Google’s 9 Principles of innovation

  • Innovation, not instant perfection
    Start rough, learn and iterate.
  • Ideas come from everywhere
    Ideas can come from the engineers, managers, users even the financial team.
  • Share everything you can
    Everything is put on the intranet, so employees know what is happening.
  • You’re brilliant, we’re hiring
    Founders Larry Page and Sergey Brin approve hires. They favor intelligence over experience.
  • A license to pursue dreams
    Letting employees use 20% of their time on what ever they want.
  • Data is apolitical
    There is no “I like”, it is all about the basing decisions on data.
  • Creativity loves constraints
    Engineers thrive on constraints.
  • It’s users, not money
    If you can successfully engage users, you can monetize them
  • Don’t kill projects, morph them
    Products that doesn’t seem to respond well in the market should be morphed into something the market needs, not cancelled

I can relate to these principals, some more then others. There are especially two I find quite intriguing, “A license to pursue dreams” and “Data is apolitical”.

A lot of companies would probably be scared to let their employees spend 20% of their time on anything they want, because they would fear that they might slack of and not produce anything of value to the company. The interesting thing is, that 50% of all released products from Google come from the 20% that employees spend on there own. In a world where the costs of producing something is cheaper in places like Asia, we in the western world have to differentiate our self by being more innovative. So it might be a good idea to consider if one could (should) apply the Google model or something similar.

I have had the pleasure of sitting through various meetings (usually it’s about design decisions), some good and some less productive once. One thing they have in common is that, at some point, someone will state an argument that begins with “I like..” and then you know things starts to get bad. Arguments based on personal preferences and not data is bound to heat up any discussion.

“Besides wasting time, these arguments create tension and erode respect among team members, and can often prevent the team from making critical decisions.”
Steve Krug, Don’t make me think

Even though this seems obvious to anyone, it stills occur too often, so it is nice to see that Google has build a culture that acknowledge the importance of data.

Marissa Mayer talks about the 9 principles at Stanford University

An interview with Marissa Mayer and the 9 principles

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5 thoughts on “Google’s 9 Principles of innovation

  1. CHAN KJ wrote:

    Arguments based on personal preferences and not data is bound to heat up any discussion. Exactly. This is dedicated to my Project Manager. It’s a slight deviance from “I LIKE” and probably a cousin which is “I FEEL”. My project manager is absolutely inept when he said “I feel this web apps is slow when loading” using his guts feeling. He was banished out of the meeting room immediately shortly after.
    1) he is incapable of backing his statement with profiling and benchmarking.
    2) He has forgotten the project triangle. Good,Cheap,Fast Choose Two.

  2. Ivan wrote:

    100 shades of blue = creativity definitely.

  3. Nice article. :)

    To me the point is not “I like” vs. data-based work. The point is that the “I like” argument must be backed up by many “I likes”: “we like”.

    Decision making is a number’s game. ;)

  4. While I would agree that it would be nice to have decisions based on “data”, we must not think that this “data” will come easily. Check out the discussion on quantitative project management in IEEE Software, May/June 2008 and a discussion of quantitative v.s. qualitative quality measures in the IEEE Software 2008 March/April.

    I think “data” is only useful when the cost of collecting the data is appropriate in the context of the decisions being made with it.

    Data must also be properly interpreted (Disraeli: There are lies, damn lies – and statistics.) And educated people should never be afraid of questioning interpretation of data.

    So, just because we don’t like endless discussions by “experts”, I think there is still a lot of room for design and implementation discussion that is based on “experience” rather than on pure numbers. E.g. can a benchmark show that an application is “fast enough” or does some just have to try to use it?

    My point is that while hard numbers are good and desirable, they enable discussions, rather than replacing them.

  5. Pingback: Culture Change | The WorkNET

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