Category Archives: Management

Traditional B2B Sales is Dead, Long Live the UCE?

In the land of disruption, there’s always something dying and something lining up to replace it, so we’re pretty used to hearing things like “on-premise is dead, long live SaaS.”  Sometimes, they’re right.  Despite the 2008-era views of our resident luddite below, SaaS really did kill on-premises.

Sometimes they’re wrong.  Despite years of hearing, “the data warehouse is dead, long live the data lake,” the data warehouse is doing just fine, thanks.  Snowflake can tell you 60 billion reasons why.

Sometimes, they’re both right and wrong.  Data lakes are doing pretty well, too.  Not everything is zero sum.

You don’t hear this just about technologies, but business models, too.

When the Internet eliminated sellers’ monopoly power over information, I heard, “traditional B2B sales is dead, long live facilitating buying processes.”  This was right and wrong.  B2B sales wasn’t dead, it just changed.  When buyers can get more information themselves and advance further without needing sellers, reframing sales as facilitating buying is a good idea.

When product-led growth (PLG) became the rage, you started to hear it again:  “traditional B2B sales is dead, long live PLG.”  While companies like Atlassian really did dispense with traditional B2B sales, other companies — like Zendesk, Slack, and Twilio — showed the power of blending the two models.  Heck, even Atlassian eventually blended them.

I think of PLG as embracing the continuation of a trend already started by the Internet.  In phase one, buyers no longer needed sellers to get basic product information.  (It’s almost hard to believe, but back in the day, if you wanted even a white paper let alone a demo, you had to talk to a seller.)  In phase two, buyers no longer needed sellers to get hands-on product trial.  It’s the same transformation, just applied to the next two phases down the funnel.

While some companies consider trials customers (and ergo need to count them in churn), I think most enterprise startups should consider trials leads, and the ones who do the right things with the product become leads worthy of passing to sales.  Because they’re qualified by product usage and not marketing actions, they’re called PQLs instead of MQLs.  (Ask my friends at Correlated, or any of the new PLG CRMs, to learn more.)

The other day an old friend of mine, now a highfalutin GM at a big-name software company, forwarded me this article, Traditional B2B Sales and Marketing are Becoming Obsolete.  So, anticipating the content, I donned my “it’s PLG and enterprise, not PLG or enterprise,” gloves and got ready to fight.

But I was surprised.  Instead of saying, “B2B sales is dead, long live PLG,” the article threw me a curveball:

“B2B sales is dead, long live the unified commercial engine (UCE).”

Huh.  The what?

Who wrote this, I think?  Ah, it’s some guy from Gartner.  Before I can add, “and they should stick to IT prognostication,” I see that “some guy” is Brent Adamson, coauthor of The Challenger Sale, one of my top five favorite sales books.

Darn.  Now I have to read this eight-page article and figure out what I think.  The rest of this post is the result.

The Article:  Summary and Analysis
The article argues that it’s no longer enough to try and integrate (in the sense of align) sales and marketing, we should instead unify them.  That’s because buyers have more access to information (including hands-on trials), buyers have access to that information via multiple channels (e.g., vendor websites, review sites), and buyers don’t want to interact with salespeople (which is not exactly new, though he argues that younger people want to interact with sellers even less than older ones).

Sales is thus fighting for relevancy in the buying process and seeking to regain customer access.  The linear model is dead, long live the unified model.  In short:

Helping today’s B2B buyers buy isn’t a sales challenge, nearly so much as an information challenge (or, alternatively, an information opportunity).

He begins with motherhood and apple pie:

The companies that best provide customers the information they most urgently seek, specifically through the channels they most clearly prefer, are in a far better position to drive commercial success in today’s rapidly evolving digital commercial landscape.

He moves into rhetoric to amp things up:

While once a relatively accurate proxy for the underlying buying behavior it was meant to approximate, the serial commercial engine is hopelessly out of date — and dangerously out of sync — with how today’s B2B buyers buy.

With a requisite Gartner dash of profundity:

Today’s buyers are not only channel agnostic in terms of behavior, they’re digitally dominant in terms of preference.

I think that means people like to research shit online before buying it.  Got it.  Stipulated.

