The “Tim” story

I had the chance to work on a discovery sprint recently. During this two-week sprint, I revisited a bunch of agile delivery fundamentals in a way I haven’t in a long time. The project was suffering from some of the great, classic mistakes of software delivery we all know and love such as working in silos, internal politics, inability to deliver anything into production, finger pointing, comments like “we tried agile and it didn’t work” and so on.

Our discovery sprint team started using an example we called the “Tim” story. Tim is one of the executives in charge of the project.

After doing twenty user interviews, looking at code and reading a business case and other artificacts, one of our findings was the project was using a waterfall approach to manage a project with complex business rules, an ERP system. The team would talk about insufficient requirements and failing tests. Everyone was blaming each other.

Our recommendation was for Tim to be migrated out of the old system into the simpliest version of the new system that could be deployed to production. Because the team were working in silos, they had accomplished a great deal in their own silo but nothing worked together thus zero business value had been delivered in two years of working on the project.

Tim would receive his paycheck from the new system and if that failed, he could receive a handwritten paper check, bugs would be fixed and we’d try again two weeks later. Because Tim as an employee is one of the simplest payroll scenarios, the salaried employee with no special circumstances, we described this to the team as “the happy path”. Once Tim was being successfully paid by the new system, the entire management team working on parts of this project would be migrated. This is a way to deliver small iterative value while also demonstrating how committed the executives and team members are to the effort.

Now, a lot needs to happen before Tim can get his first paycheck. The system needs to be deployed to production, how a single employee is migrated from the old system to the new system needs to be understood, there needs to be confidence in the basic security of the production system and more.

As additional groups are migrated, the complexity will increase. For example, an employee that is working two different jobs with overtime and several dependents. They split their paycheck into several bank accounts and had previously worked at the company, quit and has now returned to their old job.

The team should take these complex use cases that the new system needs to support, focus on them as a team one-by-one and see success. They should continue in this “continuous improvement” phase of the project as new groups of employees are onboarded.

Contrast

Now, contrast the “Tim” story with the project team’s current way of working. For over two years the team has been assembling a complex list of never-ending requirements aspiring to a place where “we have all the requirements” (unrealistic) and “we have confidence the system works for all HR and payroll complexities” (impossible) and “then we can do a big bang cutover to the new system” (dangerous).

When our discovery sprint team talked about the happy path versus waterfall big bang approach in our readout it resonated with the whole team. You saw head nods from non-technical folks, agreement and understanding from Tim and validation from others saying things like “We tried 5 test cases six months ago and they all failed but they were our most complex payroll scenarios involving overtime pay, employees working two jobs and more. We never thought to start simple. This totally makes sense.”

In past products I’ve worked on, I’d tell a very similar story about “how we can take the first $1.” Executives would often scoff at this and talk about how we need to support millons of dollars of revenue and get inpatient. However, it’s powerful. Understanding the first simple flow, the happy path, the MVP, etc is still a great thing to lean on if you are trying to help unstick a giant enterprise project or working on your next small startup.

How Product Managers Can Mess Around With Open Datasets

Most Cities, States and Federal Agencies are working on some type of Open Data initiatives. The most common is an “Open Data Portal” that makes it easy to grab and use datasets:

https://data.cincinnati-oh.gov/
https://data.colorado.gov/
https://data.commerce.gov/
https://www.data.gov/

Some cities are using Open Data to publish performance metrics like the Seattle Police Department or Louisville’s LouieStat.

Civic Leaders working on these initiatives cite promoting transparency in Government, improving performance and providing data for innovation as reasons why Open Data is so important.

As a Product Manager, it’s helpful to be familiar with what’s out there and how you can play around with these datasets to better understand how your product may benefit.

Before you dive into querying APIs, checkout a few of these projects to see the end result of building something with Open Data.

USAFacts
CollegeScorecard
500 Cities Project
Data.gov

Ok, now let’s dig into some datasets you can play with.

Socrata’s Open Data Network
Socrata hosts over one hundred different data catalogs for governments, non-profits, and NGOs around the world. Checkout their Open Data Network where you can search for datasets.

For example, here’s a page about San Bernardino County Employment. Click “View API” to end up on a page giving you data and an API call you can paste into your browser or Postman.

