To put a figure on this, McKinsey estimated in September 2018 that AI and associated technologies could potentially deliver additional economic output of around $13 trillion by 2030, boosting global GDP by about 1.2 percent a year.
Organisations that can embrace tech-led innovation and bring to market a steady supply of new products, services and efficiencies are most likely to come out on top. For most companies, innovation at enterprise scale is an expensive activity. A more cost-effective approach is needed.
It’s a Volume Problem
Keeping pace with tech giants, new market entrants and customer expectations requires continuous experimentation.
But as AI and advanced technologies (XR, Blockchain, IoT) continue to transform almost every task in every line of business, companies are under pressure to experiment with dozens of technologies across hundreds, if not thousands, of use cases.
Without the deep pockets of Google or Amazon, for example, is it sustainable to investigate every new idea, let alone develop meaningful prototypes? Particularly when most won’t make it to market?
Is it possible to respond to this challenge of innovation at scale? Where does work need to be focused? Is there a winning move?
Focus on Cost-per-idea
What if we could use tools and disciplined ways of working that can deliver products from conception to launch at a much lower overall cost?
It would be a bonus for the good ideas that have a successful launch, but the real difference is in the cost of the many others that didn’t make it.
This would enable a step-change in the number of ideas that can be tested and, ultimately, launched.
Democratising this ability to innovate at volume, previously the exclusive capability of some of wealthiest companies in the world, is a powerful and exciting idea.
BJSS has developed innovation practices that allow every organisation to thrive in a world changing at pace.
Start with a Falsification Funnel
What really disqualifies an idea? And how do you test that? We encourage clients to introduce a process that invests in generating ideas and discarding unworkable ones as quickly as possible. This is based on the asymmetry that it’s easier or possible to disprove a hypothesis, than to prove it.
To move an idea through the funnel, and unlock more funding, it must pass a series of exercises designed to disprove each of the following statements in turn:
- This idea is desirable. Our users will want it.
- This idea is feasible. From a technical perspective, it is possible.
- This idea is viable. This will create value beyond its costs.
Depth of testing and success criteria are iterative, meaning it starts with a basic, low-cost approach, (e.g. pen and paper sketches) and works up as confidence in each idea builds (e.g. wireframes and clickable prototypes).
Built into this process is the familiar progression from Proofs-of-Concept and Prototypes to Alphas and Launches.
For most organisations, developers, engineers and data scientists are an expensive, scarce resource. The BJSS approach to innovation advocates keeping them away from individual projects for as long as possible, favouring instead the provision of self-service tools that can be used, for example, by strategists, designers and subject matter experts themselves.
To achieve low cost-per-idea technologists have an important role in reducing the time they spend on individual ideas, particularly at an early stage, in favour of providing solutions that make experimenting with AI and advanced technologies accessible and repeatable across many thousands of ideas.
Shelve Sprint Zero
Building a reusable set of tools suitable for managing the delivery of enterprise-scale advanced technologies can offer a way to massively compress traditional Sprint 0 activity. For example, setting up Continuous Integration/ Continuous Deployment (CI/CD) pipelines in a day, rather than a week, leaves a lot more time for value-adding opportunities such as requirements gathering, user research and iterative design.
Innovation projects tend to be very short by default so having reusable infrastructure available ‘off the shelf’ can proportionally relieve a huge amount of overall time and cost.
Managed Tech Debt
Tech debt is everything that needs to be revisited and rebuilt as a product develops. Tracking and managing tech debt at early stages is essential to keeping longer term costs down.
Adopting a falsification approach is helpful to inform decisions about how much debt is acceptable at each stage. Additionally, reusable tools can help circumvent the accumulation of debt altogether by building on solution architecture from previous products.