Thinking about Enterprise Software Startups

I ended up down a rabbit hole of research on Sapphire Ventures thanks to the Origins (Notation Capital) podcast on my flight home from Boston early this morning. Sapphire invests in Enterprise software companies. I got to thinking, if I were to analyze companies in that space with my Product Manager hat on, what would I look for?

These 5 areas came to mind.

1. How will the Product interoperate?

Ex: Zapier, BI fabric, Hybrid Cloud

Is the team thinking about how to move pieces of data around from their app to other apps, from their app to the Enterprise systems, between their Public Cloud and the Enterprise’s on-prem and Dedicated Clouds?

How will insights and raw data from their product be accessible to the Enterprise’s BI Fabric, Data Scientists, etc? How does that strengthen the value of the offering?

2. Where are Users interacting with the Product?

Ex: Mobile, APIs, Slackbots, Echo

Is their product enabling all types of Users to be engaged anywhere? Is extension of the product easy by a Customer Developer via APIs? Is there potential for an Ecosystem to organically grow around the product? Does it feel like a Platform? Is the pretty Mobile app for the on-the-go Sales person just as well thought out as the Developer API?

3. What are the Combinatorial Effects?

Ex: Exongenous Datasets, Data Network Effects

Is the team thinking about combining datasets together to create something new? Does the product have inherent data network efforts? As more people use this, will the value increase?

What two features used together accomlishing something really powerful?

4. What role does analytics play?

Ex: NLP, Computer Vision, Salesforce Einstein

Enterprise data is flowing through the product. How is that data being mined into features? How are signals being extracted using NLP, Computer Vision, Machine Learning, etc? Does the business analysis get smarter the more people use it? Does AI feel like a foundational part of their approach or do they think of it as gimmicky and a nice-to-have?

5. Talk about the Tech Stack

Ex: Microservices, Serverless

Is the team using technologies like AWS Lambda? Do they talk about Reference Architectures and Blueprints? Are they taking a Microservices-first approach?

A few more articles I came across while writing this post:

It’s fun to think this stuff through. I remember the days of meeting with investor after investor while in Techstars and how many of those conversations led to strategy and product improvements.

There’s a lot going on in Healthcare Tech

In 2015, venture funding of digital health companies surpassed $4.3B and accounted for 7% of total VC funding in the US. Deal sizes are growing and the percentage of later stage deals is increasing signaling a maturing in healthcare investments.

In my first six months as part of the Watson Health team, I’ve observed a few trends such as:

Google’s Investment in India will impact Healthcare
Google announced they will train 2M Indians on Android OS and promote internet use among rural women by 2019. In India, 5% of the population has health insurance (“cash for care”) and over 70% live in rural areas without access to quality healthcare (source). No doubt Entrepreneurs and Engineers will be creating major innovations in this space. Related: IBM and Manipal announcement

a16z is talking about Digital Therapeutics
Behavioral change is an area Startups/Developers/Apps have and will continue to embrace. A positive signal is a16z’s movement into this space asVijay Pande talks about in this interview. In this class of app, Email/SMS/Push Notifications/Phone calls are the engagement mechanisms.

VC Investing has increased == Startup activity is very hot
A few months ago Rock Health published their 2015 Healthcare Funding report, a must read. Combine this funding data with a review of new Healthcare products on Product Hunt,new Healthcare companies raising capital on AngelList and scanning Dan Primack’s Term Sheet or any other funding source and you will have a good grasp of the pace.

Regulation continues to provide opportunities
Today, major Health IT spend is in certified electronic health record (CEHRT) technology needed to comply with the federal meaningful use (MU) program, better security systems, and ICD-10 conversion software. Coming soon, additional legislation from the Protecting Access to Medicare Act kicks in mandating “that starting January 1, 2017, physicians ordering advanced diagnostic imaging exams (CT, MRI, nuclear medicine and PET) must consult government- approved, evidence-based appropriate-use criteria, namely through a CDS system.” (source)

Another helpful way to look at the Healthcare VC space is to think about the trends and contrast with VC investments.

