Commercialising Innovation - scaling tech start-ups

Innovation and innovative people are spread evenly around the globe. But there is more of an uneven challenge to bring products and services successfully to market. Many times this is due to a lack of resources or funding and sometimes a lack of a supportive ‘community’. Hence all the ‘Silicon Geography’ models dotted in countries around the world.

However, despite many potentially ‘disruptive’ technologies and propositions, it is often the inertia of the marketplace, aided by the dominance of major players, that holds back the commercial success of technically interesting ideas and concepts.

Perhaps there is another way to tackle this market challenge?

It is an old adage oft-quoted in a now dispersed Californian hotshot open systems hardware company (Sun Microsystems), that the key is not to be first to market, but first to volume.

This requires momentum. The technology, and crucially connectivity, available to today’s tech start-ups removes much of the friction and permits web scale growth, but they still need to focus on ensuring that commercialisation will scale as well.

DevCom 5

Perhaps the Agile and DevOps approaches to software development can offer some alternative thinking to help commercialise technology innovation and more rapidly scale? Here are a set of steps to consider:

  1. Keep the value chain short. If an innovation relies on aligning the agendas of too many organisations, it is going to get bogged down. The term ‘herding cats’ is popular for a reason. Get a tight, small and supportive supply chain and over-collaborate within that team.
  2. Ensure everyone gets their cut. Companies used to talk about ‘money being left on the table’ and then try to make sure they picked it up. This is a short term win from an accounting perspective, but rapid scaling of the value chain needs fuel. Make sure that all involved are sharing the revenues fairly.
  3. Deliver real value at the end (user). How do you know? Check. Get feedback, encourage interaction between users, accept what comes back and learn and adapt. “Lessons will be learned” rarely are in large monolithic institutions, but successful rapid scaling operations learn constantly.
  4. Innovate in rapid cycles. It is a worthy goal to get it right first time, but who knows what ‘right’ really is? Customer research may help at times, but only if the context is well understood. Being able to develop, test value to customer, refine and re-release allows innovative improvement to align most closely to customer needs. Innovation for its own sake is rarely going to bring in sufficient rewards to match the effort involved. Technology companies often try to out-innovate each other, when in reality they should be trying to be ‘most relevant’ to customer requirement.
  5. Automate to scale. Once the innovation/value cycle is gathering pace, accelerate the process by optimisation. Look for the opportunities that deliver most speed up and gain over the whole cycle, rather than within themselves. Halving a 24 hour configuration process is nowhere near as valuable as a 20% reduction in a 2 week deployment process. Take a holistic and systemic approach.

Using this model of tightly-focussed teams, innovating rapidly and delivering customer value is not just for small start-ups. The two pizza guideline employed in Amazon (any team should be small enough to be fed by two pizzas) seems to be at the heart of what has helped it to experiment, learn and scale rapidly since July 1994.

Perhaps there is something in the approach?

Data Center
Data Management