I always say that any good sales pitch is 80% tee-up and 20% knockdown.  Now, on the receiving end of such a pitch, I need to advise some caution in that approach.  At some point people want to hear your solution; I’m on page 6 of what’s barely 8 pages and still waiting.  It’s always easier to agree on the problem than the solution (e.g., child poverty, wealth inequality, climate change).  It’s why the 80/20 formula works — you get people agreeing with you, sounding smart, heads nodding, and then you shift to a credible solution that drives your agenda.

But you can’t wait too long to shift to the solution (so I should probably revise my rule to 60/40).  And you should introduce the solution from first principles, not via a case study (which you can always present later, as proof). And if you’re going to introduce the solution via a case study anyway, it shouldn’t be a 1300-person company based in Calgary that I’ve never heard of.

Yet, here I am, about to learn how SMART Technologies found the answer to this pervasive problem by “rebuilding it from the ground up.”  But first, I need to learn about SMART Technologies.  I am now at page 6.75 of an 8.25 page article and still not heard the solution.

The answer:  completely dismantle traditional sales, marketing, success, and service altogether and reconfigure them into a unified commercial engine (UCE).

I’m now thinking:

  • Can you partially dismantle something?
  • Can you completely dismantle something without it being altogether?
  • Where did success and service sneak into things?  While I’d certainly, almost definitionally, want to put all customer-facing teams into a unified engine, how is it that success and service are totally omitted from the argument’s tee-up?

You create a UCE by:

Careful mapping of customers’ buying journeys across a range of predictable “jobs to be done” as part of a typical educational technology purchase.

Never one to miss a gratuitous Clayton Christensen reference, I have to observe that while I am big believer in his work and the jobs-to-be-done framework, I think this is something of a misapplication.  Christensen’s point was about innovation — if you think of products as hired instead of bought, and hired to do specific jobs, then you will anchor yourself in the customer’s point of view when contemplating new products and features.  Think:  not how can we make this milkshake tastier, but how can we make this milkshake more effective when it’s hired as a one-handed commuter breakfast.  What we’re talking about at SMART is simply mapping customer journeys.

When you do that careful mapping, this happens (or, at least, this is what happened at SMART):

Through that initiative the team identified five common buying jobs (Learn, Buy, Order/Install, Adopt, Support) and established an internal team specifically deployed to support each one, reassigning nearly every member of legacy marketing, sales, service, and success staff as a result. In all, over 250 team members received new job designations as part of the process.

You can’t do a re-org these days without creating a center of excellence, so SMART created three:

SMART created three centers of excellence, where they consolidated otherwise duplicative efforts across traditional functional boundaries, one for data and analytics, and one for customer insights and positioning, and one for creative and digital experience.

Those, by the way, sound like a good idea.  I like centralized, specialized support teams, particularly in areas where we’re trying to present one face to the customer.

And then, the re-organization:

Finally, the team then deployed their staff in geographically aligned “pods,” where each pod contains members supporting each of the respective five buying jobs. So, the pod for the southeast United States, for example, is made up of combination of individuals tasked with supporting the entire range of customer jobs from Learn to Support across all relevant digital and in-person channels (including third-party distribution).

In short, run your regions in the USA more like you run countries in Europe.

It’s neither a bad idea nor some insanely different approach.  It does create the need, however, for sophisticated regional leaders who are capable of aligning on both dimensions of the matrix.  Concretely:  is the French country marketing manager part of the French team or the marketing team?  Answer:  it’s a trick question.  The answer is both and they need to learn which way to look, when, as they face managerial decisions — e.g., look to the CMO for questions on messaging and positioning, look to the French country manager when prioritizing campaigns and investments.

I’m going to ignore the end of the article where the VPs of sales and marketing proudly introduce themselves “the former heads” of their respective departments, because they both seem to still work at the company and do something, though the article doesn’t say what their new titles and jobs are.  I’ll assume, hype and semantics aside, that they’ve implemented some sort of functional vs. pod matrix.  As one does with countries in Europe.

Before wrapping up, let me challenge some of the more detailed points in the tee-up.

