The one most important SaaS metric. (Hint: LTV/CAC.)
The most misunderstood SaaS metric. (I can’t remember what I said, but I should have said CAC Payback Period.)
A prediction about a workplace activity that is outrageous today but could be commonplace in the future. (I said salary transparency after struggling a bit. I suppose face masks and elbow bumps would have been an easier answer.)
Thoughts on the best software cultures. (Keyword: winning.)
My advice to my younger self. (“Put your hands in the air and step away from the keyboard,” in reference to the various troubles I’ve caused myself over email when I should have either said nothing or called.)
The link to the podcast episode is here. I hope you get a chance to listen to it and enjoy it if you do. Thanks for having me Dan.
As I’ve been doing every year since 2014, I thought I’d take some time to write some predictions for 2020, but not without first doing a review of my predictions for 2019. Lest you take any of these too seriously, I suggest you look at my batting average and disclaimers.
Kellblog 2019 Predictions Review
1. Fred Wilson is right, Trump will not be president at the end of 2019. PARTIAL. He did get impeached after all, but that’s a long way from removed or resigned.
2. The Democratic Party will continue to bungle the playing of its relatively simple hand. HIT. This is obviously subjective and while I think they got some things right (e.g., delaying impeachment), they got others quite wrong (e.g., Mueller Report messaging), and continue to play more left than center which I believe is a mistake.
3. 2019 will be a rough year for the financial markets. MISS. The Dow was up 22% and the NASDAQ was up 35%. Financially, maybe the only thing that didn’t work in 2019 were over-hyped IPOs. Note to self: avoid quantitative predictions if you don’t want to risk ending up very wrong. I am a big believer in regression to the mean, but nailing timing is the critical (and virtually impossible) part. Nevertheless, I do use tables like these to try and eyeball situations where it seems a correction is needed. Take your own crack at it.
4. VC tightens. MISS. Instead of tightening, VC financing hit a new record. The interesting question here is whether mean reversion is relevant. I’d argue it’s not – the markets have changed structurally such that companies are staying private far longer and thus living off venture capital (and/or growth-stage private equity) in ways not previously seen. Mark Suster did a great presentation on this, Is VC Still a Thing, where he explains these and other changes in VC. A must read.
8. Oracle enters decline phase and is increasingly seen as a legacy vendor. HIT. Again, this is highly subjective and some people probably concluded it years ago. My favorite support point comes from a recent financial analyst note: “we believe Oracle can sustain ~2% constant currency revenue growth, but we are dubious that Oracle can improve revenue growth rates.” That pretty much says it all.
9. ServiceNow and/or Splunk get acquired. MISS. While they’re both great businesses and attractive targets, they are both so expensive only a few could make the move – and no one did. Today, Splunk is worth $24B and ServiceNow a whopping $55B.
10. Workday succeeds with its Adaptive Insights agenda. HIT. Changing general ledgers is a heart transplant while changing planning systems is a knee replacement. By acquiring Adaptive, Workday gave itself another option – and a far easier entry point – to get into corporate finance departments. While most everyone I knew scratched their head at the enterprise-focused Workday acquiring a more SMB-focused Adaptive, Workday has done a good job simultaneously leaving Adaptive alone-enough to not disturb its core business while working to get the technology more enterprise-ready for its customers. Whether that continues I don’t know, but for the first 18 months at least, they haven’t blown it. This remains high visibility to Workday as evidenced by the Adaptive former CEO (and now Workday EVP of Planning) Tom Bogan’s continued attendance on Workday’s quarterly earnings calls.
With the dubious distinction of having charitably self-scored a 6.0 on my 2019 predictions, let’s fearlessly roll out some new predictions for 2020.
Kellblog 2020 Predictions
1. Ongoing social unrest. The increasingly likely trial in the Senate will be highly contentious, only to be followed by an election that will be highly contentious as well. Beyond that, one can’t help but wonder if a defeated Trump would even concede, which could lead to a Constitutional Crisis of the next level. Add to all that the possibility of a war with Iran. Frankly, I am amazed that the Washington, DC continuous distraction machine hasn’t yet materially damaged the economy. Like many in Silicon Valley, I’d like Washington to quietly go do its job and let the rest of us get back to doing ours. The reality TV show in Washington is getting old and, happily, I think many folks are starting to lose interest and want to change the channel.
2. A desire for re-unification. I remain fundamentally optimistic that your average American – Republican, Democrat, or the completely under-discussed 38% who are Independents — wants to feel part of a unified, not a divided, America. While politicians often try to leverage the most divisive issues to turn people into single-issue voters, the reality is that far more things unite us as Americans than divide us. Per this recent Economist/YouGov wide-ranging poll, your average American looks a lot more balanced and reasonable than our political party leaders. I believe the country is tired of division, wants unification, and will therefore elect someone who will be seen as able to bring people together. We are stronger together.
