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The Empty Promise of Data Moats Andreessen Horowitz 20190509
The Empty Promise of Data Moats Data has long been lauded as a competitive moat for companies, and that narrative’s been further hyped with the recent wave of AI startups. Network effects have been similarly promoted as a defensible force in building software businesses. So of course, we constantly hear about the combination of the two: “data network effects” (heck, we’ve talked about them at length ourselves). But for enterprise startups — which is where we focus — we now wonder if there’s practical evidence of data network effects at all. Moreover, we suspect that even the more straightforward data scale effect has limited value as a defensive strategy for many companies. This isn’t just an academic question: It has important implications for where founders invest their time and resources. If you’re a startup that assumes the data you’re collecting equals a durable moat, then you might underinvest in the other areas that actually do increase the defensibility of your business long term (verticalization, go-to-market dominance, post-sales account control, the winning brand, etc). Treating data as a magical moat can misdirect founders from focusing on what’s really needed to win In other words, treating data as a magical moat can misdirect founders from focusing on what is really needed to win. So, do data network effects exist? How might a scale effect behave differently from the traditional network effect? And once we get past the hype of having to have them… how can startups establish more durable data moats — or at least figure out where data best plays into their strategy?
#strategy  #startups  #data  #asset  #critique 
13 days ago by phil_hendrix
Data is not the new oil Zetta VC TechCrunch 20180327
Data is not the new oil Jocelyn Goldfein, Ivy Nguyen8 months ago Comment Jocelyn Goldfein Contributor Jocelyn Goldfein is a managing director at Zetta Venture Partners. Ivy Nguyen Contributor Ivy Nguyen is an associate at Zetta Venture Partners. More posts by this contributor Measuring AI startups by the right yardstick Finding the Goldilocks zone for applied AI It’s easier than ever to build software, which makes it harder than ever to build a defensible software business. So it’s no wonder investors and entrepreneurs are optimistic about the potential of data to form a new competitive advantage. Some have even hailed data as “the new oil.” We invest exclusively in startups leveraging data and AI to solve business problems, so we certainly see the appeal — but the oil analogy is flawed. In all the enthusiasm for big data, it’s easy to lose sight of the fact that all data is not created equal. Startups and large corporations alike boast about the volume of data they’ve amassed, ranging from terabytes of data to quantities surpassing all of the information contained in the Library of Congress. Quantity alone does not make a “data moat.”
#data  #strategy  #asset  #monetize  #differentiation  #critique  #vc  #A+ 
november 2018 by phil_hendrix
How to create a virtuous cycle of data with your customers VentureBeat 20180819
How to create a virtuous cycle of data with your customers S. SOMASEGAR, MADRONA VENTURE GROUPDANIEL LI, MADRONA VENTURE GROUP@DANIELXLI AUGUST 19, 2018 10:25 AM MOST READ Tally brings its app for credit card debt payments to Android 4 of the coolest things we saw at IFA 2018 Google releases AI-powered Content Safety API to identify more child abuse images Google Search now uses Service Worker for repeated searches Google releases open source reinforcement learning framework for training AI models UPCOMING EVENTS BLUEPRINT: Oct. 9 - 11 VB Summit 2018: The best in AI. An invite-only executive event. Oct. 22 - 23 Over the last decade, technology companies like Amazon, Apple, Google, and Facebook have risen to the top of brand value lists by outgrowing many of the traditional consumer companies like Disney, Toyota, and McDonald’s. There are many factors driving this rapid growth in tech brand value, but a large portion of the growth can be attributed to the virtuous cycle of data for tech companies. Technology companies know their customers, even anonymously, much better than the companies behind traditional consumer products, and they use that customer data to continuously improve their products which, in turn, drives brand affinity and loyalty.
#data  #analytics  #strategy  #value  #asset  #A+ 
september 2018 by phil_hendrix
Infonomics How to Monetize, Manage, and Measure Information as an Asset for Competitive Advantage Douglas Laney 201709
Infonomics: How to Monetize, Manage, and Measure Information as an Asset for Competitive Advantage Hardcover – September 19, 2017
by Douglas B. Laney (Author)

The discipline of infonomics takes you beyond thinking and talking about information as an asset to actually valuing and treating it as one. Infonomics provides the foundation and methods for quantifying information asset value and tactics for using information as your competitive edge to drive growth.
#data  #value  #strategy  #asset  #competitive  #advantage  #equity  #monetization  #Gartner  #book  #PEH 
january 2018 by phil_hendrix

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