Category Archives: Management

Kellblog 2021 Predictions

I admit that I’ve been more than a little slow to put out this post, but at least I’ve missed the late December (and early January) predictions rush.  2020 was the kind of year that would make anyone in the predictions business more than a little gun shy.  I certainly didn’t have “global pandemic” on my 2020 bingo card and, even if I somehow did, I would never have coupled that with “booming stock market” and median SaaS price/revenue multiples in the 15x range.

That said, I’m back on the proverbial horse, so let’s dig in with a review of our 2020 predictions.  Remember my disclaimers, terms of use, and that this exercise is done in the spirit of fun and as a way to tee-up discussion of interesting trends, and nothing more.

2020 Predictions Review

Here a review of my 2020 predictions along with a self-graded and for this year, pretty charitable, hit/miss score.

  1. Ongoing social unrest. No explanation necessary.  HIT.
  2. A desire for re-unification. We’ll score that one a whopping, if optimistic, MISS.  Hopefully it becomes real in 2021.
  3. Climate change becomes new moonshot. Swing and a MISS.  I still believe that we will collectively rally behind slowing climate change but feel like I was early on this prediction, particularly because we got distracted with, shall we say, more urgent priorities.  (Chamath, a little help here please.)
  4. The strategic chief data officer (CDO). CDO’s are indeed becoming more strategic and they are increasingly worried about playing not only defense but also offense with data, so much so that the title is increasingly morphing into chief data & analytics officer (CDAO).  HIT.
  5. The ongoing rise of devops. In an era where we (vendors) increasingly run our own software, running it is increasingly as important as building it.  Sometimes, moreHIT.
  6. Database proliferation slows. While the text of this prediction talks about consolidation in the DBMS market, happily the prediction itself speaks of proliferation slowing and that inconsistency gives me enough wiggle room to declare HITDB-Engines ranking shows approximately the same number of DBMSs today (335) as one year ago (334).  While proliferation seems to be slowing, the list is most definitely not shrinking.
  7. A new, data-layer approach to data loss prevention. This prediction was inspired by meeting Cyral founder Manav Mital (I think first in 2018) after having a shared experience at Aster Data.  I loved Manav’s vision for securing the set of cloud-based data services that we can collectively call the “data cloud.”  In 2020, Cyral raised an $11M series A, led by Redpoint and I announced that I was advising them in March.  It’s going well.  HIT.
  8. AI/ML success in focused applications. The keyword here was focus.  There’s sometimes a tendency in tech to confuse technologies with categories.  To me, AI/ML is very much the former; powerful stuff to build into now-smart applications that were formerly only automation.  While data scientists may want an AI/ML workbench, there is no one enterprise AI/ML application – more a series of applications focused on specific problems, whether that be C3.AI in a public market context or Symphony.AI in private equity one.  HIT.
  9. Series A remains hard. Well, “hard” is an interesting term.  The point of the prediction was the Series A is the new chokepoint – i.e., founders can be misled by easily raising $1-2M in seed, or nowadays even pre-seed money, and then be in for a shock when it comes time to raise an A.  My general almost-oxymoronic sense is that money is available in ever-growing, bigger-than-ever bundles, but such bundles are harder to come by.  There’s some “it factor” whereby if you have “it” then you can (and should) raise tons of money at great valuations, whereas, despite the flood of money out there, if you don’t have “it,” then tapping into that flood can be hard to impossible.  Numbers wise, the average Series A was up 16% in size over 2019 at around $15M, but early-stage venture investment was down 11% over 2019.  Since I’m being charitable today, HIT.
  10. Autonomy CEO extradited. I mentioned this because proposed extraditions of tech billionaires are, well, rare and because I’ve kept an eye on Autonomy and Mike Lynch, ever since I competed with them back in the day at MarkLogic.  Turns out Lynch did not get extradited in 2020, so MISS, but the good news (from a predictions viewpoint) is that his extradition hearing is currently slated for next month so it’s at least possible that it happens in 2021.  Here’s Lynch’s website (now seemingly somewhat out of date) to hear his side of this story.

So, with that charitable scoring, I’m 7 and 3 on the year.  We do this for fun anyway, not the score.