  • Yes, the machine is by default linear.  But that’s just the first pass.
  • Contacts that don’t make it MQL or SQL get put into nurture and nurture is not linear.  Nurture is a popcorn machine where we dump kernels in, expose them to heat, and over time and in a pretty random order, the kernels pop into recycled MQLs.  I’ve run companies where half of all MQLs are recycled.
  • There’s the question of whether we should nurture people or accounts, as we would in account-based marketing.  Nurturing accounts is definitely not linear, it’s like having one popcorn machine per account.
  • There is no 11th Commandment where God said that nurture shalt be digital only.  While a lot of nurture is automated digital, marketers should remember that a nurture track, broadly defined, can also involve live events (e.g., C-level dinners), dimensional marketing (e.g., mailing a coffee-table book or a Moleskine), and live interactions  (e.g., SDR or AE outreach).  Nurture doesn’t definitionally mean a sequence of emails, nor should it.
  • The part of the linear handoff I detest is when sales “waives off” marketing once an opportunity is in play.  This happens less frequently than it used to, but it reveals a deep lack of trust that should be fixed by destroying walls, not erecting them.

I’ll conclude by saying I think the article misses the most important point in organizational design.  When it comes down the game on the field, who calls the plays and the audibles?  Sure, we have a playbook, and we all know the play we’re supposed to be running.  But things have changed.  There’s a new participant in the meeting.  They mentioned a new competitor who we didn’t know was in the deal.

With a group of talented people, they’ll usually be several different and vocal opinions expressed on how to proceed.  The AE may want to reschedule the meeting.  The SC wants to proceed with the demo.  The consultant thinks we shouldn’t be in the deal in the first place.  The sales manager thinks we can win it because the champion has our back.  What do we do?  Who calls the plays and the audibles that modify them?

In my mind, the person with the quota wins.  As the old joke goes about breakfast:  the chicken is participating, but the pig is committed.  In a world where accountability for results legitimizes decision-making authority, it’s not enough to have a pod/commune and say we can all work it out.  Sometimes we can’t.  And often we can’t fast enough.

Whether you call that person the regional pod leader or the country manager, the role needs to exist and they need to take lead on deal strategy. Everything else is a supporting resource.  Which is why I think marketing alignment with sales is enough.  Yes, we need to collaborate and yes we need smart managers to work in the functional/regional matrix.  Yes, in the case of marketing, we need field marketing to ensure ground-level local alignment.

But do we need to reorganize everything into regional pods?  No.  We just need to work together and be aware that buyers have more information, options, and control than ever before.

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End note
The irony is I ran a company in a pod structure, MarkLogic, where we had vertical pods (aka, business units) where we didn’t have sellers, SCs, and consultants.  We had Federal sellers, Federal SCs, and Federal consultants — all working for a VP/GM of Federal.  Ditto for information & media.  But we did it not in the name of “traditional B2B sales is dead because buyers have more information,” but in the name of a vertical go-to-market strategy where we wanted specialization and alignment.  Pods can work.  It’s all about strategy first and organizational design to support strategy.

Appearance on the Precursive Podcast: The Role of Services in Today’s SaaS Market

A few weeks back, I sat down with Jonathan Corrie, cofounder and CEO of Precursive — a Salesforce-native professional services (PS) delivery cloud that provides PS automation, task, and resource management — to discuss one of my favorite topics, the role of professional services in today’s SaaS businesses.

Jonathan released the 48-minute podcast today, available on both Apple and Spotify.

Topics we discussed included:

  • The Hippocratic oath and executive compensation plans (do no harm).
  • How to frame the sales / services working relationship (i.e., no chucking deals over the fence).
  • Why to put an andon cord in place to stop zero-odds-of-success deals early in the sales process.
  • How to package services, including the risks of tshirt-sized QuickStart packages.
  • How to market methodology instead of packages to convince customers of what matters:  success.
  • The myth of services cannibalization of ARR.  (This drives me crazy.)
  • The alternatives test:  would a customer pay someone else to be successful with your software?
  • Selling mistake-avoidance to IT vs. selling success to line-of-business executives.
  • How and why to bridge “air gaps” between functions (e.g., sales, customer success, services).
  • How to position the sales to CSM “handoff” as à la prochaine and not adieu.
  • The perils of checklist-driven onboarding approaches.
  • The beauty of defining organizational roles with self-introductions (e.g., “my name is Dave and my job is to get your renewal”).
  • The three types of CSMs — the best friend, the seller, and the consultant — and how to blend them and build career paths within the organization.
  • Top professional services metrics.  Caring about (versus maximizing) services margin via compensation plan gates.
  • The loose coupling between NPS and renewal.

Thanks again to Jonathan for having me, and the episode is available here.

