Category Archives: Predictions

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 to 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.

Kellblog’s 10 Predictions for 2020

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.

5. Social media companies get regulated.  PARTIAL.  While “history may tell us the social media regulation is inevitable,” it didn’t happen in 2019.  However, the movement continued to gather steam with many Democratic presidential candidates calling for reform and, more notably, none other than Facebook investor Roger McNamee launching his attack on social media via his book Zucked: Waking Up To The Facebook Catastrophe.  As McNamee says, “it’s an issue of ‘right vs. wrong,’ not ‘right vs. left.’”

 

6. Ethics make a comeback.  HIT.  Ethics have certainly been more discussed than ever and related to the two reasons I cited:  the current administration and artificial intelligence.  The former forces ethics into the spotlight on a daily basis; the later provokes a slew of interesting questions, from questions of accidental bias to the trolley car problem.  Business schools continue to increase emphasis on ethics.  Mark Benioff has led a personal crusade calling for what he calls a new capitalism.

7.  Blockchain, as an enterprise technology, fades away.  HIT.  While I hate to my find myself on the other side of Ray Wang, I’m personally not seeing much traction for blockchain in the enterprise.  Maybe I’m running with the wrong crowd.  I have always felt that blockchain was designed for one purpose (to support cybercurrency), hijacked to another, and ergo became a vendor-led technology in search of a business problem.  McKinsey has a written a sort of pre-obituary, Blockchain’s Occam Problem, which was McKinsey Quarterly’s second most-read article of the year.  The 2019 Blockchain Opportunity Summit’s theme was Is Blockchain Dead?  No. Industry Experts Join Together to Share How We Might Not be Using it Right which also seems to support my argument. 

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, why is one reason why I decided to work with Kelda in 2019.

6. Database proliferation slows.  While 2014 Turning Award winner Mike Stonebraker was right over a decade ago when he argued in favor of database specialization (One Size Fits All:  An Idea Whose Time Has Come and Gone), I think we may now too much of a good thing.   DB Engines now lists 350 different database systems of 14 different types (e.g., relational, graph, time series, key-value). Crunchbase lists 274 database (and database-related) startups.  I believe the database market is headed for consolidation.  One of the first big indicators of a resurgence in database sanity was the failure of the (Hadoop-based) data lake, which happened in 2018-2019 and was the closest thing I’ve seen to déjà vu in my professional career – it was as if we learned nothing from the Field of Dreams enterprise data warehouse of the 1990s (“build it and they will come”).  Moreover, after a decade of developer-led database selection, developers and now re-realizing what database people knew along – that a lot of the early NoSQL movement was akin to throwing out the ACID transaction baby with the tabular schema bathwater.

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.

Kellblog Predictions for 2019

Because I’ve been quite busy of late with the sale of my company, I’m doing a somewhat quicker and lighter (if not later) version of my annual predictions post.  Here goes, starting with a review of last year’s predictions.

2018 Kellblog Predictions Review

1. We will again continue to see a level of divisiveness and social discord not seen since the 1960s. HIT.  Hard to argue I need to justify this one.  Want to argue about it?

2. The war on facts and expertise will continue to escalate. HIT. Unfortunately, the President is leading the charge on this front, with the Washington Post fact checker tallying 7,645 false claims since taking office.

factchecker

3. Leading technology and social media companies finally step up to face ethical challenges. MAJOR MISS.  Well, I nailed that the issue would be critical, but boy did I overestimate the maturity of the management of these companies.

4. AI will move from hype to action, meaning bigger budgets, more projects, and some high visibility failures. HIT, I think.  See this McKinsey report for some interesting survey data on AI adoption and barriers to it.

5. AI will continue to generate lots of controversy about job displacement. HIT. While the optimists say AI will create more jobs than it will displace, many still worry conversely.  Since the prediction was about the controversy continuing, we’ll call it a hit.