 Kellblog’s Ten Prediction for 2021

1. US divisiveness decreases but unity remains elusive. Leadership matters. With a President now focused on unifying America, divisiveness will decrease.  Unity will be difficult as some will argue that “moving on” will best promote healing while others argue that healing is not possible without first holding those to account accountable.  If nothing else, the past four years have provided a clear demonstration of the power of propaganda, the perils of journalistic bothsidesism, and the power of “big tech” platforms that, if unchecked, can effectively be used for long-tail aggregation towards propagandist and conspiratorial ends.

The big tech argument leads to one of two paths: (1) they are private companies that can do what they want with their terms of service and face market consequences for such, or (2) they are monopolies (and/or, more tenuously, the Internet is a public resource) that must be regulated along the lines of the FCC Fairness Doctrine of 1949, but with a modern twist that speaks not only to the content itself but to the algorithms for amplifying and propagating it.

2. COVID-19 goes to brushfire mode. After raging like a uncontained wildfire in 2020, COVID should move to brushfire mode in 2021, slowing down in the spring and perhaps reaching pre-COVID “normal” in the fall, according to these predictions in UCSF Magazine. New variants are a wildcard and scientists are still trying to determine the extent to which existing vaccines slow or stop the B117 and 501.V2 variants.

According to this McKinsey report, the “transition towards normalcy is likely during the second quarter in the US,” though, depending on a number of factors, it’s possible that, “there may be a smaller fall wave of disease in third to fourth quarter 2021.”  In my estimation, the wildfire gets contained in 2Q21, with brush fires popping up with decreasing frequency throughout the year.

(Bear in mind, I went to the same school of armchair epidemiology as Dougall Merton, famous for his quote about spelling epidemiologist:  “there are three i’s in there and I swear they’re moving all the time.”)

3. The new normal isn’t. Do you think we’ll ever go into the office sick again? Heck, do you think we’ll ever go into the office again, period?  Will there even be an office?  (Did they renew that lease?)  Will shaking hands be an ongoing ritual? Or, in France, la bise?  How about those redeyes to close that big deal?  Will there still be 12-legged sales calls?  Live conferences?  Company kickoffs?  Live three-day quarterly business reviews (QBRs)?  Business dinners?  And, by the way, do you think everyone – finally – understands the importance of digital transformation?

I won’t do detailed predictions on each of these questions, and I have as much Zoom fatigue as the next person, but I think it’s important to realize the question is not “when we are we going back to the pre-COVID way of doing things?” and instead “what is the new way of doing things that we should move towards?”   COVID has challenged our assumptions and taught us a lot about how we do business. Those lessons will not be forgotten simply because they can be.

4.We start to value resilience, not just efficiency. For the past several decades we have worshipped efficiency in operations: just-in-time manufacturing, inventory reduction, real-time value chains, and heavy automation.  That efficiency often came at a cost in terms of resilience and flexibility and as this Bain report discusses, nowhere was that felt more than in supply chain.  From hand sanitizer to furniture to freezers to barbells – let alone toilet paper and N95 masks — we saw a huge number of businesses that couldn’t deal with demand spikes, forcing stock-outs for consumers, gray markets on eBay, and countless opportunities lost.  It’s as if we forget the lessons of the beer game developed by MIT.  The lesson:  efficiency can have a cost in terms of resilience and agility and I believe,  in an increasingly uncertain world, that businesses will seek both.

5. Work from home (WFH) sticks. Of the many changes COVID drove in the workplace, distributed organizations and WFH are the biggest. I was used to remote work for individual creative positions such as writer or software developer.  And tools from Slack to Zoom were already helping us with collaboration.  But some things were previously unimaginable to me, e.g., hiring someone who you’d never met in the flesh, running a purely digital user conference, or doing a QBR which I’d been trained (by the school of hard knocks) was a big, long, three-day meeting with a grueling agenda, with drinks and dinners thereafter.  I’d note that we were collectively smart enough to avoid paving cow paths, instead reinventing such meetings with the same goals, but radically different agendas that reflected the new constraints.  And we – or at least I in this case – learned that such reinvention was not only possible but, in many ways, produced a better, tighter meeting.

Such reinvention will be good for business in what’s now called The Future of Work software category such as my friends at boutique Future-of-Work-focused VCs like Acadian Ventures — who have even created a Bessemer-like Future of Work Global Index to track the performance of public companies in this space.