Everything I’ve Learned About Recruiting and Interviewing

The other day a founder asked me about interviewing because a candidate had described me as “a great interviewer,” and she wanted to know why. (And for that matter, so did I.)

Emboldened by this seeming endorsement, I dashed off what turned into a lengthy email on interviewing and recruiting, a topic about which I am passionate not because I think I am good it, but because I think I am not.  I find interviewing and recruiting difficult, have made plenty of mistakes over the years, and the consequences of those mistakes are invariably painful.  The wise manager approaches recruiting as a great opportunity to strengthen the organization, but does so with some degree of humility, if not trepidation.

Thoughts on The Recruiting Process
Let’s start by sharing some things I’ve learned over the years on the recruiting process, before we dive specifically into interviewing.

  • Know what you’re looking for.  Most troubles begin here because people fail to ponder and debate what they are actually looking for, so you do the equivalent of walking into Costco without a shopping list.  For example, for a seller, do you require software applications, platform, or data & analytics experience?  What size deals?  To line of business, IT, or both?  For a CFO, do you require a accounting or finance background?  A veteran or an up-and-comer?  A CF-No or a CF-Go style?  You should know the answers to these questions; keep yourself honest by documenting them in a must-have / nice-to-have document.
  • Remember it’s a mutual sales process.  Unless you’re blessed to be at the hottest company in town, always remember that recruiting is a mutual sales process.  That means you need to be selling and filtering at the same time.  Particularly at the end of the process, interviewers should be told whether they should be primarily in “sell mode” or “filter mode.”  As it turns out, the person who said I was a “great interviewer” was a late-stage candidate who saw me in sell mode.  (And, yes, we succeeded with the hire!)  But who knows what they’d have thought of me in filter mode?
  • Follow some methodology or book.  I’m not particularly religious about which one, but I think a common framework helps to ensure completeness and improve communication during the recruiting process.   My private equity friends at ParkerGale, who do a great job of methodology selection, swear by Lou Alder so I’ll plug Hire With Your Head here.  ParkerGale has their own hiring playbook available as well.
  • Use work test samples.  While I’m not big into puzzles with prisoners and lightbulbs, I am a huge believer in having candidates do anything that approximates the work they’ll be doing if they take the job.  Have a product marketing manager give a presentation.  Ask a seller to role-play a sales call.  Have an engineer write pseudo-code to generate the Fibonacci sequence (to see if they understand recursion).  My all-time favorite was giving two FP&A directors the same three-tab spreadsheet with instructions “fix it,” “answer it,” and “model it” to test their attention to detail, problem solving, and modeling abilities.  The two were neck-and-neck on paper and in the interviews, but the exercise revealed a massive difference between them.  (We hired the one whose work stood out and were happy we did.)
  • Check references.  While I suppose the standard process of checking candidate-supplied references is still de rigeur, my favorite reference checks are backchannel and framed not in a binary hire-or-not light, but instead in the light of:  if I were to hire them, what strengths and weaknesses should I expect to see and how should I work with them to get the best results?  This framing tends to produce a better conversation.
  • Consider a try-and-buy.  One way to remove enormous risk from the recruiting process is a try-and-buy:  hire the person as a contractor or consultant, try working together for 3 to 6 months, and if both sides are happy at the end of that period, then convert the candidate to regular employment.  This works for some positions better than others — e.g., fractional CFOs and rent-a-CMOs already exist, whereas fractional CROs and CPOs (product) generally do not.  This works for some situations better than others:  it won’t work when recruiting a veteran CMO out of an existing job, but it can work nicely when considering a between-jobs, up-and-coming VP of Finance for their first CFO role.  Be open, be creative.  I’ve made some great hires this way — and avoided some train wrecks.

Thoughts on the Interview
When it comes specifically to interviewing, here’s what I’ve learned.