6. The bitcoin bubble bursts. MAJOR HIT.  This one partially redeems me for over-estimating Facebook’s management.

btc

7. The Internet of Things (IoT) will continue to build momentum.  HIT. See this Forbes article about data from Dresner Advisory’s 2018 IoT Intelligence Market Study.

8. The freelance / gig economy continues to gain momentum with freelance workers poised to pass traditional employees by 2027. HIT.  Per this Forbes article, 57M people now participate in the gig economy in some way.

9. M&A heats up due to repatriation of overseas cash.  HIT. Per Berkery Noyes, software M&A deal value was up nearly $100B over 2017.  To the extent this was due to overseas cash repatriation I don’t know, but it certainly was a factor.

m-and-a

10. 2018 will be a good year for cloud EPM vendors. MAJOR HIT.  Anaplan went public, Adaptive Insights was acquired by Workday, and Host Analytics was acquired by Vector Capital. 

With 9 hits, two of them major – and with only one offsetting major miss — I should probably just drop the mike and get out of the predictions business.  But no guts, no glory.

Kellblog’s 2019 Predictions

Reminder to see the disclaimers in my FAQ and remember that these predictions are not financial or business advice – they are made in the spirit of fun.  To the extent they’re concrete, that’s to make the game more interesting so we can better assess them next year.  Here we go.

1. Fred Wilson is right, Trump will not be president at the end of 2019. I think Fred’s also right on virtually all of the other predictions made in his epic post, which I won’t attempt to summarize here. Read Fred’s post – and just make sure you read to the end, because it’s not all doom and gloom.  So, as a Kellblog first, prediction #1 is a pointer.

2. The Democratic Party will continue to bungle the playing of its relatively simple hand. Party leaders will continue to fail to realize that the way to beat Trump is not through a hard-left platform with 70% tax rates that caters to the most liberal Democrats – but a centrist, pragmatic, people- and business-friendly platform that certainly won’t be enough for the far left, but will be far better than the Republican alternative for all Democrats, and most importantly, give centrist Republicans a realistic alternative to what their party is offering them.  The Democratic Party will continue to be more concerned with making statements than winning elections.  This may cost it, and the Nation, dearly.

Remember the famous Will Rodgers quote: “I am not a member of any organized political party.  I am a Democrat.”

 3. 2019 will be a rough year for the financial markets. Political problems in the USA, Europe, and increasingly Latin American.  Trade wars.  Record deficits as we re-discover that trickle-down, tax-cut economics don’t work.  Threat of rising interest rates.   Brexit.   Many folks see a bear market coming.

Years ago, I accepted the fact that – like many – I am a hypocrite when it comes to the stock market.  Yes, I absolutely believe that it’s theoretically impossible to time the market.   But yes, I’m entering 2019 with a high allocation to cash and intend to keep it that way.  Hum.  Try to reconcile that.

For fun, let’s makes this concrete and predict that the BVP Emerging Cloud Index will end 2019 at 750.  I do this mostly to provide some PR for Bessemer’s Index, officially launched via the NASDAQ in October, 2018, but which was built on the back of five years of Bessemer maintaining it themselves.

4. VC tightens. Venture capital funding has been booming the past several years and – for the above reasons and others (e.g., the fact that most VCs don’t product enough returns to justify the risk and illiquidity) – I believe there will be tightening of VC in 2019.  If you agree, that means you should raise money now, while the sun’s still shining, and try to raise two years of capital required in your business plan (with some cushion).

dwk-2mru8aaof8b

If things follow the recent trends, this will be hardest on average and/or struggling companies as VCs increasingly try to pick winners and make bets conservative in the sense that they are on known winners, even if they have to overpay to do so.  In this scenario, capital on reasonable terms could all but dry up for companies who have gone off-rails on their business plans.   So, if you’re still on rails, you might raise some extra capital now.  Getting greedy by trying to put up two more good quarters to take less dilution on your next round could backfire – you might miss one of those quarters in this increasingly volatile environment, but even if you don’t, VC market tightening could offset any potential valuation increase.