6. Tech flight happens, but with a positive effect. Much has been written about the flight from Silicon Valley because of the cost of living, California’s business-unfriendly policies, the mismanagement of San Francisco, and COVID. Many people now realize that if they can work from home, then why not do so from Park City, Atlanta, Raleigh, Madison, or Bend?  Better yet, why not work from home in a place with no state income taxes at all — like Las Vegas, Austin, or Miami?

Remember, at the end of the OB (original bubble), B2C meant “back to Cleveland” – though, at the time, the implication was that your job didn’t go with you.  This time it does.

The good news for those who leave:

  • Home affordability, for those who want the classic American dream (which now has a median price of $2.5M in Palo Alto).
  • Lower cost of living. I’ve had dinners in Myrtle Beach that cost less than breakfasts at the Rosewood.
  • Burgeoning tech scenes, so you don’t have go cold turkey from full immersion in the Bay Area. You can “step down,” into a burgeoning scene in a place like Miami, where Founder’s Fund partner Keith Rabois, joined by mayor Francis Suarez, is leading a crusade to turn Miami into the next hot tech hub.

But there also good news for those who stay:  house prices should flatten, commutes should improve, things will get a little bit less crazy — and you’ll get to keep the diversity of great employment options that leavers may find lacking.

Having grown up in the New York City suburbs, been educated on Michael Porter, and worked both inside and outside of the industry hub in Silicon Valley, I feel like the answer here is kind of obvious:  yes, there will be flight from the high cost hub, but the brain of system will remain in the hub.  So it went with New York and financial services, it will go with Silicon Valley and tech.  Yes, it will disperse.  Yes, certainly, lower cost and/or more staffy functions will be moved out (to the benefit of both employers and employees).  Yes, secondary hubs will emerge, particularly around great universities.  But most of the VCs, the capital, the entrepreneurs, the executive staff, will still orbit around Silicon Valley for a long time.

7. Tech bubble relents. As an investor, I try to never bet against bubbles via shorts or puts because “being right long term” is too often a synonym for “being dead short term.” Seeing manias isn’t hard, but timing them is nearly impossible.  Sometimes change is structural – e.g., you can easily convince me that if perpetual-license-based software companies were worth 3-5x revenues that SaaS companies, due to their recurring nature, should be worth twice that.  The nature of the business changed, so why shouldn’t the multiple change with it?

Sometimes, it’s actually true that This Time is Different.   However, a lot of the time it’s not.  In this market, I smell tulips.  But I started smelling them over six months ago, and BVP Emerging Cloud Index is up over 30% in the meantime.  See my prior point about the difficultly of timing.

But I also believe in reversion to the mean.  See this chart by Jamin Ball, author of Clouded Judgement, that shows the median SaaS enterprise value (EV) to revenue ratio for the past six years.  The median has more than tripled, from around 5x to around 18x.  (And when I grew up 18x looked more like a price/earnings ratio than a price/revenue ratio.)

What accounts for this multiple expansion?  In my opinion, these are several of the factors:

  • Some is structural: recurring businesses are worth more than non-recurring businesses so that should expand software multiples, as discussed above.
  • Some is the quality of companies: in the past few years some truly exceptional businesses have gone public (e.g., Zoom).  If you argue that those high-quality businesses deserve higher multiples, having more of them in the basket will pull up the median.  (And the IPO bar is as high as it’s ever been.)
  • Some is future expectations, and the argument that the market for these companies is far bigger than we used to think. SaaS and product-led growth (PLG) are not only better operating models, but they actually increase TAM in the category.
  • Some is a hot market: multiples expand in frothy markets and/or bubbles.

My issue:  if you assume structure, quality, and expectations should rationally cause SaaS multiples to double (to 10), we are still trading at 80% above that level.  Ergo, there is 44% downside to an adjusted median-reversion of 10.  Who knows what’s going to happen and with what timing but, to quote Newton, what goes up (usually) must come down.  I’m not being bear-ish; just mean reversion-ish.

(Remember, this is spitballing.  I am not a financial advisor and don’t give financial advice.  See disclaimers and terms of use.)

