Alternative Data Weekly #156
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Three Announcement(s):
1- This is the 3-year anniversary of the Alternative Data Weekly! Thank you! Scroll to the bottom for more.
2- I’ll be moderating a panel at the upcoming Beryl Elites Conference in NY November 6-7. Please join me!
Panel Topic = Alternative Data: At The Forefront of Innovation in Investment Management.
3- Vertical Knowledge’s Chief Product Officer & Head of Data Strategy Rayne Gaisford will be presenting at the BattleFin Nov 2 Corporate Discovery Day.
Theme that emerged in this week’s email is … build moats & reduce churn … make your data indispensable!
QUOTES
“The ones (data businesses) that succeed won’t just be the companies with the most comprehensive data or the most curation, but they’ll also require thoughtful strategies designed around strong network effects.” – Travis May
News Articles
Podcasts
Cool Charts
Final Thoughts (data products)
#1 – Travis May published The Six Moats of Data Businesses. October 2023.
My Take: Really like this thought piece … frameworks like this help drive decisions at data firms everywhere. We all want that deep & wide moat! See below in Charts sections for a nice visualization. I think we are going to see a lot more of 3, 5, & 6 below as more firms realize the value of the data they have in-house.
Data currencies (data is needed for two parties to transact)
Navigating the long tail (data from lots of partnerships, tough to replicate)
Proprietary data from exclusive sources (good licenses)
Proprietary data from give-to-get models
Proprietary data creation (ex. Yelp)
Proprietary exhaust data
#2 – Bobsled’s Steven Jacobs published 6 Strategies to Reduce Churn in a Data Business. October 2023.
My Take: Data is sold, not bought. This is a world of long sale cycles and challenging use cases. Churn sucks. This is a good thought piece on reducing that churn. Here are the six:
Faster onboarding
Improve the UX of your product
Solve issues before they turn into problems
Feedback loop to product
Go wide
Always tie it back to value
#3 – James Cicalo & Vera Shulgina from Arcesium published Raw to Refined: A Framework for Data Sourcing. October 2023. First of 3-part series.
My Take: Lots of frameworks being published these days. I believe this speaks to state of the industry (“trough of disillusionment” per the article). There is a lot of activity, but we have a long way to go. I think the value of data is becoming more widely understood but the value extraction is harder than expected (see article about the short tenure of CDOs). I like the Arcesium structure as they suggest starting with the end in mind, focus on your internal data first, and try to get some early wins. Then use that success to inform you about best use cases for external data.
BONUS: Dan Hock published The Concept That Explains Everything About Marketplaces. June 2023. “Marketplaces are simply businesses that don’t sell goods or services, but instead sell the reduction of transaction costs. As a result, studying transaction costs will help you understand where marketplaces will succeed, what kind of marketplace to build, and how to price them.”
What else I am reading:
Adam Braff’s Sam Bankman-Fried, professional ghost. October 2023.
Washington Post’s Life Expectancy Calculator. October 2023.
Nat Rubio-Licht from The Daily Upside published Meta May Turn to Synthetic Data to Feed its AI Growth. October 2023.
Saurabh published Mapping The Data Landscape. October 2023.
Jason Derise’s Avoid "Basket Case" Data Products Through Iteration. October 2023.
Rob Martinez’s BattleFin London 2023: Insights And Key Takeaways. October 2023.
Most anything from The Random Walk.
Source: Louise de Leyritz from The Data Couch podcast interviews The Atlantic’s Jenna Lemonias. October 2023.
My Take: This is a new podcast with a focus on making conversations about data more accessible. The Atlantic is a case study of taking a very traditional organization into the age of data. Building a data culture in a traditional organization. The importance of getting those early (easy?) wins to get the business execs on board and excited about how data can help them. Explain to the business team how to use the data (directional insights vs precise insights). Make it as easy & straightforward as you can because once you lose trust in data, it is tough to get it back.
Highlights (29-minute run time):
Minute 01:00 – Jenna background & discussion of The Atlantic
Minute 02:45 – how did the need for a data strategy emerge at The Atlantic
Minute 05:30 – how is data team structured?
Minute 07:00 – life cycle of data
Minute 10:00 – how does data team impact business decisions
Minute 13:30 – discussion of data quality
Minute 15:30 – building a data culture at a traditional organization & what worked well?
Minute 21:30 – bridging gap between data team & business team (leadership buy-in is key)
Minute 24:00 – measuring ROI
Minute 26:00 – looking to the future
Minute 28:00 – get easy wins to get people on-board
BONUS: Lenny’s Podcast How to become a category pirate | Christopher Lochhead (author of Play Bigger, Niche Down, Category Pirates, more).
Minute 57:00 - “Looking for breakthrough in language to describe it to people, because I think when most people realize the difference between data/content and training data ,there is a massive breakthrough that occur there. The languaging is still not sufficient but we are getting there.“
Source: Harbr published a CDO Survival Guide. October 2023.
CDOs have the shortest average tenure in the c-suite. This guide will help CDOs & other data leaders overcome the universal challenges we all face.
CDOs should start by understanding the impact that any of the following would have on the needs and priorities of their role:
Technology
Legacy
Regulation
Corporate Structure
Competency
My comment: higher value to the right … see my data products post below … Harbr Data helps here.
My comment: Again …data product are where the customer engages with the data.
My comment: Harbr sits between Manufacturing & Consumption.
BONUS: Travis May’s Six Moats of a Data Business. October 2023.
First – Thanks for 3 years! The first 3 readers to reply with “ADW Rocks” get an Amazon book of your choice gifted from me … the catch: the book must be business- or data-related. AND I am going to buy 2 copies & … one copy for you & one copy for me!
Let’s go!
Final Thought - Source: My brain thinking about data products.
Loyal readers of the ADW will know the idea of data products is mentioned quite a bit (including this week). I see data products as being akin to a gateway drug into using data. The highest impact data product is one that confidently addresses a specific business issue.
Understand your one issue & use your data to provide some useful insight.
If the end user cannot understand the conclusion in sub-5 seconds, you’ve missed an opportunity.
“Simple can be harder than complex: You have to work hard to get your thinking clean to make it simple. But it’s worth it in the end because once you get there, you can move mountains.” - Steve Jobs
Not unlike a regular executive team update on the financials of a company. This deliverable is an example of a “data product”.
Weekly financials are a straightforward use case with information that is readily available presented in a format that is easily digested. Most execs are looking for 2-3 specific high leverage datapoints in the financials … they know what to look for given to goals of the quarter or year.
We now have access to far more data … apply those same delivery ideas (straightforward, easy to understand, insight into high leverage inputs for the company, etc).
I’ll get excited here at Vertical Knowledge because there is SO MUCH information we make available. To draw people in, I need to demonstrate how our data and clearly address those 2-3 high leverage inputs that will impact your decision making process.
Once hooked then we can get into the next 100 ideas I might have for you!
Last one … please join me at Beryl Elites Nov 6-7 in NYC:
