Life As a FA

Disorganized Trying to Organize (Notes from Feb 3 – Feb 9, 2020) August 4, 2020

Productivity tools have been all the rage. Those familiar with adoption of new technology or tools in an office setting bigger than 20 people have likely been through what’s described as the J curve for adoption, popularized by Erik Brynjolfsson and Daniel Rock in their paper (see: https://economics.stanford.edu/sites/g/files/sbiybj9386/f/brynrocksyv_j-curve_final.pdf) of September 2018 on general purpose technologies. There is a slope downward to start for the adoption because the productivity decrease and difficulty in trying to set it up often leads to a loss. Over time and the consistent use, it can go away and lead to the productivity gains we sought in the first place.

Well, I’m in that too many tools, too many valleys section. Bundle and use a tool that tries to do it all? Or unbundle and use multiple tools. If you are trying to optimize notes for one platform and it doesn’t work for your other platforms (mobile/to-go/car), is it optimal? Is 90% great if you miss on the 10% you don’t have a good solution for? I’m not sure. I’m hopeful that audio can work easily – may even jump into Otter.ai for transcription there.

A family friend of ours was so obsessed with keeping track of all his clothes, colors and features that he took it upon himself to build a database of his closet. Upon telling someone else, I recall a similar story for someone who went further and did bar codes on their clothes. You spend so much time obsessing over something you’d love organization over until that organizing takes up the time you were hoping to save. We could take this further and draw similar analogies to corporate, big companies compared to start-ups in growth as an early employee – always something to be done, may not be optimizing the work, just attempting to get something out compared to optimization runs for something that worked until it breaks. Exciting work on either end but ultimately, there’s a line you must draw.

There are tons of benefits to organization for notes, processes, documentation in that someone could come in at any point and figure out what connects to what. There’s a context. I think YourStacks is doing something like this for personal / professional use of tools and games and everything one comes into contact. There have been corporate / enterprise stack technology sites that break down webpage technology or company technologies. Then there are transparent people / companies who document it both privately and publicly for others to see. We try what we think may improve but it’s tough to know where to start.

There’s a lesson to be learned here in starting, trying to going from there. Some of us want to try to optimize all the tools or one tool to its fullest before moving forward. How good is good? Or not good enough? At what point do you pass to the next or add another tool? How many tools are too many? And will we get a bundling or unbundling of different aspects? I’m hopeful we get voice tools that enable bundling for all sorts of this. Currently, I’ve yet to find the solution. Let me know what your set is!

