When Firestone entered the aviation tyre market they found themselves with a surplus of stock as at the time it was difficult to enter a market monopolised by existing suppliers. Through an internal innovation session, they had the idea to only charge airlines for when they were using the tyres…..when the aircraft was on the ground. This was an early form of As a Service or a Data Driven business model.
Since then we have seen a number of other data driven business models including Rolls-Royce's now famous TotalCare service where engines and services are billed based upon usage.
Many projects undertaken by organisations are still technology and often done as a stand-alone project: whether a company uses on premise or cloud solutions, bespoke applications or SaaS, automation or low cost labour etc. However, one of the biggest challenges faced by business leaders is how to differentiate themselves in the market and this often involves exploring new business models, for both B2B and B2C markets, which ultimately drive profitability and new level of services.
These new models can take various forms:
- Consumption Driven – usage, processors, transactions etc
- Performance Driven – throughput, availability, service level etc
- Value Driven – Increase revenue, profitability, loyalty etc
However to do this, the business will need to capture and understand the relevant data to drive those models. But data driven models are still not widely adopted. Why is this?
Moving to a new business model can be problematic for organisations, often struggling to balance the necessary changes in culture, R&D, technology and financial results as they move from one model to the next over time. A good example of this is how a sales culture would change as a business moves from large upfront sales of product and services to outcome-based opportunities that start small and grow over time. This change affects areas such as product development, sales incentives, reduction in order book value and lower in-year revenue, as well as requiring far closer integration with the client’s business. In most cases, organisations are also constrained by their legacy systems, that are often too old to handle new transaction types but at the same time critical to existing services and revenue streams.
But legacy systems shouldn't stop organisations from developing new services. As John Hicklin explores in his 'Have you cake and eat it' blog, cloud and IoT technologies can now help explore new models with only a fraction of the cost currently being spend on maintaining legacy services.
So, if, and more likely when, organisations start to plan new business models there are four major areas they should be exploring that will underpin new data driven business models.
- Internet of Things – as you become more integrated into your customer’s business or people’s lives, it will become essential that you can monitor how you products and services are performing….in real time.
- Analytics – with outcomes and performance against baselines becoming the main drivers for business, analytics will be at the heart of your organisations decision-making.
- User Experience – given digital is the main driver to necessitating new business models, then a great user experience of those digital services will be the key to driving increased adoption rates.
- Organisational Transformation – it should not be under-estimated the magnitude of change that your people will have to go through, requiring a carefully managed transformation programme.
So, whether you are trying to enter a new market, disrupt your existing market or just optimise how you run your business, using data drive business models in your business is fast becoming an approach you cannot ignore.