8. Net dollar retention (NDR) becomes the top SaaS metric, driving companies towards consumption-based pricing and expansion-oriented contracts. While “it’s the annuity, stupid” has always been the core valuation driver for SaaS businesses, in recent years we’ve realized that there’s only one thing better than a stream of equal payments – a stream of increasing payments.  Hence NDR has been replacing churn and CAC as the headline SaaS metric on the logic of, “who cares how much it cost (CAC) and who cares how much leaks out (churn) if the overall bucket level is increasing 20% anyway?”  While that’s not bad shorthand for an investor, good operators should still watch CAC and gross churn carefully to understand the dynamics of the underlying business.

This is driving two changes in SaaS business, the first more obvious than the second:

  • Consumption-based pricing. As was passed down to me by the software elders, “always hook pricing to something that goes up.”  In the days of Moore’s Law, that was MIPS.  In the early days of SaaS, that was users (e.g., at Salesforce, number of salespeople).  Today, that’s consumption pricing a la Twilio or Snowflake.   The only catch in a pure consumption-based model is that consumption better go up, but smart salespeople can build in floors to protect against usage downturns.
  • Built-in expansion. SaaS companies who have historically executed with annual, fixed-fee contracts are increasingly building expansion into the initial contract.  After all, if NDR is becoming a headline metric and what gets measured gets managed, then it shouldn’t be surprising that companies are increasingly signing multi-year contracts of size 100 in year 1, 120 in year 2, and 140 in year 3.  (They need to be careful that usage rights are expanding accordingly, otherwise the auditors will flatten it back out to 120/year.)  Measuring this is a new challenge.  While it should get captured in remaining performance obligation (RPO), so do a lot of other things, so I’d personally break it out.  One company I work with calls it “pre-sold expansion,” which is tracked in aggregate and broken out as a line item in the annual budget.

See my SaaStr 2020 talk, Churn is Dead, Long Live Net Dollar Retention, for more information on NDR and a primer on other SaaS metrics.  Video here.

9. Data intelligence happens. I spent a lot of time with Alation in 2020, interim gigging as CMO for a few quarters. During that time, I not only had a lot of fun and worked with great customers and teammates, I also learned a lot about the evolving market space.

I’d been historically wary of all things metadata; my joke back in the day was that “meta-data presented the opportunity to make meta-money.”  In the old days just getting the data was the problem — you didn’t have 10 sources to choose from, who cared where it came from or what happened to it along the way, and what rules (and there weren’t many back then) applied to it.  Those days are no more.

I also confess I’ve always found the space confusing.  Think:

Wait, does “MDM” stand for master data management or metadata management, and how does that relate to data lineage and data integration?  Is master data management domain-specific or infrastructure, is it real-time or post hoc?  What is data privacy again?  Data quality?  Data profiling?  Data stewardship?  Data preparation, and didn’t ETL already do that?  And when did ETL become ELT?  What’s data ops?  And if that’s not all confusing enough, why do I hear like 5 different definitions of data governance and how does that relate to compliance and privacy?”

To quote Edward R. Murrow, “anyone who isn’t confused really doesn’t understand the situation.”

After angel investing in data catalog pioneer Alation in 2013, joining their board in 2016, and joining the board of master data management leader Profisee in 2019, I was determined to finally understand the space.  In so doing, I’ve come to the conclusion that the vision of what IDC calls data intelligence is going happen.

Conceptually, you can think of DI as the necessary underpinning for both business intelligence (BI) and artificial intelligence (AI).  In fact, AI increases the need for DI.  Why?  Because BI is human-operated.  An analyst using a reporting or visualization tool who sees bad or anomalous data is likely going to notice.  An algorithm won’t.  As we used to say with BI, “garbage in, garbage out.”  That’s true with AI as well, even more so.  Worse yet, AI also suffers from “bias in, bias out” but that’s a different conversation.

I think data intelligence will increasingly coalesce around platforms to bring some needed order to the space.  I think data catalogs, while originally designed for search and discovery, serve as excellent user-first platforms for bringing together a wide variety of data intelligence use cases including data search and discovery, data literacy, and data governance.  I look forward to watching Alation pursue, with a hat tip to Marshall McLuhan, their strategy of “the catalog is the platform.”