• Dr. Tara Smith, Professor of Epidemiology at Kent State University College of PH, Erik Moses (Wharton Moneyball 2/5/20)
  • Hockey – East and West split of conferences currently, top 4 teams in the East and defending champs Blues in the West are 5th
    • More or less deterministic (coin flips previously) – 50% as max from a conference if coin flips
  • Mookie Betts as trying to get 10 year, $40 mil per because he’s so young
  • Joined in August 2013 after being at Univ of Iowa in Emerging Infectious Diseases
• Chetan Puttagunta, GP at Benchmark Capital (Invest like the Best 1/28/20)
  • Investing in early-stage, MongoDB, Elastic, Mulesoft and advice for POS in enterprise software building Canvas
  • MongoDB – 2012 and had experience building consumer apps from 2007-08 trying to build tech that was pretty limited
    • Felt like an advantage between large companies with proprietary data and tools compared to DIY
    • Met Elliott (MongoDB founder, from DoubleClick) – would ask best devs to work with Mongo and they responded “Don’t need”
    • DB expert – MySQL can work with everything but would miss the class of devs that wanted without planning for scale, app may not work
    • DB could handle scale, millions of users, transactional data by 2015-16, right place right time
    • Oracle as building a great database business and moved into application tier with their apps built on their db
      • CRM, HCM (Peoplesoft) to serve application – 1977 to true leader in databases in 80s, relational
    • Other timing – 1992, for instance, and it would not have worked. Cloud has been so open to these techs.
    • Cockroach for globally scalable, relational db – TimeScale for time-series IoT model, for instance after cloud enabled it
      • Specific use cases have more specifically-tailored results
    • Initiating and potential TAM Salesforce estimates from the start compared to now, where it’s much larger now than suspected
  • Now, enterprise software permeates into companies all over for IoT and consumer tech
    • Caterpillar, Pharma, Financial Services, Shipping companies are all buyers
    • Diva built a CRM system for healthcare vertical on general CRM, Salesforce – multibillion dollar company
    • Client facing software is very important – system that will be helpful and customers will tackle that and tell you directly
  • People come to work and complete a specific job or task – not to work or be an expert with your software
    • New tool into a workflow, only certain amount of walls to learn the software before leaving
    • Go slow to go fast – if you’re building a software solution in the start, build for 5-10 important users
      • Address the needs of those customers – generally applicable to the market (not just the single customer)
      • Won’t become an outside services or dev shop if you deliver services to the general customer
    • Workday and Viva early days – 50% of revenue were services since they entered enterprises (large installation of PeopleSoft)
      • On-prem CRM for Viva – lots of handholding, data migration and such
  • Duffel (Global Distribution System) for airlines selling to consumers
    • Convoluted system to sell and the flows is astounding – entrepreneurs in payments looking to innovate in these instances
    • Found airlines and approached them to “Shouldn’t it work like this?” to get your first partners/customers
    • Patient capital of “go slow to go fast” to super efficient business – spreadsheet vs software
      • Example at Greg Shaw – Mulesoft – burned $8mln from $100mln to 200mln in revenue and burned $4mln from 2-300mln
        • Inside Salesforce, they’ve grown top-line revenues further
  • Unlikely that someone else is building what you’re building
    • 2004 – Salesforce selling CRM, main competitor was Seibel – Salesforce had ACV of $4k and 15 licenses at a time vs Seibel $100k/1k
      • Go after the larger competitors when you have thousands of customers and users ecstatic about your product
    • Won’t run into competitors directly, just objections to your own system, since it’s incomplete
      • Valuing you against their internal/custom solution – take time to create product maturity before prematurely scaling
  • If you’re not missing as an investor, you aren’t taking enough shots
    • 1x your capital if you miss compared to if you pass, miss on 10x or 100x
    • At Benchmark, they’re making 5-10 investments per year, so it’s 1-2 per partner
  • Recruiting and sales – candidates have to feel very good as they go through the proces
    • Only way to scale the software business is to hire the best people to make the software
  • Hard to stand out in SF as an enterprise software integration problem (Mulesoft)
    • Competing with FAANG in a limited labor market, have to be able to recruit amazing talent
    • For start-ups, they have 2 advantages: really exciting for them to embrace remote talent (global market)
      • Running a remote company at scale has very little to do with the tools, and more so with the work culture that’s friendly
      • Everyone meets remotely on video, even in same room
      • Writing a lot of documentation, transparency about thinking in the wikis docs so anyone can catch up
    • Offline ad inventory is very efficient – account-based enterprise software ads at airports – targeting top of funnels
    • How do you transmit a culture that was highly efficient in 10 person to 20 or 100 or 1000 and further, if you’re doing 100% each year
      • 1/2, 1/4, 1/8 haven’t been there for more than 1 year, 2 years, 3, etc..
  • Most portable of early stage investing – Bill Gurley’s blog on CAC and LTV
    • Going down unit economic traps are widely applicable to all tech businesses, consumer, enterprise, etc
      • Can’t drive spreadsheet growth with CAC/inorganic growth for LTV numbers
    • Product engagement – customers in consumer and enterprise
  • Benchmark as 5 equal partners at the firm, no juniors or others
    • Don’t have a NEXT topic that they have to move on to because of this, so open-ended discussions can go very deep
      • Wide networks so they can get useful people to talk
    • Probably not a question that they can’t answer
• Adam Draper, Founder & CEO of Boost VC (20min VC 2/24/16)
  • Seed stage accelerator, blockchain and VR
  • Before Boost, angel invested in 20+ co’s, including Coinbase, Plangrid, Practice Fusion
    • Geography – heart of SV and ecosystem of entrepreneurs, recently adding V/R to build
  • Founder of Xpert Financial after UCLA graduation, helping later stage companies raise capital in private markets
    • Made every mistake – funding, hiring, firing, product
    • Helped early-stage companies build product and raise capital, including for a friend – wanted to mentor in bulk
      • As a family, helping people get to where they want to go
  • Meeting a lot of people while raising money and helping – took him 12 months to raise his fund
    • $6.6mln after reaching out to 3k, 350 meetings and closed ~35 – basically rule of 10
  • Had 52 investments in blockchain accelerator (had about ~120 companies) among currency/contracts-based work
