Principles of Innovation Actually Applied in Practice
I was having coffee with a management consulting friend when we got into a discussion about the best practice principles that underpin good corporate innovation activities. During that discussion I Googled “McKinsey Innovation” as I was curious to know what the global thought leader had to say on the topic (go ahead and do the same, I’ll wait). Here’s the top link for that search The Eight Essentials of Innovation. After reviewing the list and reading the article I felt underwhelmed, as this was a list of abstracted verbs not anything essential or even tangible:
- Aspire
- Choose
- Discover
- Evolve
- Accelerate
- Scale
- Extend
- Mobilize
I’ve decided to compile my own list of best practice principles in corporate innovation that can actually be applied in practice.
These following concepts are not groundbreaking insights to any rational individual, but I find them often overlooked by senior corporate innovators and leadership. This list is inspired by a mosaic of codified best practices in building startups and technology, as well as lessons I’ve picked up from over a decade of my experience spanning investment, startups, and innovation.
When being innovative you are doing or creating something new. When doing something new, as humans can’t predict future outcomes, uncertainty and lack of information dictates that the chances are that you will be wrong more often than you are right. This is why venture capitalists have a portfolio of bets, knowing that not all investments will be successful.
To reinforce these principles below I have included excerpts from Jeff Bezos’ 2014 Amazon Shareholder Letter and an article from Nassim Taleb, former derivatives trader and Author of Fooled by Randomness, The Black Swan, and Antifragile:
“Failure comes part and parcel with invention. It’s not optional. We understand that and believe in failing early and iterating until we get it right. When this process works, it means our failures are relatively small in size (most experiments can start small), and when we hit on something that is really working for customers, we double-down on it with hopes to turn it into an even bigger success. However, it’s not always as clean as that. Inventing is messy, and over time, it’s certain that we’ll fail at some big bets too.” — Jeff Bezos
“A rigid business plan gets one locked into a preset invariant policy, like a highway without exits — hence devoid of optionality. One needs the ability to change opportunistically and “reset” the option for a new option, by ratcheting up, and getting locked up in a higher state. To translate into practical terms, plans need to 1) stay flexible with frequent ways out, and, counter to intuition 2) be very short term, in order to properly capture the long term. Mathematically, five sequential one-year options are vastly more valuable than a single five-year option.” — Nassim Taleb
Principle 1 — The heart of innovation is experimentation and learning.
As Eric Ries, Author of The Lean Startup would say (borrowed from the Scientific Method) “Build — Measure — Learn”.
Principle 2 — When experimenting, you will be wrong more often than you are right. Uncertainty and lack of information dictates you can’t predict future outcomes.
“Failure comes part and parcel with invention. It’s not optional.”
Principle 3 — There is information in both failure and success. A failed experiment should be seen as buying learning and avoiding further costly mistakes. Pre-mortems, post-mortems and a strong feedback loops are also required as part of the “Build — Measure — Learn” process.
“We understand that and believe in failing early and iterating until we get it right”
Principle 4 — Have a portfolio of cheap experiments. As venture capitalists understand very well, not all investments payoff. Having a portfolio of cheap experiments means when an experiment fails you are wrong by a little and have other options for success.
“When this process works, it means our failures are relatively small in size (most experiments can start small)”
“under some level of uncertainty, we benefit more from improving the payoff function than from knowledge about what exactly we are looking for. Convexity can be increased by lowering costs per unit of trial (to improve the downside)”
“A large exposure to a single trial has lower expected return than a portfolio of small trials.”
Principle 5 — Double down on your winners. Be wrong by a little and right by a lot.
“when we hit on something that is really working for customers, we double-down on it with hopes to turn it into an even bigger success.”
Principle 6 — Maximize the frequency of iteration to adjust strategy and increase the rate of learning. Experiments need to be long enough to learn something, but should be short enough to maximize frequency of iteration: the more iterations, the more feedback loops, the more you learn in a shorter period of time.
“stay flexible with frequent ways out”
“five sequential one-year options are vastly more valuable than a single five-year option.”
Principle 7 — Balance speed and risk. By reducing the scope of an experiment, you can reduce the downside risk if the experiment fails, as well as increase the frequency of iteration and speed of learning.
Principle 8 — Use a barbell strategy — A barbell strategy is used by financial derivatives traders to balance short-term protection with long-term speculation. If an innovation strategy is only focused on long-term results (e.g. 5 years out or flying autonomous cars), as budgets tighten it gets harder to justify your budget to the CFO after two years with no tangible results. Innovation departments should balance solving short-term business problems and generating tangible ROI, with protecting the business against long-term macro trends.
Principle 9 — White space allows for positive black swans and non-obvious solutions. The uncertainty in an experiment can also yield a positive unexpected outcome.
“Some results offer abnormally large benefits from discovery; consider penicillin or chemotherapy or potential clean technologies and similar high impact events (“Black Swans”). The discovery of the first antimicrobial drugs came at the heel of hundreds of systematic (convex) trials in the 1920s by such people as Domagk whose research program consisted in trying out dyes without much understanding of the biological process behind the results.”
“Further, research payoffs have “fat tails”, with results in the “tails” of the distribution dominating the properties; the bulk of the gains come from the rare event, “Black Swan”: 1 in 1000 trials can lead to 50% of the total contributions — similar to size of companies (50% of capitalization often comes from 1 in 1000 companies), bestsellers (think Harry Potter), or wealth. And critically we don’t know the winner ahead of time.”
This is not an exhaustive list, but when these principles are combined into a cohesive innovation strategy they can yield very effective results.
