The 20th Century was defined by Humanity’s control of atoms. The material abundance we enjoy today is unfathomable to those only just a few generations ago. Organizations’ dominated by their ability to acquire, process, and distribute atoms using economies of scale. The name of the game was all about dollar cost averaging investments through greater output. With the invention of computers and later the internet we are in the middle of a second shift where organizations today dominate through their ability to acquire, process, and distribute knowledge at scale. Unlike atoms, knowledge is far more dynamic, requiring organizations to maintain a high innovation velocity, but what does this mean?
Innovation should not be confused with incremental improvement. Improvement focuses on existing elements to reduce waste or defects and increase quality or customer satisfaction, while innovation focuses on developing what has yet to exist. For instance, in the era of flip phones (buttons and simple display), greater impact resilience would be considered an improvement, and a full display touch screen would be considered an innovation. While control of atoms at scale has not gone away, it is more about how these resources are used. Nearly bulletproof, dirt cheap flip phones can be produced in the quantity of billions, but in the era of smartphones, we would not consider organizations that continue to develop and produce cheap flip phones as thriving businesses or industry leaders.
Velocity is described as a rate of change of an object’s position with respect to a frame of reference over time. For the purpose of this blog, let’s consider an organizations’ position as a representation of its knowledge. Innovation Velocity represents how quickly new knowledge can be derived from ideas validated outside the organization. To remain competitive, not only do organizations need to innovate but do so at an increasing velocity.
Many of the great ideas and practices that allowed us to master the realm of atoms can be used to foster innovation into your organization. The Lean Manufacturing movement has much to teach us. Here are some Lean Manufacturing principles that we will use as examples for improving Innovation Velocity:
- Limit work in process
- Reduce batch sizes
- Reduce the number of handoffs
In a factory it was commonly thought that idle equipment missed revenue, so parts were intentionally churned out until there was no more space left to store inventory in process. Excess inventory in process would effectively slow the entire system down as too many resources were allocated to the wrong stations. To limit work in process, it is important to make sure that all work being done in the organization is visible and being prioritized. Providing a productive team with more of the same work can cause issues in other parts of the organization. The same goes for batch sizes, if a particular has a defect, the larger batch size will result in significantly more re-work, slowly the system. The greater number of handoffs introduces not only delays in execution but also delays for feedback to move upstream. Many large projects with numerous independent actors impede knowledge generation. Therefore, consider forming small teams responsible for owning a metric, product, or feature. Then give them the latitude to innovate autonomously, with the team dissolving once a goal has been reached. Or have the team be permanent, but over the product’s lifecycle, acting as support instead of handing off these responsibilities to another group. The greater number of handoffs introduces not only delays in execution but also delays for feedback to move upstream.
Another area in which Innovation Velocity can be accelerated is through the organization’s culture. A “blame culture” within an organization is the Innovation Velocity equivalent of pulling the hand brake. In some firms, employees are punished for mistakes, which incentivizes behaviors that cover-up mistakes and avoid responsibility. Innovation within these environments is extremely challenging as innovation requires experimentation and risk taking. Likewise, the results of any experimentation are likely questionable as unfavourable results are ignored or deleted further weakening the effectiveness of the innovation pipeline.
Fostering a dynamic, disciplined, and scientific approach to experimentation and risk-taking is the goal. Information is actively sought out, messengers are not shot but trained, responsibilities are shared, collaboration between teams is encouraged, failures trigger exploration, identified problems are swarmed, and new ideas are welcomed. It is important to note that inconclusive results are still valuable results. Organizations that perform ten experiments and fail nine out of ten times will acquire knowledge at a far greater velocity than a competitor that was successful with a single experiment.