Independent of that transformation, I look forward to seeing Profisee continue to drive their multi-domain master data management strategy that ultimately results in cleaner upstream data in the first place for both operational and analytical systems.

It should be a great year for data.

10. Rebirth of Planning and Enterprise Performance Management (EPM). EPM 1.0 was Hyperion, Arbor, and TM1. EPM 2.0 was Adaptive Insights, Anaplan, and Planful (nee Host Analytics).  EPM 3.0 is being born today.  If you’ve not been tracking this, here a list of next-generation planning startups that I know (and for transparency my relationship with them, if any.)

Planning is literally being reborn before our eyes, in most cases using modern infrastructure, product-led growth strategies, stronger end-user focus and design-orientation, and often with a functional, vertical, or departmental twist.  2021 will be a great year for this space as these companies grow and put down roots.  (Also, see the follow-up post I did on this prediction.)

Well, that’s it for this year’s list.  Thanks for reading this far and have a healthy, safe, and Rule-of-40-compliant 2021.

An Epitaph for Intrapreneurship

About twenty years ago, before I ran two startups as CEO and served as product-line general manager, I went through an intrapreneurship phase, where I was convinced that big companies should try to act like startups.  It was a fairly popular concept at the time.

Heck, we even decided to try the idea at Business Objects, launching a new analytical applications division called Ithena, with a mission to build CRM analytical applications on top of our platform.  We made a lot of mistakes with Ithena, which was the beginning of the end of my infatuation with the concept:

  • We staffed it with the wrong people.  Instead of hiring experts in CRM, we staffed it largely with experts in BI platforms.  Applications businesses are first and foremost about domain expertise.
  • They built the wrong thing.  Lacking CRM knowledge, they invested in building platform extensions that would be useful if one day you wanted to build a CRM analytical app.  From a procrastination viewpoint, it felt like a middle school dance.  Later, in Ithena’s wreckage, I found one of the prouder moments of my marketing career  — when I simply repositioned the product to what it was (versus what we wanted it to be), sales took off.
  • We blew the model.  They were both too close and too far.  They were in the same building, staffed largely with former parent-company employees, and they kept stock options in both the parent the spin-out.  It didn’t end up a new, different company.  It ended up a cool kids area within the existing one.
  • We created channel conflict with ourselves.  Exacerbated by the the thinness of the app, customers had trouble telling the app from the platform.  We’d have platform salesreps saying “just build the app yourself” and apps salesreps saying that you couldn’t.
  • They didn’t act like entrepreneurs.  They ran the place like big-company, process-oriented people, not scrappy entrepreneurs fighting for food to get through the week.  Favorite example:  they had hired a full-time director of salesops before they had any customers.  Great from an MBO achievement perspective (“check”).  But a full-time employee without any orders to book or sales to analyze?  Say what you will, but that would never happen at a startup.

As somebody who started out pretty enthralled with intrapreneurship, I ended up pretty jaded on it.

I was talking to a vendor about these topics the other day, and all these memories came back.  So I did quick bit of Googling to find out what happened to that intrapreneurship wave.  The answer is not much.

Entrepreneurship crushes intrapreneurship in Google Trends.  Just for fun, I added SPACs to see their relatively popularity.

Here’s my brief epitaph for intrapreneurship.  It didn’t work because:

  • Intrapreneurs are basically entrepreneurs without commitment.  And commitment, that burn the ships attitude, is key part of willing a startup into success.
  • The entry barriers to entrepreneurship, particularly in technology, are low.  It’s not that hard (provided you can dodge Silicon Valley’s sexism, ageism, and other undesirable -isms) for someone in love with an idea to quit their job, raise capital, and start a company.
  • The intrapreneurial venture is unable to prioritize its needs over those of the parent.  “As long as you’re living in my house, you’ll do things my way,” might work for parenting (and it doesn’t) but it definitely does not work for startup businesses.
  • With entrepreneurship one “yes” enables an idea, with intrapreneurship, one “no” can kill it.  What’s more, the sheer inertia in moving a decision through the hierarchy could kill an idea or cause a missed opportunity.
  • In terms of the ability to attract talent and raise capital, entrepreneurship beats intrapreneurship hands down.  Particularly today, where the IPO class of 2020 raised a mean of $350M prior to going public.