Namara
Namara has organized a bunch of public datasets into a beautiful UI. Create a free account, sign in, create a new project then click Open Data in the left column to search and add datasets to your project. You can view the table data and manipulate it or call the data using their API.

https://api.namara.io/v0/data_sets/{DATA_SET_ID}/data/{VERSION_ID}?api_key={YOUR_API_KEY}

In your project settings, you can generate an API key. Then, in each dataset you can click “API Info” and get the data_set_id and version_id.

ProPublica
You can use ProPublica to request data about Congress such as a list of Recent Bills and Member Voting records.

https://propublica.github.io/congress-api-docs/#congress-api-documentation

You’ll need to request an API key by emailing apihelp@propublica.org then pass that in the X-API-KEY header.

For example, to query Rep. Jared Polis’s voting record:
https://api.propublica.org/congress/v1/members/P000598/votes.json

Open Data and the big IaaS Platforms

Another approach is to checkout Public Datasets baked into AWS, Google Cloud Platform and IBM Bluemix.

This is a great example of using Google BigQuery on NYC Public Datasets.

AWS hosts a bunch of Open Data in S3 buckets.

IBM, as part of the NOAA Big Data Project, has built an easy way to download tons of data.

Additional Reading

A few hashags to search around on are #govtech, #opendata, #opengovdataand #opengov. Follow people like @Josh_A_New, @JoshData, @DataInnovation, and the @SunFoundation.

Here are a few links related to Open Data policy and relevant news.

Some history on U.S. Federal Open Data Policy

DATA Act passed in 2014, America’s first open data law. It directs the federal government to transform all spending information into open data.

Conversation on the future of Open Data as Administrations change and the Preserving Government Data Act of 2017

The OPEN Government Data Act “directs all federal agencies to publish their information as machine-readable data, using searchable, open formats and requires every agency to maintain a centralized Enterprise Data Inventory that lists all data sets, and also mandates a centralized inventory for the whole government (data.gov)”.

Open Data 500 US is an interesting survey results showing what kinds of companies use which agencies’ data.

Thinking about the Government’s Role in Healthcare and Life Sciences Technology Innovation

My personal philosophy of Government is one that takes a long-term view, provides infrastructure and conditions to enable Citizens, and holds the massive responsibility to self-regulate and optimize itself.

I have read four books recently that have really informed my views and inspired me about the role of our Government in Technology:

I want to see Government continue giving Entrepreneurs Access to:

  • Data
  • Policy Makers and Regulators
  • Pilot programs

The Entrepreneurs, Venture Capitalists and Big Tech Giants will build products, fund ideas and get innovation to the people. Government will ultimately set the regulations. Lately, Government has also taken on an increasing role in sponsoring hackathons and innovation challenges (Challenge.gov) to promote adoption of their data sources and generate awareness of their role in the overall tech ecosystem. From the JOBS Act to Patent Reform to Cybersecurity to the Open Data Initiative to the America Invents Act, there are many good examples of progress outlined on Whitehouse.gov.

I also recommend this Recode Decode interview with the U.S. Chief Data Scientist DJ Patil for good examples of how various Government Agencies are using data to iterate on problems.

As I zoom in on Healthcare and Life Sciences I think about:

  • HL7, FHIR and data interoperability
  • Open Data Initiatives and Data.gov
  • FDA regulation, Medical Devices and GxP compliance
  • HIPPA compliance
  • Cures Act
  • Moonshots
  • Why do we allow drug ads?
  • Reproductive rights
  • Medicaid, Medicare
  • ACA impacts and opportunities

There are incredible examples of Government using their scale to make progress such as the Million Veteran Program (Genome study) in which Veterans volunteer their DNA analysis and health information into a massive database for Researchers. Government is also funding technology pilots and new approaches to improving care such as a Mount Sinai paramedicine pilot in which Paramedics consult via telemedicine with Docs and treat the patient in their home without transporting them to the hospital.

I hope our Government continues to build upon the power of open data, collaborate with Entrepreneurs and view Healthcare as a fundamental right for our society and citizens.

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.

Healthcare and Life Sciences Corporate Venture Capital

Moving from a background in AI and Developer Tools to Healthcare has required a crash course in healthcare policy, finance, technology and regulations. I’ve always looked to investing trends and analysis to help me better understand a market. Looking at Corporate Venture Capital (CVC) in healthcare and life sciences is a fun exercise.

“over 48% of the top Fortune 100 companies have a corporate VC arm and these corporate VCs have participated in 24% of total deals globally for the past 4 years.” [source]

First, a few basics on Corporate Venture Capital…

Why does the Corporate Venture Group exist?