  • After chit-chat, ask for a N-minute life story with an emphasis on the why, not the what (i.e., why did you major in X, take first job Y, or move to job Z, as opposed to what you did in each).  For math types, I call this the first derivative of your resume.  I like to time-bound it, typically to 5 or 10 minutes, to see if the candidate has the ability to manage time and summarize accordingly.  I like the first derivative because it provides more information:  I already (largely) know what a PMM or VP of Finance does at a software company.  I’d much prefer to hear why someone chose to work (or stop work) at company X.  Moreover, if I want to understand accomplishments or duties, I can ask that separately, not as part of the life story.
  • After hearing “tough, but fair” for the 100th time, I decided to never ask for philosophies of any type, ever again.  Instead, think about situations that are encountered on the job and ask for relevant stories:  tell me about a time your fired someone, tell me about a time you launched a product, tell me about a time you ran the planning and budgeting process.  The experts call this behavioral interviewing, and it works.
  • Drill, baby, drill.   While I first learned this technique as a way to catch liars and exaggerators (who are frequently ensnared by the details), drill-down questions make fantastic follow-ups to behavioral “tell me about a time” questions.  Example:  tell me about a time you ran a budgeting process?  Drill-downs:  what year was it, in what month did you start, what was the rough total expense budget, how did you define the process, how many budget owners were there, how many iterations did you go through, how did you agree on the sales plan, did salesops have their own model, who made the churn plan, did they properly handle multi-year deals, who was the hardest exec to get on target, what were their objections, how did you handle them, when did the board finally approve it, how many iterations did that take, what were the initial objections, what would you do differently?  I’ve literally started down this path and had people say, “uh, I didn’t actually run the process in that job, but I was part of it” — an important distinction.  Whether to catch embellishment or to better understand candidates, drill-down questions work.  It’s more effective to go ten feet deep on one situation than one foot deep across ten.
  • Consider a panel interview.  I’ve become a huge fan of properly conducted panel interviews.  But first, what a panel interview is not:  it’s not randomly throwing 2-3 interviewers into a room with a candidate with no structure or preparation.  That’s called a romp, and it’s usually a negative experience for everyone.  What I’ve seen work is the following:  after a screening process that results in three candidates who meet all must-have criteria, you appoint a lead interviewer to create 5 behavioral questions (based on expected job duties in the first 12 to 18 months), share those questions with the candidate in advance, and then run a 90-minute live interview with a panel of 3-5 members who largely listen and ask follow-up questions only.  You create a scoring rubric, have all interviewers complete it, and then conduct a live discussion to compare the candidates.  This is FIRE.  In theory any of three candidates can do the job, so you’re focused on picking the best one for the company and situation.  The panelists listen intently because they’re not worried about running the interview, the remaining time, or their next question.  All candidates are asked the same questions.  And then you debrief via a live discussion which, as much as I love technology, is far higher bandwidth than any collaboration mechanism.  And you avoid groupthink because the rubric has been completed in advance.  Fire.  I thank ParkerGale for teaching this technique to me; they have a Private Equity Funcast episode on how they approach hiring here.

A CEO’s Guide to Marketing: My SaaStr 2021 Official Video

I’d previously posted a video of my SaaStr 2021 presentation, A CEO’s Guide to Marketing, but it was a bit of hack (a link into the stage stream) done favoring time-to-market over production values.  In this post, I’m embedding the official SaaStr 2021 video of that presentation, which has improved production values.

Here’s the video:

And here are the slides:

Why Execution Matters

Some friends wonder why, as someone who considers himself a strategist, I care so much about execution.  Is it because I’m a perfectionist?  Well yes, but that’s only one reason (and perfectionism is a weakness [1] in business, not a strength).  Is it because I like metrics, measurement, and incremental improvement?  Yes, I do.  Is it because I like improving efficiency and minimizing cash burn?  Yes, even though that doesn’t matter nearly as much as it once did.

But are any of those answers the real, big reason why I care so much about execution?  No.  This quadrant is:

In business, while we all may have strong opinions about what’s going to work and what isn’t, if we have even a trace of humility we must admit that we don’t know.  Therefore, everything we do is an experiment.  When an idea succeeds, great — let’s scale it up.  But it’s also quite important to know, when an idea fails, why.

That’s why execution matters.  Because when an idea doesn’t clearly succeed you need to be able to determine whether you’re in Box 1 or Box 4 of the above quadrant [2].

Saying a new corporate initiative failed because of bad execution is like saying a lab experiment failed because the petri dishes were dirty.  It shouldn’t even be a possible cause of failure.  You should have controlled for that.  You should have hired professionals to run your experiment.

