With the new year and new decade come ideas on self improvement and how to do things better. From a business perspective, it seems like belt tightening is the focus for many growth companies in the consumer space. This week alone 3 Softbank companies have announced layoffs to try to get costs under control - Zume, Oyo, and Lime. It’s not a surprise as you can’t give away dollar bills for $0.50 forever. The real question is if this hits the enterprise sector as the later stage growth VCs feel the pain from their consumer investments and start focusing across the board on costs. You all know my perspective, things should never ever get to that point and balanced growth and prudence is ALWAYS the name of the game.
On the self improvement side, I’ve shared a few articles that may help you personally and professionally. The first is saying No to Negativity and the second is that you can get ahead by being inefficient. The first is quite clear but the second may be counterintuitive so please read on!
As always, if you like the new format or content, please share and ❤️ above!
Great advice going into 2020 - don’t let negative biases rules your thinking, just say No.
Our minds and lives are skewed by a fundamental imbalance that is just now becoming clear to scientists: the negativity effect. Also known as the negativity bias, it’s the universal tendency for bad events and emotions to affect us more strongly than positive ones.
To counteract, authors suggest:
Remember the Rule of Four. Many studies—of spouses’ interactions, people’s diaries, workers’ moods, customers’ ratings—have shown that a negative event or emotion usually has at least three times the impact of a comparable positive one. So to come out ahead, we suggest keeping in mind the Rule of Four: It takes four good things to overcome one bad thing.'
In the world of startups, what I often see is the “perfect is the enemy of the good.” Everyone is striving to the best and most efficient but Shane Parrish (Farnam Street) shares why that is not necessarily the best thing to pursue all the time. He believes we can “get ahead by being inefficient.”
Inefficient does not mean ineffective, and it is certainly not the same as lazy. You get things done – just not in the most effective way possible. You’re a bit sloppy, and use more energy. But don’t feel bad about it. There is real value in not being the best.
The team at 645 Ventures does another deep analysis on market dynamics; this time covering The Top Five Myths About Building Billion-Dollar Startups. My favorite is Myth #2, Top VC Firms Don’t Miss Billion Dollar Startups at the Early Stage.
At the seed stage, only 31% of the companies raised capital from one of these top 70 firms. Almost 70% did not have one of these firms in their cap table at the seed.
Don’t forget the value of product marketing, an often misunderstood and super important roleCouldn’t agree more! Product Marketing is essential in any business - B2C, B2B, etc. It’s misunderstood (it’s not project management), under appreciated by engineering, marketing or sales (and definitely startup CEOs) its one of the most difficult positions to hire!
aiCarly 🦄 (Carly Stoughton)@_aiCarly@martin_casado Yes! I think Product Marketing is a widely misunderstood discipline. Best way I've seen it described (pictured), is what I jump to the whiteboard with. It's a hybrid role, with tight alignment to product and sales teams. One of MANY roles in marketing, and can be quite technical. https://t.co/QgEPRYvOXn
from the New Stack, senior IT exec survey shows large enterprises continuing to build and not buy new software - more here
Product led growth cos need to keep investing in product as one of main differentiators versus incumbents - great breakdown from the Information
Year in review for privacy preserving machine learning (PPML) from Jason Mancuso (dropout labs, a portfolio co). Here’s why PPML is important:
If the field of machine learning is set to revolutionize industries in the ways many expect, it will need massive amounts of data. Two of the highest barriers to such a revolution would be the high costs of both accessing and operationalizing that data. Many in our PPML community have maintained that improved privacy and security infrastructure for machine learning will be necessary to overcome these barriers. This is especially relevant for sensitive datasets that could, for example, accelerate the discovery of life-saving treatments, or help diagnose and correct prejudiced behaviour in existing systems. By building the infrastructure to enable secure and privacy-preserving access to data, the PPML community can create a beneficial and equitable future for machine learning in society.
Win ❤️ and 🧠 of developers and you win the enterprise. Just caught up with Hashicorp’s year in review and this stood out.
Expanding our commercial footprint. We continue to make inroads with large enterprise customers, adding hundreds of new customers in the last year. We now count more than 100 of the Fortune 500 and over 200 of the Global 2000 among our commercial customers. These accomplishments are a testament to the expertise and dedication of our field teams and supporting functions that provide excellent prospect and customer experiences. HashiCorp products enable the world's largest businesses to adopt a cloud operating model, and this commercial success allows us to continue to invest in making our products better for everyone.
The evolution of RPA from macros to data and web scraping, BPM and RPA. What’s next? Great summary along with the origin stories of the big 3, UIPath, AA, Blue Prism. I got my start in software development back in early 90s through learning Visual Basic so I could write hard core excel macros to automate parts of my job at JP Morgan and certainly see a day when end users will be able to drive more of that without huge integrations.
Unicorns or Big Tech?
60 Tech IPOs potentially ready to go in 2020. The first few will set the barometer for the rest of the year as 2019 wasn’t so 🔥 in terms of performance which means bar is set much higher.
Of the 20 tech companies that went public in 2019 before the WeWork debacle, 16 saw their market values slide afterward by an average of 23% by the end of the year. That too was out of whack with tech stocks in general, and the rest of the market. The Nasdaq Composite rose 10% during the same period.