As one friend put it, it’s easy with intrapreneurship to end up with all the downsides of both models.  Better to be “all in” and redefine the new initiative into your corporate self image, or “all out” and spin it out as an independent entity.

I’m all for general mangers (GMs) acting as mini-CEOs, running products as a portfolio of businesses.  But that job, and it’s a hard one, is simply not the same as what entrepreneurs do in creating new ventures.  It’s not even close.

The intrapreneur is dead, long live the GM.

Unlearning as you Scale: Recording of my Costanoa Ventures 2020 Summit Presentation

Last month I presented Unlearning As You Scale at Costanoa Ventures 2020 Costanoa CEO UnSummit.  In response to several requests for a live recording of the presentation, I sat down this weekend and recorded the following.

Key topics discussed:

  • How to properly apply the popular Silicon Valley adage, “the folks who got you here aren’t the ones to take you to the next level.”
  • How to generalize that adage to not only people, but systems, processes, and strategies.
  • If and when required, how to hire next-level executives while avoiding common pitfalls.
  • How to critically think about success with your team.

 

An audio-only version of the presentation is here:

 

My original post on the event is here.

Unlearning As You Scale: Presentation from a VC Portfolio CEO Summit

The good people of Costanoa Ventures invited me to speak at their summit where they gather portfolio company CEOs to participate in an impressive set of sessions related to building and scaling startups.  I was honored to be in the company of friends and respected colleagues like Nick Mehta and Rob Reid as presenters at the conference.

Costanoa asked me to speak about un-learning at this year’s un-summit and, as a (sometimes, some might say frequent) contrarian, I was only too happy to do so.  The slides from the presentation are below.  I focused on 4 topics:

  • The sensible application of the popular Silicon Valley adage, “the folks who got you here aren’t the ones who will get you to the next level,” and how to reconcile it with an older, even more popular adage:  “dance with who brung ya.”
  • Generalizing the next-level adage beyond people to systems, processes, and operational strategies.
  • Things to do and pitfalls to avoid in recruiting next-level executives, with a particular focus on avoiding very successful people caught in the lather/rinse/repeat trap.
  • Critically thinking whether you have been successful because of, in spite of, or independent of a list of your company’s practices, values, and deeply held beliefs

This slides are here and embedded below.

Thanks to Greg Sands, Martina Lauchengco, and Rachel Quon for inviting me and giving me such a great topic to work with.

What Exactly Do You Mean by Anal? Thoughts on Leadership and Self-Awareness

I remember one time having an argument that went like this:

Dave:  I don’t think you’ve thought through the details on this one.

Joe:  I think there’s enough detail in there.

Dave:  No, there’s not.  There’s no underpinnings, there’s no rigor in the thought process.  Remember, David Ogilvy always said “good writing is slavery” and ergo you need to dive deep and —

Joe:  Oh, you can be so anal.

Dave:  I don’t think I’m being anal.  I’m just being rigorous.

Joe:  Yes, you are.

Dave:  Well, what exactly do you mean by anal?

I always try to listen to myself and once in a while I have a did-I-just-say-that moment.  Did I just say, “what exactly do you mean by anal?”  Oh shit, I did.  Isn’t that kind of the definition of being anal?  Oh shit, it is.  Heck Dave, you may as well just have replied:  what I really want to know is — is there a hyphen in anal-retentive?

The actual issue here is one of leadership:  being aware of your strengths and weaknesses, trying to avoid over-doing your strengths and working to compensate for your weaknesses.  It’s critical that all leaders focus on this because, by default, most folks will over-play to their strengths (to a fault, effectively turning them into weaknesses) and ignore their weaknesses.

It’s not hard to be self-aware when it comes to most strengths and weaknesses.  Most folks know, for example, if they’re great at public speaking and bad at financial analysis, or great at individual problem-solving but bad in groups.  Or high on IQ but low on EQ.  People usually know.

Sometimes we euphemize with ourselves.  For example, while others might say I’m:

  • Detail-oriented, I prefer “rigorous”
  • Blunt, I prefer “direct”
  • Contrarian, I prefer “critical-thinking”
  • And so on

But at least you’re circling the same pond.  You have awareness of the area –though you might soften how you think about it to protect the old ego, relative to how others might more bluntly, or should I say directly, describe it.

