The innovation flywheel is a concept associated with Amazon. Jeff Bezos cites it as his methodology behind the development and success of the company. Essentially it involves experimenting with a new idea, testing it on a small scale to see if it works and then if it does scaling the concept up and continuously refining it as the organisation grows. This concept has led to Amazon achieving the accolade of being one of the largest companies in the world and making Jezz Bezos the richest person in the world.
However, the concept is now reaching an age where it is being re-imagined because of a changing business context. The modern commercial enterprise IT environment is now one dominated by the management of data for the development of customer insight. At the operational level the deployment of deeply embedded autonomous systems is becoming the norm in many large organisations and this trend is beginning to trickle down to small and medium sized enterprises as well.
In this new business context, the innovation flywheel is beginning to take on new meaning. It now means that the first step is gaining freedom from legacy based systems which are not capable of integrating into the cloud or creating data fluidity. The second step is transitioning to a managed services model of IT operations and data management. This second step lays the foundation for access to the benefits the modern take on the innovation flywheel can provide. Those benefits are self-sustaining business momentum, higher levels of customer insight and higher levels of operational efficiency and effectiveness.
The third step is to modernise the data warehouse. This is important because the new way of doing data warehouse management is a big upgrade on legacy ways of thinking about this issue. Modern data warehouse operations incorporate on demand computing with an elastic supply of processing power and storage. This means you only pay for the computing resources you actually use instead of having to have an oversupply of computing resources available.
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