Aug. 4, 2021

#3 - David Ansley. Platform business models and network effects.

#3 - David Ansley. Platform business models and network effects.

David Ansley is an entrepreneur and advisor with a strong focus on digital disruption. He is owner of Ansley and Associates and director of management consulting company ACG global.

He has coached more than 100 leaders on Digital Disruption and advised many startups and corporate commercialisation projects over the past 20 years.

He lives in Sydney, loves surfing, skiing and red wine. 

We talk about platform business models and how to build and exploit network effects. We discuss paradigm shifting for business operation in light of ever increasing variability that makes robustness a non-viable option.

Highlights and takeaways

An IT platform is very different from what David calls a platform business model. The latter enables and grows with network effects. The more people participate, the greater the value to each participant or customer. The classic example is Amazon. Everyone goes there to buy, because all the sellers are there. The sellers use it because all the buyers are there. 

Another network effect can come out of data assets, particularly in B2B. The flywheel metaphor is often used to describe how more data leads to better solutions, increasing usage, which in turn increases data generation, and so on. I prefer a snowball metaphor as the flywheel only retains some of the previous momentum, whereas a snowball - like this data effect - gathers momentum with every iteration, becoming almost unstoppable. 

The key is capturing and joining data from different sources into a combined asset that is hard to replicate. Such platform business models are often winner-take-all. Uber is an example of a ‘weak’ platform model, because the network is local to each city and riders can easily switch between platforms. There are some similarities to shipping where you also need a global network to have a real network effect, in the strategic sense. 

Established enterprises often fail to plug into or create such models because they identify with a certain way of doing things and are focused on executing their existing business model. 

Digital services can exploit data and AI to bring marginal costs close to zero. With physical products and services relying on them, there is a lower limit to marginal cost though. Building digital products and services on top of your physical ones can therefore be a viable way to grow a business. The challenge again is people - the established organization can feel threatened by and resist such changes. It’s very hard to overcome this challenge and many companies have not done it very well - such as GE with their Predix efforts. 

It’s important to protect existing business models that have some amount of life left in them. For future models that are quite exploratory, it may be best to set up a separate, independent little group to work on that. For those that are more aligned with your present business model, development of such new models should be more integrated. That becomes challenging because you then have to bring the whole organization along on the digital transformation.

Leaders should try to enable their organizations to take in new, outside information, which may mean making it less hierarchical. You need a culture and organization that can react to change quickly, experiment, and take calculated risks. Not betting everything on one opportunity but rather acting on information to try lots of different things. 

CEO and board support is crucial. Without it, generating a successful new business model is unlikely, as is changing the culture of the organization. 

A good way to think about transformation is to look at sources of value. What could be done differently and better? How would a startup do that? An example being what Dollar Shave did to create a new market without competing directly with Gillette. Anytime there’s a large gap between price and cost, there’s an opportunity for a startup to create a new market.

Similar to a take-away from my conversation with Sjoerd de Jager of PortXchange [LINK], established businesses often optimize to take away variability. As variability keeps increasing through new technology, for example, this approach fails. This goes beyond culture, requiring a paradigm change. 

Deep tech is not just data and IT but many different technological innovations that challenge what we today think of as firm facts we can rely on. 

Maritime Makers Quality Quotes

“No amount of black belt efficiency and variability control will help you when someone comes and offers a completely different product/service in your marketplace.” - David Ansley

“If there’s the opportunity to disrupt, if there’s a space that can be attacked by a better solution, somebody will think that up and do it.” - David Ansley