If you’re going to spend $5M of your investors’ money to try an idea, if it doesn’t work you should be able to explain why — and be damn sure that execution is not a probable reason.  The whole Silicon Valley model is about isolating and removing risk from the equation.  That’s why boards want startups to pay high salaries and lure experienced talent with lucrative stock options.  It’s not because VCs like high compensation packages and dilution.  It’s because they want to optimize the chance of something working and, when it doesn’t, they want to be able to say, “we spent $5M and proved that was a bad idea,” as opposed to, “we spent $5M and we’re not sure whether it didn’t work because it was a bad idea or it was just poorly executed.” [3]

If Sartre said, “hell is other people,” I’d say, “hell is not knowing why you failed.”

Let’s take European expansion as an example.  You have a nice US-based $30M SaaS business and you want to expand into Europe.  But you’re not fully committed, the board is split on the decision, you’re worried about the CAC impact of initially unproductive sales investments, and you’re not sure what to do.

You think, if you had the proper budget, you’d:

  • Open in both the UK and Germany to run the experiment in parallel
  • Hire only sellers with experience in your space, with the same profile as the ones you hire in the US.
  • Hire 3 in each country to make sure the outcome isn’t dependent on any one bad hire.
  • Hire 2 SDRs and 2 solutions consultants in each country to support the sellers (the same ratio you use in the US).
  • Hire a few other staff like in functions like customer success, support, and services to support the team.
  • Hire a VP of Europe to lead this — someone experienced but who still enjoyed being close to the action; they’d be expensive but they could scale the operation as it grew.
  • All in all, you’d hire maybe 20 people and spend $4M to get going.

But given the board situation, you decide to do it on the cheap:

  • You hire one seller in UK and one in Germany, who are both junior in their careers and have never worked in the space, but they’re cheap and seem aggressive.  Good sales DNA you convince yourself.
  • You tell them to work primarily through partners because you don’t think you can afford to go direct.
  • You have them share a UK-based solutions consultant who doesn’t speak German.
  • And that’s it.  You spend less than $1M, but at least you’re getting started.

Now, zoom forward to the end of the year.  It didn’t work.  The two sellers both quit and the solutions consultant is trying to support the few customers they sold.  It’s a mess.  And what have you learned?  That Europeans don’t want software in your category?  That a partner model doesn’t work in Europe?  That it’s hard to find good talent in Europe?

Nope.  You haven’t learned anything — except that bad execution leads to failure.  And you knew that already, didn’t you?

Maybe you think you learned not to hire junior sales reps, that reps need a proper level of supporting staff, and that customers like to get demos in their native language?  But you knew that already, too.  You haven’t learned a thing, but you’ve wasted $1M, damaged your brand, and most importantly, lost a year.

By the way, if you really wanted to know if you could hire junior sellers and make them successful — if that was really the question you were trying to answer — then shouldn’t you have held all the other variables constant and just tested that?  In the US, at perhaps smaller companies but in your same target market.  With your standard support ratios.  With experienced leadership.

Imagine if you ran the other play, the one with the proper budget.  If it worked, you’d be worried about scaling up, not still worried about how to open Europe.  If it didn’t work, then you’d have some really hard questions to answer.  Because we can be pretty sure it’s not the people or the support ratios or the sales model — or execution in general.  We’re probably in Box 1 — there’s likely something about the idea that’s wrong.  Maybe, to pick a trivial example, Europeans don’t want to buy your compliance software because it’s weak on supporting European regulations [4].

The Idea/Execution Quadrant
It’s no secret that I like quadrants.  I made this one because I wanted to separate business outcomes from idea quality and execution quality.  Box 2 and Box 3 were easy to label.  I frankly struggled with the labels of Box 1 and Box 4.  So let’s talk about them in more depth as I’ve lived in both [5].

Box 1:  Bad Idea, Good Execution.  For me, this was MarkLogic, an XML database system [6].  During my six years there we grew the company from $0 to $80M in revenues, so I have trouble labeling that box — as I initially did — “failure” [7].  While I also considered labeling it “partial failure,” in the end I chose “partial success.”  We brought great execution to a hostile environment [8] and had enough success to confuse people — by the numbers we resembled many destined-for-greatness companies, but those who looked beyond the numbers knew we were not [9].  As one very smart VC summarized it, “you’re still pushing” — a great definition, in fact, of partial success.  You’re driving growth and making numbers, but you have no tailwind from the market.  When you’re in Box 2, you’re HODL-ing to stay on top of the market — in Box 1, by comparison, you are fighting for every yard.  That’s why I labeled it “partial success.”