Macro-Trends

  • The Consumerization of Healthcare
  • Consolidation of and competition between Hospitals and Integrated delivery systems
  • Strategic Investing (ex: Mayo investing in Helix)
  • Monitoring and Prevention
  • “Obamacare” disruption

Healthcare Funding Categories

  • Health IT Software
  • Digital Health
  • Medical Devices
  • Payer Disruption
  • Biotech

For further reading, I recommend checking out the various portfolio companies from Rock Health, Kapor Capital, SafeGuard, Arsenal and GV. Also checkout the Accelerator programs like Techstars Cedars-Sinai andMore Disruption Please to get a feel for the early stage. CB Insights is always publishing great insights such as this Healthcare IoT market map.

Here’s a brief sampling of some investments I’ve seen recently in these areas:

  • Patient Engagement
  • Prescription Management
  • Healthcare Analytics
  • Genetic Testing
  • Elder Care
  • Life Sciences
  • Medical Devices
  • Nanotechnology
  • Biotech
  • Insurance
  • Gene Therapy
  • Health and Wellness
  • Digital Health
  • Health IT

In Health IT software:

Care Coordination: Patientping, HealthLoop
Payer Management: Oration
Data Analytics: Medivo, BeneStream
EMRs: Elation

In Digital Health we see:

“Communities” like:

  • Health coaches (eating, personal trainers, etc)
  • Community for X
  • Competition
  • Reviews and Ratings
  • Connecting Providers (Patientping), Caregivers to Seniors (Honor)
  • Crowdsourcing data (Human Dx)

“Monitoring” is a huge category including:

  • “smart devices”, watch, smart phones
  • insights, behaviorial analytics
  • personal health and nutrition assistants
  • DNA and other self testing (23andme, Helix, uBiome)

Health and Wellness Platforms like ShareCare, Welltok and Omada Health.

Products like monthly food (Birchbox) and care packages (Citrus Lane).

Content like articles, daily emails and health guides (HealthSherpa)

Dev Tools like HIPPA data stores (TrueVault, Aptible, Catalyze.io) and IoT data streaming (Sense360).

In Biotech we see…

Biorepository, Genetic Analysis, Cellular Models, Regenerative Medicine, Bioinformatic Analytics.

Startups are using new techniques to harden defensibility into their business models such as creating Developer Ecosystems and baking in data network effects. A good example of data network effects at work is Recombine, a genetic testing company. They have built a network of partner clinics that administer its tests; with each new test, Recombine gathers more DNA data which (with appropriate consent) it can run machine learning on to improve its tests and nimbly develop new ones (therefore gathering more data). Recombine uses Machine Learning tools to find and learn patterns in historical data and uses these patterns to generate predictions. Recombine is 4 years old and has raised $3.3M.

I hope this post gets your brain spinning on all of the opportunity and innovation that’s happening in healthcare.

Using Trigger Lists in Product Management

I’m a big fan of “trigger lists”. The exercise of building them and the value they bring to a Mind Mapping or Design process have proved beneficial to me over the years. One of my favorites is David Allen’s GTD Incompletion Trigger List.

Recently, I transitioned from obsessing over providing Developers with APIs that would help them build amazing things with AI to obsessing about Healthcare and how AI can provide better care while lowering costs.

I pounded a Doppio and spent an hour brainstorming this trigger list to help me empathize with Users and better understand Actors in the crazy ecosystem that is today’s Healthcare tech.

I am a…

Healthy person
Cancer survivor
Farmer
Factory Floor Worker
CRO Administrator
CIO
CFO
CEO
Developer
Product Manager
Auditor
Patient
Physician
Nurse
RN
PA
Administrator
Researcher
Daughter
Son
Parent
Community Oncology Clinic
Hospital CEO
CMS Employee
FDA Committee Member

And I have…

Outcome data
Clinical trials
Drug databases
Medical journals
App Store Reviews
Medical Devices
Demographics
Avatars
Full Contact API data
Clinical Trial Participants
Patient data
Lab results
Population data
Reimbursement data
Patent filings
Hunches
Students
Research and Health kit data
Hospital trends
Emails
Tweets
Blog posts
Survey results
Internet searches
Essays
Product reviews
X-rays
Photos
Instagram searches
A list of questions

