One of the greatest challenges facing innovation professionals is to find the right approach to a given innovation problem. Whether that’s instilling the innovation mojo in a large corporation or simply helping teams become more innovative, the ways to do this seem to be more of an art than a science. However, during the last ten years there has been a strong push to turn this art form into more of a science.
Innovation governance can be thought of as a system of mechanisms to align goals, allocate resources and assign decision-making authority for innovation, across the company and with external parties. In this series of articles, professor Jean-Philippe Deschamps delves deeper into this topic; what is innovation governance, what different models are there and which ones seem to be the most effective?
Big data is a hot topic in the business press. Its promise of greater insights and efficiency, improved innovation and competiveness, not to mention income streams for the providers of data analytics tools are a rich source of discussion. Several recent developments indicate the power of using data analysis and statistics effectively to reach conclusions, and we almost certainly ‘ain’t seen nothing yet’ as big data techniques emerge. However, statistics do not necessarily tell the whole story and are open to radically different interpretations. That said, the power of numbers and modelling is rising.
Can we bring an open collaborative spirit to understanding, describing and prescribing innovation methods? Paul Hobcraft and Jeffrey Philips believe we can and that it will greatly simplify the innovation process.
We see a lot of programs being run in companies in the name of innovation. Of course some of the large corporations need to run innovation programs for name sake. They need some window dressing for analysts and industry observers lambasting the same for not being innovative enough.
How does your company deal with mistakes? If continuous learning from your employees, innovation and even breakthrough innovation are important to you, it is critical you embrace mistakes, at least as sources for learning and invention.