5. Social media companies get regulated. Having failed for years to self-regulate in areas of data privacy and usage, these companies will likely to face regulations in 2019 in the face of strong consumer backlash.  The first real clue I personally had in this area was during the 2016 election when Facebook didn’t just feed me, but actually promoted, a fake Denver Guardian story about a supposedly dead FBI agent linked to “her emails.”  I then read the now-famous “bullshit is highly engaging” quote from this story which helped reveal the depth of the problem:

Or, as former Facebook designer Bobby Goodlatte wrote on his own Facebook wall on November 8, “Sadly, News Feed optimizes for engagement. As we’ve learned in this election, bullshit is highly engaging. A bias towards truth isn’t an impossible goal. Wikipedia, for instance, still bends towards the truth despite a massive audience. But it’s now clear that democracy suffers if our news environment incentivizes bullshit.”

I won’t dive into detail here.  I do think Sheryl Sandberg may end up leaving Facebook; she was supposed to be the adult supervision, after all.  While I think he’s often a bit too much, I nevertheless recommend reading Chaos Monkeys for an interesting and, at times, hilarious insider look at Facebook and/or following its author Antonio Garcia Martinez.

6. Ethics make a comeback, for two reasons.  The first will be as a backlash to the blatant corruption of the current administration.  To wit:  the House recently passed a measure requiring annual ethics training for its members.  The second will have to do with AI and automation.  The Trolley Problem, once a theoretical exercise in ethics, is now all too real with self-driving cars.  Consider this data, based on MIT research in this article which shows preferences for sparing various characters in the event of a crash.

crash

Someone will probably end up programming such preferences into a self-driving car.  Or, worse yet, as per the Trolley Problem, maybe they won’t.  While we may want to avoid these issues because they are uncomfortable, in 2019 I think they will be thrust onto center stage.

7. Blockchain, as an enterprise technology, fades away. Blockchain is a technology in search of a killer application.  Well, it actually has one killer application, cryptocurrency, which is why it was built.  And while I am a fan of cybercurrencies, blockchain is arguably inefficient at what it was built to do.  While Bitcoin will not take down the world electric grid as some have feared, it is still tremendously energy consumptive –in coming years, Bitcoin is tracking to consume 7.7 GW per year, comparable to the entire country of Austria at 8.2 GW.

While I’m not an expert in this field, I see three things that given me huge pause when it comes to blockchain in the enterprise:  (1) it’s hard to understand, (2) it consumes a huge amount of energy, and (3) people have been saying for too long that the second blockchain killer app (and first enterprise blockchain killer app) is just around the corner.  Think:  technology in search of a business problem.  What’s more, even for its core use-case, cryptocurrency, blockchain is vulnerable to being cracked by quantum computing by 2027.

8. Oracle enters decline phase and is increasingly seen as a legacy vendor. For decades I have personally seen Oracle as a leader.  First, in building the RDBMS market.  Second, in consolidating a big piece of the enterprise applications market.  Third, more generally, in consolidating enterprise software.  But, in my mind, Oracle is no longer a leader.  Perhaps you felt this way long ago.  I’d given them a lot of credit for their efforts (if not their progress) in the cloud – certainly better than SAP’s or IBM’s.  But SAP and IBM are not the competitors to beat in the future:  Amazon, Google, and a rejuvenated Microsoft are.  The reality is that Oracle misses quarters, cloud-washes sales, and is basically stagnant in revenue growth.  They have no vision.  They have become a legacy vendor.

The final piece of this snapped into place when Thomas Kurian departed to Google in a dispute with Larry Ellison about the cloud.  DEC’s Ken Olsen once said that Unix was “snake oil” and that was the beginning of the end for DEC.  Ellison once said roughly the same thing (“complete gibberish”) about the cloud.  And now the cloud is laughing back.

