A conversation on design, data and business innovation

How prioritising data can lead to business innovations in times of disruption

The COVID-19 pandemic has proved to be the perfect storm of innovation for many businesses, presenting opportunities to design new solutions to address inefficiencies and cater for the new needs and behaviours created by the pandemic.

Dr Ileana Stigliani spoke with Chris Downs and Marei Wollersberger, founders of design studio Normally, about the importance of leveraging data to create rapid and impactful change.   

Over the last seven years, you have been helping businesses innovate by leveraging data with a human-centred lens. In what way does data play an important role in business innovation?  

Potentially, data can affect everything, but it is important to recognise and understand the shift from reflect to affect. Data analysis tends to reflect on past events without thinking about how it should shape the future.

Business innovation does not come from looking backwards, but from using data to radically reshape business models and user experiences.  

Are you saying that currently efforts are misplaced, and companies are looking in the wrong place when it comes to data? 

Yes, data is exponentially more valuable when it is used to drive and affect future experiences. Shifting from reflect to affect is crucial in unlocking the value and meaning of data. Paradoxically, 99 per cent of effort put into data analysis yields only one per cent of value, while the one per cent of effort put into data for innovation is where 99 per cent of the value lies.  

Can you give me a real-world example of how a business has used data to innovate? 

Spotify used data to disrupt a traditional business model to reimagine the way we consume music by moving from media ownership to music as a service. By striking licensing deals many industry veterans considered impossible, Spotify created a new, data-driven platform inviting users to give up buying music in favour of subscribing.

Users can also discover new music by using Spotify’s recommendation engine to create a uniquely relevant personalised service. The underlying technology is not very different to iTunes but rethinking the business model and embracing the innovative potential of data has been transformative and is being echoed in many other industries. 

Do you think there are certain kinds of companies and industries that would benefit most from pursuing data-enabled innovation? 

Every business in every market can benefit from data-enabled innovation. Data is useful in improving inefficiency and/or reducing waste in business or industry. For example, Spotify realised the duplication and storage of media was an unnecessary waste. Using data in this way can give businesses a great advantage. 

Data can also redress an imbalance in power. Education, healthcare and even government are three industries that could become unrecognisable as data equalises the power dynamic between the service provider and the user. 

Finally, data can be used to analyse the capability of under-used assets, for example, empty office space. Then we can find a way of collecting, modelling and rendering the data about these assets so it can be used. 

What do you mean by collecting, modelling and rendering data? 

Data has to be collected before it can be converted for use. Once it has been collected, its usefulness is only determined once logic has been applied to it. This might mean applying it to an AI model, and then matching and segmenting it.

Data is dynamic and can be manipulated to be different to how it was when it came into the collection, but when adopting a human-centred approach, the most important rendering of a data product is in the user experience.  

Can you give me an example of how data can be collected, modelled and rendered to create a great user experience? 

Uber has a clear collection strategy, as it models data effectively and renders it as an experience. The collection strategy relies on a demand side app to determine the positive identification of a customer, the customers’ intent to take a taxi and the customer’s current location. 

These data points are matched with those from the supply side, the current location of Uber taxis and their availability. The data is modelled to find the best fit based on proximity, needs and ratings.

Finally, the data is rendered as a real-time mapping interface in the app, the financial transaction, the ride-rating and customer feedback. But ultimately, it is rendered as a user journey from pick-up to drop-off. 

What else do businesses need to do to offer well-designed, innovative data-driven experiences? 

There are three factors: exploration mindset, individual data experience, and data stewardship. 

Companies should explore data to understand its provenance, history, politics, when it was collected and what wasn't collected. They should also experiment to decide what is possible. By using data efficiently, companies can both design for user groups as well as design unique experiences for individual users. 

Data stewardship is crucial because data is an asset and a liability. If we misuse people's data, our access can be revoked either by regulation or by people refusing us access. 

Are we seeing an increase in data-driven innovation since the pandemic, or is it still too soon? 

We have seen behaviours and needs change almost instantly since the start of the pandemic, but it might be too early to see how businesses will respond. There is evidence of innovation in communities and smaller businesses, which have the flexibility to reorientate themselves as circumstances change.

Data is at the heart of the iconic products and services that we use regularly. Collected, modelled and rendered through a human-centred approach, this method of working with data holds the greatest innovation potential.