  • Generate financial returns for Limited Partners (LPs) including parent Corporation
  • Generate revenue for the Corporation
  • M&A channel
  • Licensing, Divestiture, Partnerships
  • Foster Innovation, Identify Global Market Opportunities, funding initiatives that need to exist outside parent Corporation structure

What do Corporate Venture Groups do?

  • Build a Portfolio of Investments that could range from Series A to “evergreen”
  • Build an Ecosystem of Strategic Partners
  • Generate revenue from revenue share deals and equity positions
  • Invest as a Limited Partner (LP) in other Venture firms

So, what’s going on in Healthcare and Life Sciences Corporate Venture funds?

From this CB Insights report, you can see the most active funds include Merck Global Health Innovation Fund, Kaiser Permanente Ventures, Lilly Ventures, Siemens Venture Capital, Pfizer Venture Investments, Novartis Venture Funds, GE Ventures and of course Google Ventures.

Corporate Venture Capital (CVC) in Healthcare

Includes Information Technology, Therapeutics, Diagnostics and Drug Delivery, Diagnostics, Behavioral Health, retail healthcare and rise of consumerism, new provider payment models, delivery of care, implementation of the Affordable Care Act, Data and Analytics.

Kaiser Permanente Ventures

Siemens Venture Capital

Mitsubishi Healthcare

Vesalius Ventures (Vanguard Ventures, Fremont Ventures and Guidant Corporation)

GE Healthymagination

Merck Global Health Innovation Fund

Johnson & Johnson Innovation

Zaffre Investments (BCBS of Massachusetts)

BlueCross BlueShield Venture Partners

MemorialCare Innovation Fund

McKesson Ventures

Cambia Health Solutions

Rex Strategic Innovations

Corporate Venture Capital (CVC) in Life Sciences

Includes Biotechnology, Biopharma, Medical Devices and Diagnostics, Drug Discovery, Pharmaceutical services, Pharma value chain.

Nova Novartis Venture Fund and Novo Ventures

Mitsubishi Life Science

MedImmune Ventures (AstraZeneca)

SR One (GlaxoSmithKline)

Lilly Ventures (Eli Lilly and Company)

Amgen Ventures

Roche Venture Fund

Samsung Ventures

F-Prime Capital Partners (Fidelity Biosciences)

Takeda Ventures

Baxter

Pfizer

Some additional reading:

Making Sense of Corporate Venture Capital

The 117 Most Active Corporate VC Firms Of The Last Year

Digital Health Funding: 2015 Year in Review (Rock Health)

Tencent, Google Capital Invest In Indian Healthcare Startup Practo

Medtronic, Sequoia launch $60M VC fund for Chinese med tech startups

Understanding the portfolios of these Healthcare and Life Sciences Corporate Venture Capital funds, the backgrounds of the Partners, where they are based and what companies they invest in help paint a picture for where things are going.

To learn a bit more about Healthcare technology read There’s a lot going on in Healthcare tech right now.

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.

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 about Startup Investing

How are startups raising the seed funding they need to get to the next phase?  This is a very simple overview of a few vehicles that help startups raise capital and some new and interesting trends in the ecosystem.

Syndicates
An Angel or Fund can lead a Syndicate on AngelList. Investors that are backing the Syndicate have the option to invest in specific deals that are being syndicating. Syndication allows Investors to pool their resources and share risks.
Ex: FG Angels

Funds
Funds on AngelList are “index funds” or “fund of funds” that give Investors broad exposure to lots of deals within a specific vertical. An Investment committee votes on deals that have been syndicated.
Ex: AngelList Consumer Fund

Corporate Investment in Super Angels
Recently, Mailchimp invested $2M into Sig Mosley’s $30M super angel fund.  Thriving companies like Mailchimp see this type of investing as a way to diversify cash, help startups and get early access to the most innovative companies in their space.

Accelerators
Many startups choose to go through an Accelerator program. Typically an Accelerator program will take an equity stake in the startup and provide seed capital and a convertible note option, a loan that converts into equity at some point in time.
Ex: Techstars provides $118k for a 7-10% equity stake

Angel Investors
Individual Angels are a core part of the ecosystem. Startups will often bring on several Angel investments in combination with going into an Accelerator or using AngelList to assemble the seed capital they need.