3. Climate change becomes the new moonshot. NASA’s space missions didn’t just get us to the moon; they produced over 2,000 spin-off technologies that improve our lives every day – from emergency “space” blankets to scratch-resistant lenses to Teflon-coated fabrics. Instead of seeing climate change as a hopeless threat, I believe in 2020 we will start to reframe it as the great opportunity it presents. When we mobilize our best and brightest against a problem, we will not only solve it, but we will create scores to hundreds of spin-off technologies that will benefit our everyday lives in the process. See this article for information on 10 startups fighting climate change, this infographic for an overview of the kinds of technologies that could alleviate it, or this article for a less sanguine view on the commitment required and extent to which we actually can de-carbonize the air. Or check out this startup which makes “trees” that consume the pollution of 275 regular trees.
4. The strategic chief data officer (CDO). I’m not a huge believer in throwing an “O” at every problem that comes along, but the CDO role is steadily becoming mainstream – in 2012 just 12% of F1000 companies reported having a CDO; in 2018 that’s up to 68%. While some of that growth was driven by defensive motivations (e.g., compliance), increasingly I believe that organizations will define the CDO more strategically, more broadly, and holistically as someone who focuses on data, its cleanliness, where to find it, where it came from, its compliance with regulations as to its usage, its value, and how to leverage it for operational and strategic advantage. These issues are thorny, technical, and often detail-oriented and the CIO is simply too busy with broader concerns (e.g., digital transformation, security, disruption). Ergo, we need a new generation of chief data officers who want to play both offense and defense, focused not just tactically on compliance and documentation, but strategically on analytics and the creation of business value for the enterprise. This is not a role for the meek; only half of CDOs succeed and their average tenure is 2.4 years. A recent Gartner CDO study suggests that those who are successful take a more strategic orientation, invest in a more hands-on model of supporting data and analytics, and measure the business value of their work.
5. The ongoing rise of DevOps. Just as agile broke down barriers between product management and development so has DevOps broken down walls between development and operations. The cloud has driven DevOps to become one of the hottest areas of software in recent years with big public company successes (e.g., Atlassian, Splunk), major M&A (e.g., Microsoft acquiring GitHub), and private high-flyers (e.g., HashiCorp, Puppet, CloudBees). A plethora of tools, from configuration management to testing to automation to integration to deployment to multi-cloud to performance monitoring are required to do DevOps well. All this should make for a $24B DevOps TAM by 2023 per a recent Cowen & Company report. Ironically though, each step forward in deployment is often a step backward in developer experience.
7. A new, data-layer approach to data loss prevention (DLP). I always thought DLP was a great idea, especially the P for prevention. After all, who wants tools that can help with forensics after a breach if you could prevent one from happening at all — or at least limit one in progress? But DLP doesn’t seem to work: why is it that data breaches always seem to be measured not in rows, but in millions of rows? For example, Equifax was 143M and Marriott was 500M. DLP has many known limitations. It’s perimeter-oriented in a hybrid cloud world of dissolving perimeters and it’s generally offline, scanning file systems and database logs to find “misplaced data.” Wouldn’t a better approach be to have real-time security monitored and enforced at the data layer, just the same way as it works at the network and application layer? Then you could use machine learning to understand normal behavior, detect anomalous behavior, and either report it — or stop it — in real time. I think we’ll see such approaches come to market in 2020, especially as cloud services like Snowflake, RDS, and BigQuery become increasingly critical components of the data layer.
8. AI/ML continue to see success in highly focused applications. I remain skeptical of vendors with broad claims around “enterprise AI” and remain highly supportive of vendors applying AI/ML to specific problems (e.g., Moveworks and Astound who both provide AI/ML-based trouble-ticket resolution). In the end, AI and ML are features, not apps, and while both technologies can be used to build smart applications, they are not applications unto themselves. In terms of specificity, the No Free Lunch Theorem reminds us that any two optimization techniques perform equivalently when averaged across all possible problems – meaning that no one modeling technique can solve everything and thus that AI/ML is going to be about lots of companies applying different techniques to different problems. Think of AI/ML more as a toolbox than a platform. There will not be one big winner in enterprise AI as there was in enterprise applications or databases. Instead, there will be lots of winners each tackling specific problems. The more interesting battles will those between systems of intelligence (e.g., Moveworks) and systems of record (e.g., ServiceNow) with the systems-of-intelligence vendors running Trojan Horse strategies against systems-of-record vendors (first complementing but eventually replacing them) while the system-of-record vendors try to either build or acquire systems of intelligence alongside their current offerings.