And I want to…

Find Patterns
Organize my data
Filter my data
Search my data
Understand social media
Build an Android app
Surface correlations
Have access to information

So I can…

Comply with regulations
Stay up-to-date
Collaborate with a Physician
Track my progress
Get credit for a course
Be reminded of an appointment
Find cost savings
Sell an app
Make people healthier
Prove a point
Get reimbursed
Understand health trends
Track my Clinical Trial
Find a Hospital
Research and buy my medication
Predict outcomes
Make more money
Connect data together
Build a treatment plan
Find a Clinical Trial
Predict the Future
Support Meaningful Use
Make evidence-based clinical decisions
Analyze adverse events
Provide better treatment “in the field”

For those familiar with Agile, you’ll recognize the “As a User I want” format of this trigger list.

We all have so much stuck in our heads, try creating one of these trigger lists for something in your world and you’ll be surprised at how it can help.

Why a Product Manager Needs To Wander

Inbox zero, one-on-ones, daily sync calls, daily standups, weekly meetings, roadmap planning, sprint planning, quarterly planning, exec offsites…oh, and…screencasts, wireframes, designs, qa testing, a/b testing, analytics, customer interviews, customer feedback, support tickets, user stories…and on and on it goes.

Whew.

I love to travel for work and always have. I love to hike and ski by myself too. I like doing things like walking my dog, running, riding my bike and riding the bus alone.

I like to wander.

As you walk through the airport, take a moment and observe people and think about their day. Where are they from, how did they start their day, did they drive to the airport or did someone drop them off, what is stressing them out in their life right now? See that annoying person over there? See that pissed off looking person waiting in the security line? How about the friendly looking older couple walking slowly to their gate? What do you think could make their life better? What business are they in? What experience or product do you think significantly impacted their career ten years ago?

Here’s what Brad Feld was thinking about this morning in the San Jose airport.

As a Product Manager, this is one of the most important things I do even though most people don’t get it and ROI can’t be tied to it. Being empathic is often cited as an important trait of a Product Manager. Wandering helps build this muscle. When I wander, I start to see patterns, feature ideas flow and I meet people and have serendipitous interactions about new ideas that aren’t possible in most contexts.

Establishing cadences, rhythms and process is key to succeeding as a PM, especially as your team scales. Just remember to break yourself out of those molds from time to time and go get lost.

Next week I’ll be in NYC visiting the IBM Watson team at Astor Place. My early mornings and late nights won’t be totally packed with meetings and dinners, I will protect that time and wander around. Who knows what I’ll think of.

Can you explain Programmatic Advertising to your friends and parents?

I can’t either and many of the companies I’ve been working with base their businesses on programmatic ad buys.

Basically, programmatic ad buying is when computers buy and sell ads instead of humans.  One in five ads are bought and sold this way today.  The more the computer understands the content on the page you are browsing, the more relevant the ad is that you see.

Here are some terms to know:

Data Management Platform (DMP)
A huge database of customer information that big companies have.

In many of these systems, Marketers can also buy 3rd party data directly from within the system or sell their own data to other systems.

Ex: BlueKai (Oracle)

Demand-Side Platform (DSP)
Software used by Advertisers to purchase ads in an automated way targeted at specific users based on their location and browsing behavior.

Ex: Google’s DoubleClick Bid Manager

Ad Exchange
A Publisher (a big website with lots of traffic) makes ad space available through ad exchanges.

Ex: AppNexus             Here’s a list of the top five exchanges

Hopefully now you an give a quick overview and hang with a conversation about programmatic ad buying!  For further reading, checkout these articles:

WTF is a demand-side platform?
What is an Ad Exchange?

 

Learning from the Launch Festival

thiel
Two weeks ago I shook Peter Thiel’s hand, said hello to Chris Sacca, ran into some old friends and got about 25k steps per day going for beautiful runs and walks around the Marina area of San Francisco.  Those are only four of the fifty or so awesome things that happened in a three day span at the Launch Festival.

tony-hawk
Tony Hawk and Chris Sacca talking to Jason

I’ve come to the Launch Festival a few years in a row now, here’s why I enjoy it so much.

