Lessons from Amazon’s Intentional Innovation
It’s always tricky deciphering attempts at innovation when we are looking in from outside of large enterprises. Timothy Lee helps us peel back some layers from some prominent examples in his post on Vox exploring How Amazon innovates in ways that Google and Apple can’t.
What are some of the key takeaways for anyone challenged with delivering growth through innovation inside their company?
- Know your innovation buckets
- Experiment regardless of experience
- Constrain early investment capital regardless of opportunity size
- Embrace fast failure to avoid epic failure
- Know your innovation buckets: If a product idea sits outside your core competency (Horizon 3 or Transformational innovations*) you need to manage teams, investment strategy and timelines differently than innovations associated with existing products and services (Horizon 1 or Core innovations*). Don’t box transformational ideas into the systems or corporate thinking you have set up to build your core product portfolio. For Amazon this means allowing teams to play with whatever tools make sense for the project rather than limiting them to the standard sandbox and the limiting assumptions that often brings with it. In a more general sense this means recognizing that the weight of uncertainty associated with a project operating way out on the edge of what is considered business as usual for a company, isn't for everyone. Some people and teams are simply better suited at handling that level of chaos than others. Embrace that distinction by developing a strong sense of what type of innovation you are dealing with.
- Experiment regardless of experience: Testing your assumptions reduces the risk that you will be seduced by historical but potentially misleading institutional knowledge, successes or failures. Surely the world’s leading retailer should know everything about selling stuff to consumers regardless of the context? Amazon’s approach forces it to recognize that it doesn’t have all the answers, all of the time. Automated Brick & Mortar grocery stores are a new enough product offering for the company, targeted at a new enough segment of the market, that the Amazon Go team needs to test whether the broader company understanding of consumer behavior remains true in this new setting for this new product with these new customer dynamics in play. For your company, make sure executives and product teams are asking the right questions at the right time and using relevant experiment methods such as MVPs to find the answers to the gnarliest issues.
- Constrain early investment capital regardless of opportunity size: Think big but start small. Just because an idea seems like a powerful opportunity doesn’t mean you should throw large barrels of cash in its general direction. Amazon sets up deliberate funding gates to give product teams the opportunity to prove traction to investment boards. This forced constraint doesn’t slow teams down at Amazon. It simply pushes them to operate with a hungrier mindset and avoid the mistakes illustrated by Google and others of allowing the depth of their resources to lull them into a push for more complexity. A key word in Lee’s commentary is “if”. The product team would get more funding if the experiments validated their current assumptions. At your company don’t get lulled into the sunk cost fallacy, throwing more money at a project simply because you have invested it to date. If the customer is telling you there is no value, turn off the investment sooner rather than later.
- Embrace fast, small failure to avoid slow, epic failure: The faster a team can prove that its guesses and dreams are grounded in reality rather than ego and ambition, the more confidence that team and its managers can have to push hard or rethink. Amazon’s discipline in forcing team is to start with one store, despite the fact that it has the resources to start with 50, stands in stark contrast to the bet the company “moonshot” approaches we see so often. The complexity of the challenge Amazon is taking on by bringing together so many elements of the shopping experience and sophisticated technology means that exposing the idea to the world at large won’t expose some precious IP. In fact there is only upside. The earlier it learns from real customers that one feature is unnecessary or fails, the easier it will be for the team to focus on what does work. The earlier it learns what is of high value, the faster it can double down in that area. Think for a moment of the product owner coming to an investment board to share the team’s latest progress. Far better to be able to report on a quick and dirty experiment to tell them “look at all the money we saved by not building out the expensive feature that it turns out no one cares about!’ than reporting on a 2 year $100MM investment for a phone no would would buy. Gulp.
At Spinnaker we are tightly focused on helping large companies grow through a Lean Enterprise approach and framework that mirrors many of these lessons. Join us in New York (Jan 24–25) or London (Feb 20–21) for our next public workshops on these topics.
Starting Your Lean Enterprise Transformation
Lean Enterprise Decision Making
(*see McKinsey and Najgi & Tuff for a deeper examination of the taxonomy around classifying innovation)
