Learn Fast Innovation
Our Innovation Framework
Learn Fast Hypotheses-driven Innovation
We design and build rapid data science, artificial intelligence and next-generation technology powered prototypes and pilot systems governed by our learn fast hypotheses-driven approach to innovation, and supported by researchers, designers and engineers in our open innovation hub.
1. Define Hypotheses
The first step to successfully transform a great idea into a great product or service is to define an initial set of testable hypotheses. This will become the backbone of your innovation lifecycle and provide the basis from which you can evaluate and measure success.
2. Gather Baseline Data
To effectively test your hypotheses and measure success, and to help secure future investment post-protoype phase, you will need to identify and gather suitable baseline data that describes the current environment that exists without your product or service.
3. Design and Automate
A rapid design phase is critical to reduce the risks and costs of innovation. This means designing interoperable and ethical services, and making use of open automation technology as much as possible so that you can concentrate on the exciting bit - building your product!
4. Develop and Demo
Now that you have done the hard work, the fun bit can start - building your product or service. Use open source technologies and interoperable standards by default, and showcase your blossoming product to your customers to get them excited and for feedback.
5. Deploy and Monitor
Once you have a functioning product or service, deploy it into a real-world but managed environment. And most important of all, gather customer feedback and monitor its operational usage and performance in preparation for evaluation.
Qualitatively and quantitatively analyse the managed operational usage and performance data, and customer feedback, against the baseline data in order to test your initial hypotheses and to prove that your product or service is a success and ready for future investment.