaving gaping holes in informal knowledge networks.
Managers come only slowly to realize the value of informal networks, and the consequences of destroying them. One consequence of a nonfunctional informal network can be the hiring of external expertise even though the skills required might readily be available in-house. As managers have become increasingly aware of the value of such informal networks, many organizations are now seeking to put infrastructure in place that aids the capture of such knowledge. Expert databases are one way of capturing people’s areas of expertise. Hodgson (1999) has identified the following advantages of such databases:
- Elimination of rework and duplication of effort by linking together individuals working in similar areas;
- A reduction in cycle time and costs through quicker resolution of problems;
- Increased transfer of best practices.
However, she also points out that managers establishing such a database must be clear about its purpose. Is it an experts database or a skills database that’s needed? A list of other questions to be asked before setting up an experts database are shown in the sidebox, below right. Hodgson describes an experts database as selective, assuming that some people have more knowledge than others, due to their education and/or experience. Such a database is used to create networks and linkages between different parts of the organization. Hodgson also suggests that expert databases can facilitate the elicitation and sharing of tacit knowledge. A skills database, on the other hand, is more inclusive and can provide information on just about anyone in the organization. Hodgson suggests that such a database would generally be used by the human resources department to identify personnel for project teams on particular job placements. In my view, the problem with the experts database is who actually identifies the experts. While Hodgson suggests five possible avenues (see sidebox, p. 30), I would argue that it is sometimes the most unlikely people that have some relevant experience, and this may only be known by a few. Another reason for being more inclusive, especially in the context of innovation, is that you may not be aware what kinds of skills you may need for an innovative project. Giving people the opportunity to provide insights into skills and expertise, areas of interest and involvement in past projects (possibly even outside work) will ensure that everything employees have to offer can be harnessed. However, this means that the database can be quite large, which makes good, easy-to-use search facilities absolutely necessary. One example is BP, who have successfully introduced a knowledge management database. Before we go deeper into why the management of knowledge is important, and what companies can do about it, let us have a brief look at what “knowledge” actually means. Knowledge is distinguished from information and data in that an interpretation is applied to it. This also means that knowledge is something that is developed by individuals, and that the quality of the knowledge in question depends on that individual’s insights and expertise.
The ability to access tacit knowledge is very important – but there are also problems associated with it, as Quintas et al. (1997) point out. “Lots of what employees know (their tacit knowledge) reflects the past that we are trying to escape.” This means that existing knowledge can often hold innovation back. If people are too aware of constraints, of what is possible and what is not – or rather, what they consider to be possible or not, based on their previous experience – they might miss great opportunities to innovate. It is those who believe that the impossible is possible, despite what everyone is telling them, who are the great innovators.
Minimizing the impact of the destruction of informal networks through redundancies and retirement is one reason why managers engage in knowledge management. But there are other reasons why organizations striving to become more innovative should consider a formal knowledge management process. Innovation happens when making new connections, connections that have not existed before – applying laser technology to fix eye problems, or using microwaves to heat food. In his report on the Second Comparative Study of Knowledge Creation Conference, held in June 1998 in St. Gallen, Switzerland, Rumizen (1998) uses the Unliever case study as an illustration of the fact that “Many organisations are beginning to recognise the need to manage knowledge assets to meet business needs” (see sidebox, p. 31).
The capture of “who knows what” has become one important aspect of knowledge management. Another aspect is the need to store and make available any information on past and current projects, and in a way idea management can be classed as another aspect of knowledge management. In fact, I would suggest that all major stages of new product development should be covered in a company’s approach towards KM:
- Idea management (from idea generation to idea selection);
- Development and review;
- Commercialisation and monitoring.
IT IS THOSE WHO BELIEVE THAT THE IMPOSSIBLE IS POSSIBLE, DESPITE WHAT EVERYONE IS TELLING THEM, WHO ARE THE GREAT INNOVATORS.
Idea management involves the storage of ideas generated in focused sessions as well as those coming from more spontaneous sources, perhaps through ongoing suggestion schemes. Keeping track of ideas, what happens to them, why a certain idea is selected, and why others are rejected can provide a powerful trail that helps understand an organization’s innovation projectory. Keeping information on ideas that have been rejected as well as those that have been selected is important for two reasons. Firstly, when the same or a similar idea comes up again, it is possible to check why it has been rejected previously, and whether the reasons for rejection are still valid. Secondly, ideas that do not fit within an organization’s innovation strategy might still be great ideas, which means that the organization should investigate whether they can be sold off. The example of the Xerox lab comes to mind; this enterprise generated many significant inventions but did not convert the potential into benefits for the organization.
Development and review
Once ideas have been chosen for development, there is again great value in tracking their progress. What went right and what went wrong during the development, and why? What lessons can be learned and how can they be fed back into future projects? It’s at this stage that the experts or skills database comes in handy. Who has been working on similar projects who has the right skills? Quick access to such information at any time during the project can save a lot of time and money (particularly if it helps to avoid buying in outside experts). Finally, while most organizations are getting better at generating data and information on projects due to the use of the Stage-Gate process (though often this is not stored in a systematic and easily accessible way), it seems true that most organizations could increase their learning by undertaking “post mortems” of those ideas that have not made it to market.
Commercialization and monitoring
But even once the product has been introduced to market, the learning is not over. What is the reception in the market? How does the product or service perform? Is there anything to be learned from competitors’ reactions? Are sales or market shares targets met? And so on. Despite powerful arguments for the use of knowledge management, many organizations struggle with it. Systems are put in place but aren’t used. The most frequently used arguments as to why companies are not engaging more in the active management of their knowledge asset is a lack of time. However, my question would be, is it not more time-consuming not to manage knowledge, and to repeat mistakes and spend time and money on finding the right skills if and when needed?
However, there are also some challenges for the database-based management of knowledge, such as:
- How to ensure consistency of the quality of information inputted into the system;
- Providing guidelines on what kind of data is to be entered;
- Training people to use the database; one company asks people to sign a “code of conduct”;
- How to keep information up to date and relevant;
- Ensuring that time is scheduled for maintenance and upkeeping tasks;
- Appointing a dedicated database manager;
- How to make sure that learning and insights are fed back into future projects;
- Scheduling consultations on the database during the early stages of a project’s development;
- Closing projects properly – a review of activities and issues should be undertaken.