9. ServiceNow and/or Splunk get acquired. A friend of mine planted this seed in my mind and it’s more about corporate evolution than anything else.  They’re both great businesses that mega-vendors would love to own – especially if they end up “on sale” if we hit a bear market.

10. Workday succeeds with its Adaptive Insights agenda, meaning that Adaptive’s mid-market and SMB presence will be greatly lessened.   Most people I know think Workday’s acquisition of Adaptive was a head-scratcher.  Yes, Workday struggles in financial apps.  Yes, EPM is an easier entry point than core financials (which, as Zach Nelson used to say, were like a heart transplant).  But why in the world would a high-end vendor (with average revenue/customer of $1M+) acquire a low-end EPM vendor (with average revenue/customer of $27K)?  That’s hard to figure out.

But just because the acquisition was, to be kind, non-obvious, it doesn’t mean Workday won’t be successful with it.  Workday’s goals are clear: (1) to unite Adaptive with Workday in The Power of One – including re-platforming the backend and re-writing the user-interface, (2) to provide EPM to Workday’s high-end customer base, and (3) to provide an alternate financial entry point for sales when prospects say they’re not up for a heart transplant for at least 5 years.  I’m not saying Workday can’t be successful with their objectives.  I am saying Adaptive won’t be Adaptive when they’re done — you can’t be the high-end, low-end, cheap, expensive, simple, complex, agnostic, integrated EPM system.   Or, as SNL put it, you can’t be Shimmer — a dessert topping and a floor wax.  The net result:   like Platfora before them or Outlooksoft within SAP, Adaptive disappears within Workday and its presence in the mid-market and SMB is greatly reduced.

# # #

Disclaimer:  these predictions are offered in the spirit of fun.  See my FAQ for more and other terms of use.

Kellblog Predictions for 2018

In continuing my tradition of offering predictions every year, let’s start with a review of my hits and misses on my 2017 predictions.

  1. The United States will see a level of divisiveness and social discord not seen since the 1960s.  HIT.
  2. Social media companies finally step up and do something about fake news. MISS, but ethical issues are starting to catch up with them.
  3. Gut feel makes a comeback. HIT, while I didn’t articulate it as such, I see this as the war on facts and expertise (e.g., it’s cold today ergo global warming isn’t real despite what “experts” say).
  4. Under a volatile leader, we can expect sharp reactions and knee-jerk decisions that rattle markets, drive a high rate of staff turnover in the Executive branch, and fuel an ongoing war with the media.  HIT.
  5. With the new administration’s promises of $1T in infrastructure spending, you can expect interest rates to raise and inflation to accelerate. MISS, turns out this program was never classical government investment in infrastructure, but a massive privatization plan that never happened.
  6. Huge emphasis on security and privacy. PARTIAL HIT, security remained a hot topic and despite numerous major breaches it’s still not really hit center stage.
  7. In 2017, we will see more bots for both good uses (e.g., customer service) and bad (e.g., trolling social media).  HIT.
  8. Artificial intelligence hits the peak of inflated expectations. HIT.
  9. The IPO market comes back. MISS, though according to some it “sucked less.”
  10. Megavendors mix up EPM and ERP or BI. PARTIAL HIT.  This prediction was really about Workday and was correct to the extent that they’ve seemingly not made much progress in EPM.

Kellblog’s Predictions for 2018

1.  We will again continue to see a level of divisiveness and social discord not seen since the 1960s. We have evolved from a state of having different opinions about policies based on common facts to a dangerous state based on different facts, even on easily disprovable claims, e.g., the White House nativity scene.  The media is advancing, not reducing, this divide.

2.  The war on facts and expertise will continue to escalate. Read The Death of Expertise for more.   This will extend to a war on college. While an attempted opening salvo on graduate student tuition waivers didn’t fire, in an environment where the President’s son says, “we’ll take $200,000 of your money; in exchange we’ll train your children to hate our country,” you can expect ongoing attacks on post-secondary education.  This spells trouble for Silicon Valley, where a large number of founders and entrepreneurs are former grad students as well as immigrants (which is a whole different area of potential trouble).

