Why you need a data strategy, yesterday

When Covid-19 appeared in early 2020, many airlines were forced to borrow so they could stay afloat – or maybe “aloft” would be more accurate.

The only problem was, with everything shut down, United Airlines didn’t have much to offer investors. UA boasted a fleet of 1358 total aircraft assets valued at roughly $35 billion. Essentially, with a lot of very expensive paperweights, UA was in a tough position. But it did have an ace up its sleeve: data.

The world’s worst-kept secret is that data is valuable. UA had plenty of data gathered from more than 100 million members over 30 years as part of its MileagePlus Holdings programme. Before the pandemic, the loyalty scheme generated about $US5.3 billion in annual revenue for the airline, or 12% of the company’s total earnings.

This customer data was already proving hugely lucrative for UA, so it valued the programme at $US22 billion (12x EBITDA) or 62% of the value of UA’s total fleet. That was a big number, but investors at Goldman Sachs, Barclays Bank and Morgan Stanley all seemed to agree with the aggressive valuation of the MileagePlus programme.

By June 2020, just four months after the pandemic gripped the world, UA successfully secured a $US5 billion loan with these funders. That was enough to keep the airline aloft until passengers emerged from isolation and started using its services again. And they did. United Airlines reported a $US737 million net profit for 2022.

Similar stories highlighting the value of data are now common headlines across all parts of the corporate world as more companies realise that intangible assets like data have deep value.

Slowly, slowly, companies are learning how their data can be deployed to maximise profit. UA already had a great plan to use its data (the MileagePlus programme), but the airline only outlined the true value of its loyalty scheme when forced to collateralise it for investors. Until then, the data was just a small portion of UA’s overall business. In 2020, the data became an asset.

The discussion about data is usually associated with tech companies like Facebook or Alphabet (Google’s parent) which were the first to demonstrate how data is fundamental to modern businesses.

Normal (non-internet) organisations tend not to focus too greatly on data. If they do have data, it is usually collected by more subtle means as part of their day-to-day operations. Some businesses don’t even know if they are collecting any valuable data at all (they usually are).

But one thing is becoming abundantly clear. Companies that figure out how to transform their data into new revenue streams are quickly pulling away from the pack.

Amazon is a great test case here. In August 2022, Amazon acquired iRobot, the creator of the automated vacuum cleaner Roomba, to add to its suite of “smart” household devices. It made sense that online retailer Amazon needed its own range of robot vacuum cleaners, right?

Well, the real play for Amazon wasn’t the machines, it was getting access to the data generated by millions of those robots crawling around people’s homes.

Roombas suck up hairballs and dandruff, but they also map the layout of a home. The robots then feed this data straight back to Amazon. If the map reveals that a home has multiple bedrooms, then it’s probably a safe bet for Amazon to assume the family has children. With this one piece of data, Amazon can now send targeted ads for children’s toys to electronic devices in the home.

Amazon is probably an unfair comparison of what the average business can do with data. After all, the multinational earned $514 billion in revenue in 2022. But even the smallest company on a strict budget can learn to use data in smarter ways, just like Amazon, if it can develop a sound data strategy.

Unfortunately, few firms are thinking about doing this. Research and advisory company Forrester reports that nearly three-quarters of all gathered data lie fallow in databases, unused and unloved. Furthermore, DataRPM found that almost 85% of “asset-intensive industries” (companies requiring above-average levels of capital to operate) aren’t even using the data generated by their own devices, let alone data from other sources.

Of course, many obstacles prevent companies from digging into their data. Maybe the data is dirty. There could be inconsistencies in the collection or duplications across datasets. It’s even possible for a business to have too much data, strange as that may sound. A good data strategy can overcome these issues and yield incredible insights such as finding potential terrorists in bank transaction data.

If they are looking for a good role model, companies could pay attention to how governments are trailblazing the clever use of data. The New Zealand government, for example, has used the Integrated Data Infrastructure (IDI) to identify how five-year-olds with certain risk factors may cost the state $320,000 before they turn 35. With this insight, the government can intervene more appropriately in these vulnerable kids’ lives while saving the taxpayer money.

As these examples show, putting data together in new ways is not just part of the game – it is the whole game. A good data strategy allows a company to see what data it already has, what data it still requires and, crucially, what it hopes to learn from its ever-growing pools of data.

EverEdge has a successful track record of helping businesses understand their data needs. Our team recently worked with a shopping centre and found a dozen end-use cases for its gathered data. In fact, that data turned out to be more valuable than the shopping centre itself.

The overall lesson is that your company doesn’t have to be Google to generate significant value from data and other intangible assets. The key is to start collecting it, yesterday.