    • Been in industry for 3 years, seeing mature products and higher quality
  • Mentioned MuggleNet as his favorite blog and TechCrunch
  • JoyStream by a solo founder, trying to merge BitTorrent / BTC
• Coronavirus (a16z 16min on the News #21, 1/29/20)
  • Judy Savitskaya – 2019-nCoV – 10-20% common cold vs epidemic ones would be severity
  • Sequencing this virus has been incredibly quick (within 2 weeks of genome) whereas it’s taken longer in past
    • If someone in SF said they had a cold at a general clinic, they could decide if it’s this or not
    • Figuring out treatments and protocols based on genome and live medicine
  • Spike proteins used to enter into lung cells didn’t look as bad as SARS, so they thought it was fine
    • Turns out that it’s actually very similar to the protein
  • Nobody really knows – animal sources of viruses (evolving away from human hosts, time in animals)
    • R0 – number of people you’d expect to get sick for every one person that has it
    • Breaking down variables in R0 – how well does virus transmit itself (easy in air, for instance)
      • Is it good at infecting cells? What’s the population like? (Chinese New Year and traveling often)
    • If virus is not that deadly, additional time in the host that can get infected (individually, if deadly and fast, population better)
  • Increase in genomic medicine – Coalition for Epidemic Preparedness Innovations gave out 3 grants to pharma co’s totaling $12.5mln
    • 12-16 weeks time to develop new drugs based on the new sequence
• Epic Battles in Healthcare, FICO Changes (a16z 16min on the News #22, 2/6/20)
  • FinTech GP’s Angela Strange and Anish Acharya
  • Starting with what is a FICO score – 5 factors: payment history, credit utilization, length of history, new credit, credit mix
    • FICO 2, 3, and 10 now as FICO comes out with reweighting
      • 1 trillion in credit card debt now, so people refi from 25% to 12% loans, but it doesn’t change user spending habits
      • Better job of incorporating debt over a long period of time
    • Designed in 1950s to create a proxy for willingness to pay, originally – now, it’s mostly lenders that have their own algorithms
    • Good lenders will use FICO as a factor but they have their own robust models
  • Hacks such as adding kids as authorized users
  • Old time, 50-100 years credit decisions made on generations, kids play ball with bankers, etc
    • Bank of Italy (now Bank of America), would make loans to Italian immigrants that other banks wouldn’t lend to
    • 2 drivers – willingness and ability to pay
  • International vs US – in US, most decisions decided on score/report, not alternative data
    • In international countries, great way to bootstrap a lending business as a proxy for consumer
    • Difficult to introduce alternative data in the US , cash flow streams for instance
  • Epic’s CEO (EHR information on data) letter sent – with Julie Yoo bio GP
    • Rule that’s been around for 1 year in context of a longer standing law
      • Opening healthcare records from ONC (Office of National Coordinator for CMS), gov agencies overseeing healthcare spend
    • 21st Century CURES Act – Upton and Waldon – means by which we implement the act (healthcare costs will rise, care will suffer)
      • Contending with nonprofit orgs with slim margins
    • Uniquely stored in healthcare data is the doctors’ context (and dialogue) – for what reason would you need the context vs “code”
    • Connecting data between APIs and interoperability – major concept
  • Clause in rule about screenshot sharing – contractual obligations not to share screenshots
    • In trying to see a workflow in a system to connect yours efficiently – one of Julie’s customers at EHR company got hand-slapped for sharing
  • Annual meeting with OMB and ONC for driving sharing and interoperability – Epic wasn’t there – everyone else, systems, plans, incumbents, big tech, EHRc
    • HHS secretary was saying that scare tactics won’t affect what they’re looking for
• Introduction to ARK’s Big Ideas 2020 (FYI 1/13/20)
  • James Wang interviewing Cathie Wood, CEO/CIO at ARK Invest
    • Building on other years – DL, EV, 3D printing, autonomous ride hailing, automation, genome sequencing, digital wallets and Bitcoin
  • New ones – streaming media, aerial drones and biotech R&D efficiency
  • Streaming media – changing behavior patterns should catapult the industry, roughly $80-90bn, projecting $400bn+ in next 4 years
    • Most people couldn’t understand why she was buying Amazon at $5bn cap at her old firm (when no profits)
      • Believed about their revenues would increase CAGR at 25% for 20 years, deep value play (exp growth wasn’t understood)
    • Terrible sales out of box retailers – want to survive and go to online
    • Gaming could consume media, so is value in content or platforms (say, Tencent showing the way, maybe) – larger than box office now
      • Every time music has come out, it has cannibalized the other, older parts as replacement
      • Gaming was different – expansive, explosive market as stacking (mobile only added to consoles and others)
  • Aerial drones – early side of S curve still – released a paper in 2014 suggesting that if FAA would allow Amazon to deliver parcels over 10 mi
    • Amazon, at that time, could have done it profitably for just $1 per parcel for 5 lb package, for instance
    • Food delivery now, air taxis / passenger drones and given battery tech, could save 20k lives associated with heart attacks – drone faster than ambulance
      • Projecting $275bn food delivery (3mi Delivery for cars is about $4.85 – $5) – drones could do it for $.20, profitably
  • Biotech R&D Efficiency as converging Nextgen sequencing, AI, CRISPR editing
    • Impact on pharma and biotech sector
    • Fewer trial failures with DNA sequencing and companion diagnostics for trials, time to market decrease
      • Human trials, CRISPR is curing things such as Beta-_ and sickle cell (2 people)
    • Value-based pricing could be installment payments, for every year you live – reduction of trials and drugs to market, higher pricing utility
      • Margin structure could follow more of 1980s and 90s (mid20-30s) – innovations were exhausted from there, but now should be innovative
    • CRISPR and gene therapies are delivering great results, cures and evidence of these
      • AI and software side with mundane, life science has supported SaaS company in Viva – extremely motivated for productivity structure
      • Most AI companies doing R&D drug discovery are early, M&A ripe – tech in Alpha Go search problems, for instance
    • Analysts can’t just be healthcare, have to be technology as well – permeating every sector
  • Over past year, innovation has been highly valued in private space – too few opportunities with too much capital
    • Private is valued much higher – seeing some disappointments, public markets should be ripe (P/E ratio is not ideal)
    • 5 year opportunities, not 1-2 timeline and finding out how much growth they’re going to deliver