I mostly think of his career when I think about doing a good job at sales in a startup environment.
I know it's a bit of a fairy tale, but nobody can deny Degnan worked his tail off.
I'd love to read more stories of early sales leads.
Full case here: commoncog.com/c/cases/deg...
I'm not going to explain why he left Degnan alone — you can read the case for yourself.
But I just really like this story because it showcases the hunt for PMF across multiple CEOs, board members, and eras.
Snowflake had a great IPO. Degnan had a great outcome.
A couple of years later, Muglia was fired and the board brought in legendary CEO Frank Slootman.
Slootman was ruthless. He cut exec ranks within days of his hiring. He had just one job: prep Snowflake for IPO, which meant targeting the Fortune 500.
But he left Degnan alone.
He had an ally on the board. Right before Speiser left, Degnan asked him to bring on John McMahon. McMahon coached Degnan before board meetings.
During the Muglia era, Muglia and McMahon protected Degnan. Prevented the board from hiring someone to take his role.
By this time, Snowflake was beginning to attack mid-market enterprise companies. They needed compliance certs. Security features. Demanded SLAs.
Degnan needed to show he could run sales across timezones. He recruited a person to run Europe and then someone to run NA under him.
The next challenge Degnan faced was surviving under the next CEO. Speiser stepped down and brought on Bob Muglia, a former president from Microsoft.
Muglia was great at product. He introduced usage-based pricing. Degnan's challenge was to scale sales.
And he figures out that ad-tech and gaming companies needed Snowflake's performance so acutely that they were willing to overlook EVERY flaw with the product.
Degnan begged their first 2 customers to use it for free. But once they did, they loved it and were referenceable.
Degnan doesn't know it yet, but he has to find PMF THREE times.
Initially, Snowflake has no security, zero access control, no SOC II, etc etc. It was literally 'just' a souped-up analytical database. Degnan has to sell this product, and he can't complain. So he tests a bit ...
Degnan says yes. Partly because the founders are old Oracle hands (super impressive), and partly because he was sick of selling commodities.
Of course who knows what lies in the hearts of men, etc etc but he DOES join Snowflake. And then the story shifts into one of finding PMF.
Speiser was, at that moment, putting Snowflake together. The company was but a handful of engineers, and Degnan is pitched a horrible offer:
- 50% pay cut
- Told he'd NEVER be the head of sales (they'd hire someone externally)
- No quota
- Also the database product sucks.
The rough story goes like this: Degnan tires of selling commodity hardware at EMC. He becomes good at sales under John McMahon, a legendary (and famously tough) sales leader.
But after 8 years he's tired; he quits his job after a meeting with venture capitalist Mike Speiser.
Whenever I want a prototypical example of “here's what an effective B2B startup salesperson looks like”, I think of Chris Degnan.
Degnan was the first sales hire when Snowflake was a 16-person stealth startup. 7 years later, he was CRO of an $81B company.
Pretty good prototype!
Full essay below: commoncog.com/how-experts...
This one clocks in at 11k words so it's REALLY long, but — well, I include a case study at the very end to demonstrate what it's like to change your sensemaking about AI.
I think you'll find this useful.
Also, for good measure, we talk about how, uhh, if you take the Data-Frame theory seriously, you also have to conclude that Confirmation Bias is fake.
Yes, really:
The Data-Frame theory is simple to articulate (it's captured in a single pic, below) but the implications are rather profound.
By the end of my essay, we talk about a) how experts sensemake differently from novices, b) what traps to look out for, and c) how we apply it to AI.
This week's Commoncog essay is about that theory.
The theory is 19 years old. It comes out of some research that was funded by the US military. Its name: The Data-Frame Theory of Sensemaking, by Gary Klein and colleagues.
Also, I made a pretty cover for the paper!
At the end of that piece I said that in order to improve we needed to talk about how sensemaking ACTUALLY works.
We needed some theory.
And for good reason: if we know how experts sensemake differently from novices, for instance, we could copy them and improve ourselves.
Two weeks ago I wrote an essay titled "How to Make Sense of AI." It struck a chord. Folks shared it with their friends. One friend printed it out to give copies away.
That essay laid out a method of making sense of AI developments without losing your head. But it was not enough.
I don’t say this enough, but I find @DellAnnaLuca’s writing incredibly clear, pragmatic, and useful. I recommend everyone who is interested in operational excellence to buy his books.
Oh, brilliant, interview with Jobs about Juran's impact on him: www.youtube.com/watch?v=XbkM...
FT link (paywalled): www.ft.com/content/080...
Archive[.]is link: archive.is/W2qjQ
And if you want a taste of what these ideas are about, my viral essay on the topic: commoncog.com/becoming-da...
Choice quote, mildly paraphrased: [Steve Jobs] realised that “great people and brute force” was no longer good enough.
and ‘You had to “see everything as a repetitive process, instrument that process, and find out how it’s running.”’
Sure sounds familiar, doesn't it?
Surprise, surprise: Steve Jobs understood process control. I didn't realise that he learnt quality from Joseph Juran, a Deming contemporary.
This is, incidentally, where “blameless post-mortems” and “fix the system, don’t blame the person” comes from.
Full breakdown is available here: commoncog.com/demand-idea...
Members only.
(But you can, of course, read the book, listen to Furst’s interview on the James Altucher podcast, and work out what to do). jamesaltuchershow.com/episode/how...
Bottom line:
Post-facto frameworks (Sales Safari, JTBD) are great once you have customers.
Ex-ante frameworks (Lean Startup, Customer Development) have real limitations that most people miss.
The Heart of Innovation is the best ex-ante framework I've found.
A couple of weeks ago, I did a tight, actionable summary of HOI’s best ideas.
The big idea is that demand HIDES in a situation.
It’s a little difficult to explain these ideas in a social media post, so I’ve included a screenshot as preview.
The 2023 book ‘The Heart of Innovation’ contains the best ex-ante demand framework I’ve found. (And trust me, I’ve been looking for a bit).
Last year, I wrote a summary: commoncog.com/the-heart-o...
That summary did well, but I think it could be clearer.
So what do you actually do when you have zero customers and need to find demand?
Most founders just muddle through. They interview people, build things, hope something sticks.
But I think there’s a better way to think about this.
Finding demand ex-ante is HARD. Every time I built a new product from scratch, I’d notice that it was all a crapshoot.
Some ideas took off. Most died.
No way to tell which would work beforehand. I just knew all the fancy frameworks didn’t seem to work as advertised.
And there are ‘urgent’ problems that people simply DO NOT buy to solve.
Hell, the following anecdote (from multi-time founder and tenured professor) Merrick Furst should terrify you: