The Friday Five by Jefdata - HealthTech/Everything as a Service

1. Sourcing Alternative Data Responsibly

2. TechCare or HealthTech?

3. Everything-as-a-Service Will Create New Data Sources

4. Data Science is a Skill, Domain Expertise is a Career

5. Is Alternative Data Taking the Fervor Out of Earnings Season?

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1. Sourcing Alternative Data Responsibly

With the $3 billion alternative data industry exploding, hedge fund managers fear a crackdown could be coming – Business Insider (Subscription) - 4 Minute Read

Rich's Thoughts: Transparency, Transparency, Transparency. Protect yourself, ensure that data vendors have the rights to license data to an asset manager. Data vendors should be just as invested in compliance, transparency, and process as the investor is. Michael Marrale (CEO of M Science) has been vocal, persistent, and forward-looking on this topic. He notes that there are many vendors in the data space that are small and do not have a legal and compliance infrastructure with scale. Because of this, it is inevitable that someone or some entity could run afoul.

As we have discussed in prior Friday Five reports, there have been “crackdowns” related to collection and usage of consumer data in other sectors including the City of Los Angeles filing a lawsuit against The Weather Channel for “unfairly manipulating users into turning on location tracking by implying that the information would be used only to localize weather reports.”

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2. TechCare or HealthTech?

Making New Drugs with a Dose of Artificial Intelligence – New York Times – 5 Minute Read

Rich's Thoughts: What do you consider a healthcare company? You probably wouldn’t say Google, Amazon, Apple or Facebook, and that is what they want…at least for now. Slowly, tech giants (mostly through their venture capital arms) are investing in the future of healthcare such as Jeff Bezos, Bill Gates and Google Venture investing in companies like Grail, a Palo Alto based company poised to detect cancer early using one of the largest clinical study programs ever pursued in genomic medicine. In some situations, tech and large biopharma are co-investing, in others, they seem to be competing. The New York Times article above shows how even chemists are starting to embrace “Man + Machine” that investors are employing within asset management.

What is the end game for large tech within healthcare? Walter De Brouwer from Doc.AI believes that information technology companies will look more like “Life Technology” companies by 2020, as they point their search and intelligence engines towards healthcare and life science. Stay tuned for more from Jefdata on this topic in the coming months.

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3. Everything-as-a-Service Will Create New Data Sources

Would you rent Ikea furniture? Subscription plans are coming – Fast Company - 2 Minute Read

Rich's Thoughts: This week, Ikea made one of the quirkier subscription/platform model announcements to date as they test the “Netflix of Furniture” model in a number of markets. As more consumer product types enable consumers to rent, trial and share products rather than buy, new datasets will evolve the way investors are able to understand consumer purchasing trends broadly. All consumer product types with high upfront costs and long buying cycles should be ripe for subscription-based services. Used furniture has been vital for both teens attending university and millennials/Gen Z individuals that rent their first apartment or home, the Jefdata team is surprised it has taken this long to trial a furniture subscription service. What do you think will be next?

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4. Data Science is a Skill, Domain Expertise is a Career

Why There Will Be No Data Science Job Titles by 2029 – Forbes – 2 Minute Read

Rich's Thoughts: The rise of the data scientist began within internet companies and has recently started to spread into companies within all sectors. “Data science” will be a baseline skill needed to succeed within analytical businesses over the next ten years. This means understanding at least one coding language and having the capability to use different visualization and data storage tools. Within asset management, the Jefferies Data Strategy team identifies an individual with BOTH data science expertise and financial expertise as the “Practitioner’s Bridge”. This individual or team of individuals is vital to the success of the data strategy and is also the most valuable.

In November, we highlighted a TED Talk named Why Tech Needs the Humanities which was filmed in December of 2017. Eric Berridge presents how STEM talent needs humanities talent to succeed. The Jefdata team believes that this talent will not be separated and that all individuals should obtain STEM skills as a baseline before moving into mastering their domain.

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5. Is Alternative Data Taking the Fervor out of Earnings Season?

Don’t Obsess Over Earnings Season – The Wall Street Journal – 4 Minute Read

Rich's Thoughts: Jeff Bezos once famously said "Friends congratulate me after a quarterly-earnings announcement and say, 'Good job, great quarter,' and I'll say, 'Thank you, but that quarter was baked three years ago.' I'm working on a quarter that'll happen in 2021 right now." In most sectors, future guidance on earnings calls drives stock price moves around quarterly earnings results, unless the backwards looking numbers beat or miss in dramatic fashion. Why don’t fundamental investors focus on earnings with the same intensity as they used to? The Wall Street Journal article above focuses on stock price movements around earnings releases, the “what” rather than the “why.” Last year, investors debated the prospect of a bi-annual reporting schedule rather than a quarterly one, which would increase the importance of alternative data collection within investment management even more.

The investors’ mosaic is broader than ever, many of the quarterly reported numbers are expected within a tighter range. Volatility around quarters still remains. Investors tend to ask which buyers and sellers have which data, and why are they trading the name that way using that data? The question bank becomes larger as more data sources come to market and the processes become more black box.