But some weaknesses are harder to self-assess.  For example, I’ve taken assessments that basically prove I’m low on flexibility.  But I never knew it.  In fact, I thought I was supremely flexible because I was capable of moving.  Think:  OK, we’ll move a bit in your direction.  You see, I’m flexible!  Voila, QED.  Bravo Chef!  I was, however, blind to the fact that one person’s mile is another’s inch.  When you’re inflexible you risk self-congratulation for a tidbit of demonstrated movement when the other party thinks you haven’t moved at all.

As another example, because communication is one of my strengths, I always thought I did better in groups, when in fact I do better with people one-to-one — which was a key strength of which I wasn’t even aware.  Some of these things are just hard to see.

My advice on this front is three-fold:

  • Be aware of your strengths and beware your natural tendency to overplay to them.  If one of your strengths has become a running joke (e.g., at one point one of my staff handed out “Captain Anal” pins), it could be time to think about it.
  • Be aware of your weaknesses and, while you can work on them if you want, use building a complementary team as your primary way to compensate.
  • Attend programs like LDP (managers, directors) or LAP (C-levels) to build a deep understanding of both.  These programs aren’t cheap, but they will give you self-awareness, in a kind of data-driven and ergo virtually undeniable way, that few other programs will.

(And can somebody please spell-check this thing to make sure there aren’t any errors.)

Foreword to The Next CMO: A Guide to Marketing Operational Excellence

The folks at Plannuh, specifically Peter Mahoney, Scott Todaro, and Dan Faulkner, asked me to write the foreword for their new book, The Next CMO:  A Guide to Marketing Operational Excellence.  (Free download here.)

Here’s what I wrote for them.

CMO is a hard job. Early in my career I worked for CMOs, in sort of an endless revolving-door progression, at one point having 7 bosses in 5 years. I have been a CMO, for over 12 years at three different companies. I have managed CMOs, working as CEO for over a decade at two different companies. And I have guided CMOs, serving as an independent director on the board of five different companies.  Let’s just say I’ve spent a lot of time in and around the CMO role.

In the past two decades, no executive suite role has changed more and more quickly than the CMO. Marketers of yesteryear could focus on strategic positioning and branding, leaving such banalities as lead generation to sales-aligned field marketing teams, managing scraps of paper in cardboard boxes.

Sales and marketing automation systems changed everything. Concepts like pipeline, conversion rates, and velocity were born. From lead generation sprung lead nurturing. Attribution emerged to solve one of the world’s oldest marketing problems.

Artificial intelligence (AI) arrived at the scene, helping with areas like lead scoring and prioritization. The demand for analytics followed suit. Marketing ops arose as the cousin of sales ops.

Digital marketing changed everything again. Spend became even more accountable. Pay-per-click replaced pay-per-view which replaced just-pay. Targeting became more precise both via search and the rise of social media. Content marketing emerged to supplement declining traditional public relations. If yesterday’s marketing was leaflets dropped from airplanes, today’s is A/B-tested, laser-guided, call-to-action missiles.

Technology came at CMOs faster than they could keep up. Software could power your website, run your resource center, generate your landing pages, test your messaging, drive repeatable SDR processes, identify your ideal customer, drive account-based marketing, and even record and analyze prospect conversations.

What’s more, as CEOs and boards knew that entirely new classes of questions were becoming answerable, they started asking them.

  • What percent of the pipeline are prospects within our ideal customer profile?
  • What’s the stage-weighted expected value of the pipeline?
    Forecast-category weighted?
  • What’s our week 3 pipeline conversion rate for new logo vs upsell opportunities?
  • What’s our cost per opportunity and how does it vary by channel and geography?
  • What’s marketing’s contribution to our customer acquisition cost (CAC) ratio and how are we improving it?

And dozens and dozens more.

The hardest job in the C-suite got harder. Today’s CMOs need to be visionary strategists by day and operational tacticians by night. Operational marketing has become the sine qua non of modern marketing. If the website is optimized, if the demand generation machine is running effectively, if marketing events are executed flawlessly, if quality pipeline is being generated efficiently, if that pipeline is converting in line with industry benchmarks, and if and only if all that is being done within the constraints of the marketing budget — spending neither too little nor too much — then and only then does the CMO get the chance to be “strategic.”