Because if you bring good execution to a bad idea [10], smart people can often figure it out, and you can drive some success.  But it won’t be easy and it won’t scale [11].

Box 4:  Good Idea, Bad Execution.  For me, this was Ingres, my first job out of college.  If I told you I joined a startup after school, stayed there 7 years, and it grew from $30M into a $240M division of a $400M company, you might be tempted to say “success.”  But you’d be wrong.  One clue is obvious:  division.  We grew, but not so much that we were able to stay an independent company.  The other is non-obvious.  During those same 7 years our archrival (a company called Relational Software) grew from $30M to $1B.  During that period Relational Software changed its name to match that of its product:  Oracle.

The idea was clearly good.  In terms of wealth generation, the RDBMS was the second best idea of the 20th century [12].  Did Ingres succeed?  While my quip is that I experienced great success and great failure simultaneously [13], there is no question.  No.  Ingres failed.  It got third place in the race of the century.   Second place (Sybase) was a set of steak knives.  Third place was for our acquiror, ASK, to get acquired by CA for less than 1x revenues.  Was our execution bad?  I think so, not only because of hindsight bias based on the result, but because I worked there.  While I go into considerable depth in this post, I think the simple answer is that Ingres never really understood either the stakes of the game it was playing or the power of increasing returns in software market leadership.

You could argue I should label Box 4 “failure,” but we did manage to grow the company, go public, and achieve other key milestones — so, optimists could argue that we were succeeding.  Semantically, would I argue the partial success is not success and thus failure?  Maybe.  Practically, do I want to label Box 4 “failure” and potential enable misguided optimists to argue that some success equals success and that they’re ergo in Box 2?  No.

That’s why Boxes 1 and 4 are so difficult.  You’re not sure if you’re succeeding or failing and you’re not sure why.  Which, in the end, is why execution matters.  So you succeed when your idea is good and so you can rule out execution as a factor when it’s not.

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Notes

[1]  As it took me way too long to realize, you need to focus on getting what matters right.  It’s one of several points discussed in this deck.

[2]  See the second part of the post for more discussion of the quadrant itself.

[3]  And now they need to decide if we want to spend another $5M to try it again, but this time with professionals.

[4]  And a professional team would likely figure that out and tell you.  The amateurs might offer 100 different excuses and/or forms of hope.

[5]  Happily, I’ve also done plenty of time in Box 2!

[6]  I am not speaking of MarkLogic in its contemporary form (about which I know fairly little), but as it was in the 2004-2010 period when I ran it.  Disclaimer:  I own some residual shares in MarkLogic.

[7]  Though a VC might easily do so.  The investor view on these things is pretty simple:  did I make a lot of money?  The operator view is different.  We grew a business, in an environment as hostile as a sea-floor vent, to $80M and solved plenty of hard problems for plenty of happy customers in the process.

[8]  Something like 15 of the 16 original XML database companies basically went out of business.  I’d call that hostile.

[9]  Specifically that NoSQL was emerging and that those systems (e.g., Hadoop, MongoDB) and their associated open source models, were going to become the mainstream way to solve the problems that our technology solved.

[10]  This begs the question of how to define the idea.  In MarkLogic’s case, what was the idea?  Building a search engine with database parts and using a distributed scale-out architecture were good ideas — very good, in fact.  But the overall business idea was that XQuery would do for MarkLogic what SQL did for Oracle.  That, because XQuery never took off (and was arguably a case of infantcide by the megavendors) was a bad idea, and the one that put us in Box 1.

[11]  Critical thinkers may be wondering if I’ve rationalized the company into Box 1 because (as a non-founder CEO) I was responsible for the execution and not the idea.  Let’s test that.  The team who took over the company was definitionally “better” in the minds of our top-tier VCs who brought them in and who are presumably skilled at evaluating such things.  Ergo, if you were in Box 4 and upgraded the team (and ergo execution), you should move to Box 2 and see improved results.  That didn’t happen.  Similarly, if you look at the idea compared to other companies pursuing the same idea (see endnote [8]) you can’t find any evidence that it was a good idea.  Had 1-2 competitors done materially better than we did in size, growth, or exit value that would suggest the idea was good and our execution bad, but that didn’t happen either.  Hence my belief that we were in Box 1.

[12]  First place was PC operating systems with Microsoft.

[13]  Because we did face the challenges of high growth.