9. Series A rounds remain hard. I think many founders are surprised by the difficulty of raising A rounds these days. Here’s the problem in a nutshell:
Seed capital is readily available via pre-seed and seed-stage investments from angel investors, traditional early-stage VCs, and increasingly, seed funds. Simply put, it’s not that hard to raise seed money.
Companies are staying in the seed stage longer (a median of 1.6 years), increasingly extending seed rounds, and ergo raising more money during seed stage (e.g., $2M to $4M).
Such that, companies are now expected to really have achieved something in order to raise a Series A. After all, if you have been working for 2 years and spent $3M you better have an MVP product, a handful of early customers, and some ARR to show for it – not just a slide deck talking about a great opportunity.
Moreover, you should be making progress roughly in line with what you said at the outset and, if you took seed capital from a traditional VC, then they better be prepared to lead your round otherwise you will face signaling risk that could imperil your Series A.
Simply put, Series A is the new chokepoint. Or, as Suster likes to say, the Series A and B funnel hasn’t really changed – we’ve just inserted a new seed funnel atop it that is 3 times larger than it used to be.
10. Autonomy’s former CEO gets extradited. Silicon Valley is generally not a place of long memories, but I saw the unusual news last month that the US government is trying to extradite Autonomy founder and former CEO Mike Lynch from the UK to face charges. You might recall that HP, in the brief era under Leo Apotheker, acquired enterprise search vendor Autonomy in August, 2011 for a whopping $11B only to write off about $8.8B under subsequent CEO Meg Whitman a little more than a year later in November, 2012. Computerworld provides a timeline of the saga here, including a subsequent PR war, US Department of Justice probe, UK Serious Fraud Office investigation (later dropped), shareholder lawsuits, proposed settlements, more lawsuits including Lynch’s suing HP for $150M for reputation damages, and HP’s spinning-off the Autonomy assets. Subsequent to Computerworld’s timeline, this past May Autonomy’s former CFO was sentenced to five years in prison. This past March, the US added criminal charges of securities fraud, wire fraud, and conspiracy against Lynch. Lynch continues to deny all wrongdoing, blames the failed acquisition on HP, and even maintains a website to present his point of view on the issues. I don’t have any special legal knowledge or specific knowledge of this case, but I do believe that if the US government is still fighting this case, still adding charges, and now seeking extradition, that they aren’t going to give up lightly, so my hunch is that Lynch does come to the US and face these charges.
More broadly, regardless of how this particular case works out, in a place so prone to excess, where so much money can be made so quickly, frauds will periodically happen and it’s probably the most under-reported class of story in Silicon Valley. Even this potentially huge headline case – the proposed extradition of a British billionaire tech mogul — never seems to make page one news. Hey, let’s talk about something positive like Loft’s $175M Series C instead.
To finish this up, I’ll add a bonus prediction: Dave doesn’t get a traditional job in 2020. While I continue to look at VC-backed startup and/or PE-backed CEO opportunities, I am quite enjoying my work doing a mix of boards, advisory relationships, and consulting gigs. While I remain interested in looking at great CEO opportunities, I am also interested in adding a few more boards to my roster, working on stimulating consulting projects, and a few more advisory relationships as well.
I wish everyone a happy, healthy, and above-plan 2020.
I’m Dave Kellogg, advisor, director, consultant, angel investor, and blogger focused on enterprise software startups. I am an executive-in-residence (EIR) at Balderton Capital and principal of my own eponymous consulting business.
I bring an uncommon perspective to startup challenges having 10 years’ experience at each of the CEO, CMO, and independent director levels across 10+ companies ranging in size from zero to over $1B in revenues.
From 2012 to 2018, I was CEO of cloud EPM vendor Host Analytics, where we quintupled ARR while halving customer acquisition costs in a competitive market, ultimately selling the company in a private equity transaction.
Previously, I was SVP/GM of the $500M Service Cloud business at Salesforce; CEO of NoSQL database provider MarkLogic, which we grew from zero to $80M over 6 years; and CMO at Business Objects for nearly a decade as we grew from $30M to over $1B in revenues. I started my career in technical and product marketing positions at Ingres and Versant.
I love disruption, startups, and Silicon Valley and have had the pleasure of working in varied capacities with companies including Bluecore, FloQast, GainSight, Hex, MongoDB, Pigment, Recorded Future, and Tableau.
I currently serve on the boards of Cyber Guru (cybersecurity training), Jiminny (conversation intelligence), and Scoro (work management).
I previously served on the boards of Alation (data intelligence), Aster Data (big data), Granular (agtech), Nuxeo (content services), Profisee (MDM), and SMA Technologies (workload automation).
I periodically speak to strategy and entrepreneurship classes at the Haas School of Business (UC Berkeley) and Hautes Études Commerciales de Paris (HEC).