Data is everywhere.
Data is revolutionising business, changing the way organisations work, the services they offer and the decisions leaders make. This trend is obvious in born digital businesses like Netflix, Amazon and Uber. Their data is used to make recommendations, manage inventories or match capacity (drivers) to demand (passengers).
For many businesses, data has become the lubricant that allows markets to operate more seamlessly – allowing firms to better match supply and demand. And it is not just in ‘born digital’ businesses that data is creating a stir by enabling markets to operate more seamlessly.
Take insurance – where risk premiums can be adjusted based on customer insights. Think about black boxes on cars – data on driver performance and behaviour is streamed back to the insurance provider who can modify premiums based on the insights derived. The insurer can offer tailored services – insurance on demand – where drivers pay only when they are driving their car.
The providers can modify premiums based on driver performance – safer drivers pay lower premiums. Or they can change the premiums based on where cars are located – you pay less when your car is at home in your garage than when parked in a multi-story car park, where local crime data shows there’s a higher risk of car crime.
Many of the examples that illustrate how data is changing business come from the business-to-consumer world. Yet in the business-to-business world, data is having the same revolutionary impact. Construction and mining firms such as Caterpillar are also innovating their business models. Rather than selling trucks and equipment, they are selling services – for example, guaranteeing a fixed cost per tonne of mineral extracted from a quarry.
Data plays a fundamental role in enabling this business model. Modern construction and mining equipment is adorned with sensors which provide data on numerous variables – oil pressure, engine temperature and GPS location to name but three. These data are valuable because they allow the health of individual assets to be tracked, so uptime and availability can be maximised. But even more importantly, combining data from different sources allows smart operators to glean insights into the efficiency of quarry operations.
Take a simple example – if the scales in the bed of a truck tell you the truck is full, but the GPS position isn’t changing, you are losing valuable time and hence productivity. As soon as the truck is full it should be heading off to dump the minerals at the crusher so they can enter the next stage of processing.
While en route, to minimise fuel consumption, the driver of the truck should put the truck into first gear and keep a constant speed, avoiding acceleration or braking. Fuel consumption is one of the largest controllable costs on a quarry. Every time you brake or accelerate you increase fuel consumption, so data on speed can be used to monitor driver performance, improve driver skills and enhance fuel efficiency.
Data as an asset.
Wherever you look you see organisations being disrupted by data. In healthcare, in education and in politics, data has become an incredibly powerful asset. Yet interestingly data is rarely thought of as an asset. That’s an important point and one that is worth reiterating – rarely is data thought of as an asset.
In recent years we’ve seen a significant shift in the basis of company valuation. According to a recent Financial Times article, 80% of the world’s corporate wealth now resides in just 10% of companies1. As the graphic below shows, the shift in company valuations – even between 2013 and 2019 – is striking. Alibaba, Alphabet, Amazon and Tencent are all new entries to the list of the world’s most valuable companies and fundamental to their operation is data.
There is a longer-term underlying trend, best encapsulated in the idea of intangible assets. Back in 1975, up to 83% of a firm’s valuation was accounted for by its tangible assets – plant, equipment and inventory. Now, close to 90% of a firm’s valuation can be accounted for by its intangible assets – intellectual property, brand, goodwill, and we would argue – data2.
Data on customers – what they buy, when they buy and how often they buy? Data on employees – who they are and what skills they have? Data on suppliers – where they are, how reliable they are and what capabilities they have? Data on assets – who owns them, how are they using them and what state are they in?
Yet if this is true – if data is a key intangible asset – then how can the value of data be quantified? And what would the implications for an organisation be if it knew the value of its data assets? The purpose of this blog and the ones that follow it are to explore these questions. Let’s start by thinking about data as an asset.
What would be the implications of valuing data as an asset?
Anmut recently completed a data valuation for Highways England, the government funded company who maintains England’s motorways. The total economic value of Highways England is £311 bn – this includes £115 bn of physical asset value (the strategic road network) and £196 bn of value created by users of the strategic road network.
Highways England are engaged in multiple initiatives designed to help their stakeholders extract more value from the road network – smart motorways, real time traffic flow information, advanced warning of roadworks, etc. These initiatives are all – to some extent – informed by data.
In Highways England’s case we have calculated that the total value created through data is £39 billion, that’s around 30% of Highways England’s physical asset value.
Now, if data is worth one third of their tangible asset value, then for every three hours they spend talking about their material assets, do they spend one hour talking about data? How about staff? For every three people working on maintaining tangible assets, do they have one person maintaining their data assets?
What about governance and risk management – for every three hours spent on risk management for their physical assets, is an hour spent on risk management for data?
Move away from time and effort – think about focus. If data is worth one third of the physical asset value then are they thinking carefully enough about where to invest? Do they spend £1 on data for every £3 they spend on the Strategic Road Network?
Could they get a better return on investment by spending a little more on data – improving its quality and availability – thereby improving timeliness of traffic updates.
If they did, could they improve the speed and flow of traffic on the Strategic Road Network, meaning that they have to build less physical infrastructure, because data is allowing them to use the existing infrastructure much more effectively?
An alternative perspective – think about KPIs and reporting. For every three KPIs that relate to the Strategic Road Network, do they have one that relates directly to data? Are they tracking the right things inside their organisation?
If data is potentially one of your most valuable assets, shouldn't you be treating it like one?
We’ve found that organisations that have climbed the data maturity ladder usually benefit from market caps 4-6x that of their peers, who have yet to start treating their data as an asset.
The first step to managing your data asset properly is understanding its value. Once you understand the true value of your data, you can make smarter investment decisions, and leverage your data to gain a competitive advantage.
Contact us to find out how Anmut can help your organisation understand the true value of its data.
1- Rana Foroohar, Financial Times: https://www.ft.com/content/04d3614e-078a-11ea-a984-fbbacad9e7dd
2- The rise of intangible asset value study: https://www.oceantomo.com/intangible-asset-market-value-study/