Operational excellence is thus a necessary but not sufficient condition for CMO success. So it’s well worth mastering and this book is the ideal guide to building and managing your own integrated marketing machine.

There’s no one better to write this book than the leadership team at Plannuh, Peter, Scott, and Dan. With their experience running marketing teams from startups through multi-billion dollar public companies, teaching and mentoring generations of marketers, and now building a platform that codifies their thinking into a scalable SaaS platform, this guide is certain to raise the IQ of your marketing function.

– Dave Kellogg

On the Perils of Taking Advice from Successful Business People

One of the hardest things about running a startup is you’re never sure who to listen to.

Your board members own big stakes in the company, but that doesn’t automatically align them with you.  Your late-stage investors want low multiples on big numbers.  Your early-stage investors want big multiples on small numbers.  And they have their own specific needs driven by their funds and their partnerships.  Your rank-and-file employees own relatively small stakes which, ceteris paribus, should make them want you to swing for the fences — but, in these days of decade-to-liquidity, you may have employees so jaded on equity compensation that they’d just like to keep their well-paying jobs.

Your executive team wants to hit their targets, earn their bonuses, and maybe some of them are deeply motivated by winning in the market, but maybe not.  With a 0.5% to 1% share, a $500M exit can mean a $2.5M to $5.0M pop.  Maybe some would prefer to take the early exit, upgrade the house in Menlo Park, and go do it again somewhere else, as opposed to riding it out for the long term.

The idea that giving everyone some equity is a good one, but as I wrote nearly ten years ago, it’s quaint to think that doing so aligns everyone.

So, if you can’t really look inside the company, what then?  Well, if you’re like many, you look outside.  You might read books, subscribe to blogs, or listen to podcasts.  You might seek out advisors or create an advisory board.

In all such cases, you’ll be taking advice from business people who have gone before you, have had anywhere from some to considerable success, and interested in sharing their learnings with others.  You know, people like me [1].

Look, I’m not going to argue that getting advice from successful people is a bad idea — it certainly seems preferable to the alternative — but I am going to point out a few caveats, most of which aren’t obvious in my estimation:

  • Successful people don’t actually know what made them successful.  They know what they did.  They know it worked.  They have hunches and beliefs.  Causality, not so much.  Some of them can be quick to forget that, so you shouldn’t be [2].  There was no control group.  If Marc Benioff carried a rabbit’s foot, would you?
  • Too many successful people are rinse/repeat [3].  I’m frankly surprised by how many successful people are chomping at the bit to do exactly what worked for them at their last company with total disregard for whether it applies to yours.  Beware these folks.  Interview question:  so could you tell me about a situation where you wouldn’t do that?  It’s not foolproof because most will catch the hint, so this is really something you need to listen for before asking.  Do they diagnose-then-prescribe or prescribe without diagnosing?
  • Their situation was likely different from yours.  In fact, in the land of disruption, as Kelly Wright points out in this podcast, it almost certainly was.  Are you creating a new category without competition?  Are you in an over-funded next-big-thing category?  Are you competing against a big company transitioning product lines?  Are you trying to get people to buy something they don’t believe they need or pick among alternatives when they know they do?  Are you disrupting technology, business model, or both?  Are you filling a need that is in the midst of being created the rise of another category?

Should you listen to these people?  I think yes [4].  But try to find ones who have seen both success and failure, seen success in many situations (not just one), and who are thoughtful about a company’s specific situation, and approach the advisory process and their own prior success with humility.

# # #

[1] While I’d characterize my own success as towards the left of that spectrum, I am advising and/or have advised over 20 startups, some of them stunningly successful.

[2] One of my favorite quotes of this ilk is from former Harvard marketing professor, Theodore LevittNothing in business is so remarkable as the conflicting variety of success formulas offered by its numerous practitioners and professors.  And if, in the case of practitioners they’re not exactly “formulas,” they are explanations of “how we did it” implying with firm control over any fleeting tendencies toward modesty that “that’s how you ought to do it.”  Practitioners filled with pride and money turn themselves into prescriptive philosophers, filled mostly with hot air.

[3] By the way, “I made $1B doing it this way” is one of the more difficult arguments you’re probably wise not to take on.

[4] “Duh.”