Watching Startups Pitch On Stage

Each day, there are a bunch of Startups that “launch” their companies on stage. As a Product Manager, you can learn a lot from watching tons of pitches. You will see common patterns, demo techniques and recognize the difference between a clear value prop and a rambling one.

Getting Demos and Talking Product

At every conference I like to walk around and get demos. I’ve been in those shoes, standing for 2-3 days in a row on booth duty talking to tons and tons of people. Try and help each person demoing to you. Give them honest feedback, tell stories about how you would use the product and tell them what you understood about the pitch and where you got confused. The best conferences have either the Founder or Product people at the demo pod.

Great People Watching

I like the contrast between early stage companies looking for their first round of funding and the incredibly successful fireside chat speakers. It’s interesting to listen to the fireside chat macro views then walk over to the demo pit trenches and think about how truly hard it is to get a Startup to go big.  And of course, there’s always a wonderful mix of eccentrics, startup t-shirts and tech fashion to observe.

crowd
The Demo Pit, a great place to talk with awesome Startups about life and products

It’s Like Working From Home But At A Conference

During Launch, I spend a lot of time half listening and half writing blog posts or working on wireframes. Being surrounded by tons of cool features, products, apps, designs and ideas is a good influence on my projects.  Sometimes being away from the office is more important than being there for creativity and productivity.

run
Out for a run near Fort Mason Center

A few themes from this year:

  • SMS as the UI
  • Exploring the world (Detour Audio Tours, Recommendation Apps, Curated Social Driven Travel)
  • Group messaging apps mostly targeted at college kids
  • Content Tools (Sharing, Webinars)
  • Food Delivery
  • Wearables
You can see some of the themes merge together in companies like Etch (wearables, messaging)….and a few themes talked about on stage but not well represented in the demo pit:
Checkout the full list of companies that launched at Launch Festival and I’ll see you there next year!

A Deep Learning Primer for Product Managers

Most of my discussions lately with CTOs and Product Managers have ended with me emailing some links and info about Deep Learning. I’m a relative newbie to the space myself so hopefully this is a good primer.

For Product Managers and CTOs, having an understanding of what’s possible with Deep Learning and how the technology could impact your features and stack is quickly becoming very important.

A great summary of Deep Learning from Lee Gomes taken from this article:

The current excitement about AI stems, in great part, from groundbreaking advances involving what are known as “convolutional neural networks.” This machine learning technique promises dramatic improvements in things like computer vision, speech recognition, and natural language processing. You probably have heard of it by its more layperson-friendly name: “Deep Learning.”

Here are few more article I like:

Albert Wenger from USV talks about Machine Intelligence
Shivon Zilis from Bloomberg Beta created a Machine Intelligence Landscape

And, here’s a list of terms to explore:

Word Embeddings
Nodes and edges
Precision and recall
Deterministic
Frame semantics
Knowledge graph
Hypernym and Hyponym
Word sense disambiguation
Hearst Patterns
GPU computing
Dropout
Stochastic Pooling
Cognitive Computing

And, some good people to follow in the Deep Learning space:

Yann LeCun – Facebook’s Director of AI Research
Geoffrey Hinton – Distinguished Researcher at Google and Distinguished Professor at University of Toronto
Yoshua Bengio – Full Professor Department of Computer Science and Operations Research
and Canada Research Chair in Statistical Learning Algorithms
Elliot Turner – Founder AlchemyAPI
Derrick Harris – Senior Writer at GigaOm
Seth Grimes – Industry Analyst

And, some websites to explore:

Google Deep Learning Community
http://www.deeplearning.net
http://www.kdnuggets.com
http://www.r-bloggers.com
http://fivethirtyeight.com
http://www.datasciencecentral.com/profiles/blogs/50-blogs-worth-reading
http://www.semanticweb.com

And finally, some awesome AI videos:

Introducing Spot
Space Invaders