There’s Gold In Them There Files – Alternative Data, Emerging Technology, Monetize Data

Sam Walton founder of Wal-Mart would famously count cars in the parking lot as a barometer of both his business and the relative performance of rivals. He once got so engrossed in the task that he crashed his car into the back of a Wal-Mart truck.

Sam may therefore, not have been so surprised by a University of Berkley study which used historic satellite imagery to monitor parking-lots across multiple US publicly traded stores. It showed that buying shares when parking-lot traffic increased abnormally and selling when it declined would earn a return that was 4.7% over a retail sector benchmark.

Satellite imagery is not the only way to get an understanding of client visits. As highlighted in an article by Matt Turk geo-location data allowed Foursquare to predict Chipotle’s 2016 Q1 results ahead of the company announcement. Foursquare predicted correctly, that sales would be down nearly 30% based upon their analysis of changes in footfall at the food chain’s outlets. The ability to use timely data that gives a more current indication of performance, rather than waiting for backward looking quarterly updates is clearly of enormous value to investors.

Another example from 2018, concerns the much-watched company Tesla. When Elon Musk announced that the car maker was having to work around the clock to meet demand for the model 3 there was, some would say understandably, some scepticism from the market. Thasos Group which analyses trillions of geographic coordinates collected by smartphone apps set about tracking smartphone pings from inside the boundaries of the Tesla Fremont campus. Using their analysis of numbers of phones active on the Tesla site they were able to share data with hedge-fund clients showing that the night shifts grew by 30% between June and October 2018. In this way investors had independent evidence indicating that Musk was neither exaggerating demand nor Tesla’s determination to increase production to meet it.

Unsurprisingly, therefore the investment industry has become extremely interested in sourcing and using “Alternative Data” to gain competitive advantage and generate alpha. According to Alternative Data, buy-side firms are expected to spend $1.7 bn on alternative data in 2020. The University of Pennsylvania found that 20% of hedge funds with more than $1B in assets under management have multiple analysts dedicated to identifying alternative data sets and understanding their correlation to companies’ earnings.

It’s not only investors that can gain financial advantage from using alternative data. In the book “Outside Insight: Navigating a world drowning in data”, Jorn Lyseggen highlights the potential benefit to management from utilising external information that can give a more forward-looking perspective on which to make decisions. Lyseggsen says “Running a company looking only at internal information is like driving a car while looking in the rear-view mirror. Every day, competitors leave behind online breadcrumbs filled with valuable external data. Outside Insight is a business strategy for forward-looking companies that leverages AI and machine learning technology to distil valuable insights from this information for better, more informed decisions.” The key argument in the book is that senior management should be incorporating external data into their decision-making process to help them understand external environmental factors that internal data alone cannot. Examples include macro-economic indicators to help understand the health of the global economy; social media data to understand relative brand sentiment; data on the production and supply of raw materials; and current and forecast weather patterns that may impact on food production. For example, Minute Maid use data on predicted and actual weather conditions to plan and adjust the production process for its Orange Juice. By understanding both the likely future conditions and actual weather events from around the globe, they can make timely adjustments to supply chains and production processes to cope with bad summers in one region and unexpected events like an early heavy frost in another.

The desire of investors and senior managers to source data that will help them make better investment and strategic decisions is one side of the story. These are the factors that are generating ever increasing demand for data.

But what of the supply side. All firms generate data in the course of their business. Much of this is “by-product” data that is not proprietary to their core business, but which may have real value to others. Any data which a firm generates that can give insight into the activity of a particular sector or market may well be of value to others.

Based on market feedback provided by Alqami (a specialist in the monetisation of data), the value drivers for data are:

Transactional: Providing a granular view of economic activity such as orders, invoices, payments, fulfilment data, applications for services or permits.
Volume/Depth: Providing a sufficiently material insight into one or more business area that will create genuine insight.
Multi-Dimensional: allowing different insights and correlations.
Frequency: The data should be refreshed on a consistent, frequent basis, providing up to date insight into current levels of activity.
History: The history of the data should be available to allow year on year, month on month and trend analysis.

There are also a number of constraints that Alqami identify for firms to consider:

Regulatory/Legal Restrictions: Does a firm have the legal right to distribute data and what constraints are there (for example anonymity)?
Ethical: Is there any ethical concern around the supply of data and how does this impact on the content of data (for example the need to mask and aggregate certain data)?
Accuracy/Timeliness: Does the firm have the capability to meet commercial SLA conditions regarding accuracy and timeliness of supply?
Format: Raw data is of greater value than aggregated data, though that may need to be considered given the constraints mentioned above.
Valuation: There is no consistent and recognised methodology for valuing data. It requires the input of specialists.

The types of data content that may be of interest is very broad. Bloomberg for example is committed to both sourcing and distributing alternative data and segments this under multiple categories.

Multi Asset: Corporate Flight activity, App Usage, Supply Chain, Public Sentiment.
Consumer: Consumer reviews, consumer intelligence, retail traffic.
Energy: Oil & Metal storage, natural gas flows, shipping data.
Financials: Equity analytics, employment, short interest data.
Healthcare: Clinical trials, Regulatory milestones, prescription data, drug and disease-level forecasts.
Industrials: Public contracts.
Real Estate: County data, building permits, construction projects.
Technology: Technology spending intentions.

In terms of reward, the value at stake can be significant. Mastercard’s core business is processing payment transactions globally. However, they also make significant revenue from the insights that this view of payment flows provides. Based upon their Q3 2019 investor report they currently earn revenues of over $4bn per annum in their Data and Services business, a significant part of which is focused on alternative data, providing analytics on current consumer spending and comparison to historic spending trends across industries.

Whilst most firms will not be looking at $bn opportunities, the rewards for providing data can be significant. In most cases data provision will be on a licensed arrangement that will generate recurring annuity revenues. So long as the contractual arrangements and initial operational set up are well managed, then the provision of the data will not be a significant overhead. The incremental value to your firm for licensing data could therefore flow direct to the bottom line. This is something the NHS may have considered before (as reported in the Times (10/12/2019) giving Amazon the rights to a veritable treasure trove of data for free.

There may indeed be gold in them their files (of data). If you think you may have data that could be valuable and want to join the gold rush, please do get in touch. Can you afford not to explore this further?

Disclaimer: This article has been prepared for general guidance on matters of interest only and does not constitute professional advice. You should not act upon the information contained in this publication without obtaining specific professional advice. No representation or warranty (express or implied) is given as to the accuracy or completeness of the information contained in this publication, and, to the extent permitted by law, Steve Webb Advisory Limited, its directors, employees and agents do not accept or assume any liability, responsibility or duty of care for any consequences of you or anyone else acting, or refraining to act, in reliance on the information contained in this publication or for any decision based on it.

Authored by Steve Webb, Senior advisor Envorso