Crowdfunding
Hardware and hard goods startups are using a combination of Angel investing to get the company running with a prototype built and Kickstarter to fund the first product release.  Ex: Ubooly

I recommend reading Venture Deals by Brad Feld and Jason Mendelson to get schooled on VC investing.

My Last Day At PivotDesk

David and I have decided that it’s time I leave PivotDesk.  This has been the hardest choice of my professional life.

I wrote the team at PivotDesk a few days ago and stopped by the office to wish everyone well.   We have made commerical real estate more efficient and cost effective for everyone from entrepreneurs to small business owners to brokers and I’m extremely proud of that.

Hopefully this post helps others avoid a similar situation in their companies and gives some context on how this can happen to the best of teams.  As several mentors and incredible friends have told me, this is way more common than people realize.

Alright (sigh), now that’s out of the way so let’s talk about what the hell happened.

Over the past six months I gradually lost the confidence of my teammates.

Here’s how it happened.

Tunnel Vision
For the past three years I’ve woken up in the morning thinking about how to grow PivotDesk and fallen asleep almost every night thinking about what else I should have done that day.  At the park with my kids I was always reviewing my task list, on the weekends I’d crave time alone so I could think about what’s coming up, everything was about growth, scale, more.

I was so caught up in this type of thinking for so long that I had blinded myself to all of the other things that make a team truly work well together.  As all teams do, we’ve had a few disagreements over a variety of situations.  I handled these situations with little care, love or respect for my teammates.  I just wanted it over so we could go back to growth, scale, more.  Little did I realize, I was slowly eroding the support from my team that is needed to succeed together.  And worse, I was growing defensive and outwardly frustrated as my stress level rose.

Stuggling With Co-founder Balance
I began as VPE at PivotDesk and after our MVP and Engineering team took shape moved to VP of Product where I’ve been for the past two years.  I also have a second job as Co-founder.  This job has no job description or performance metrics, rather it’s a mix of a zillion different things from sales to ops to bizdev to customer support.  Finding the balance between these two roles has not been easy and is another reason I ultimately lost the team’s support.

Just a few examples:

  • Taking coffee meetings instead of attending daily standup.
  • Running the company meeting instead of focusing on a great product update during that company meeting.
  • Letting my week fill up with sales, finance, pr and exec team meetings and not leaving myself enough time for deep product focus.

As I asked others on my team for feedback once I realized things were going sideways I heard things like “No one really knows what you do anymore.”

Making the Hard Decision
Saying “hard decision” doesn’t even come close.  When David and I talked about the possibility of me leaving I started visibly shaking, my mouth turned dry and I started having trouble breathing.  As the words “If I’m getting in the way at all, we should seriously consider that I unhook from PivotDesk” came out of my mouth it was surreal.  All of the emotions started kicking in; the Imposter syndrome, anger, disbelief.  We decided to give it a week, talk to the people that have seen this the most, then regroup and make a decision.  For a week I let all of the “Co-founder projects” slip and focused only on product.  I felt like our team was in perfect harmony and kicking ass.  We released a major feature and were collaborating perfectly on the next feature.   Our OKRs were lining up to our analytics informing what we were building and planning on our roadmap.  Ironically, it was one of my favorite weeks of work ever in my career.

At the end of the week David and I spoke again, there was no change in the team’s support, it was time to unhook.  I was crushed.

When talking with a good friend and mentor of mine this week he said “You are not special!”  As I laughed and said, “Hey, thanks a lot.  Is that supposed to make me feel better.”  He said yes and went on to talk about seeing this happen in different ways over and over in fast growing startups.  The company changes so fast and sometimes people and teams simply aren’t the right fit for the phase of the business anymore.  This did make me feel better and he encouraged me to not assume 100% of the burden.

The Next Chapter
It’s incredible how much of one’s identity can get wrapped up in the company they are trying to build.  The constant pitching, the t-shirt wardrobe peppered with company logos and talking about the business at every holiday, lunch with friends or phone call with Mom really adds up.  It’s what you live and breathe as a startup founder and I wouldn’t have had it any other way.

For me, one thing has always stayed constant over the past 20 years of my professional life whether working at a big company or startup, the love of building software.  From the first 10 years as a software engineer through today as a product guy, day-dreaming about cool ideas and turning them into reality is thrilling.  I still get nervous as a I watch customers, friends and teammates use the products I’ve help build.

I don’t know exactly how the next chapter reads, but I’m positive using PivotDesk to share office space will be a part of the mix.