3.  Leading technology and social media companies finally step up to face ethical challenges. This means paying more attention to their own culture (e.g., sexual harassment, brogrammers).  This means taking responsibility for policing trolls, spreading fake news, building addictive content, and enabling foreign intelligence operations.  Thus far, they have tended to argue they are simply keepers of the town square, and not responsible for the content shared there.  This abdication of responsibility should start to stop in 2018, if only because people start to tune-out the services.  This leads to one of my favorite tweets of the year:

Capture

4.  AI will move from hype to action, meaning bigger budgets, more projects, and some high visibility failures. It will also mean more emphasis on voice and more conversational chatbots.  For finance departments, this means more of what Ventana’s Rob Kugel calls the age of robotic finance, which unites AI and machine learning, robotic process automation (RPA), natural language bots, and blockchain-based distributed ledgers.

5. AI will continue to generate lots of controversy about job displacement. While some remain optimistic, the consensus viewpoint seems to be that AI will suppress employment, most likely widening the wealth inequality gap.  A collapsing educational system combined with AI-driven pressure on low-skilled work seems a recipe for trouble.

6.  The bitcoin bubble bursts. As a reminder, at one point during the peak of tulip mania, the Dutch East India Company was worth more, on an inflated-adjusted basis, than twenty of today’s technology giants combined.

tulips

7.  The Internet of Things (IoT) will continue to build momentum.  IoT won’t hit in a massive horizontal way, instead B2B adoption will be lead by certain verticals such as healthcare, retail, and supply chain.

8.  The freelance / gig economy continues to gain momentum with freelance workers poised to pass traditional employees by 2027. While the gig economy brings advantages to high-skilled knowledge workers (e.g., freedom of location, freedom of work projects), this same trend threatens low-skilled workers via the continual decomposition of full-time jobs in a series of temp shifts.  This means someone working 60 hours a week across three 20-hour shifts wouldn’t be considered to be a full-time employee and thus not eligible for full-time benefits, further increasing wealth inequality.

freelancers

9.  M&A heats up due to repatriation of overseas cash. Apple alone, for example, has $252B in overseas cash.  With the new tax rate dropping from 35% to 15.5%, it will now be ~$50B less expensive for Apple to repatriate that cash.  Overall, US companies hold trillions of dollars overseas and making it cheaper for them to repatriate that cash suggests that they will be flush with dollars to invest in many areas, including M&A

10.  2018 will be a good year for cloud EPM vendors. The dynamic macro environment, the opportunities posed by cash repatriation, and the strong fundamentals in the economy will increase demand for EPM software that helps companies explore how to best exploit the right set of opportunities facing them.  Oracle will fail in pushing PBCS into the NetSuite base, creating a nice third-party opportunity.  SAP, Microsoft, and IBM will continue to put resources into other strategic investment areas (e.g., IBM and Watson, SAP and Hana) leaving fallow the EPM market adjacent to ERP.  And the greenfield opportunity to replace Excel for financial planning, budgeting, and even consolidations will continue drive strong growth.

Let me wish everyone, particularly the customers, partners, and employees of Host Analytics, a Happy New Year in 2018.

# # #

Disclaimer:  these predictions are offered in the spirit of fun.  See my FAQ for more on this and other usage terms.

Kellblog’s 2017 Predictions  

New Year’s means three things in my world:  (1) time to thank our customers and team at Host Analytics for another great year, (2) time to finish up all the 2017 planning items and approvals that we need to get done before the sales kickoff (including the one most important thing to do before kickoff), and time to make some predictions for the coming year.

Before looking at 2017, let’s see how I did with my 2016 predictions.

2016 Predictions Review

  1. The great reckoning begins. Correct/nailed.  As predicted, since most of the bubble was tied up in private companies owned by private funds, the unwind would happen in slow motion.  But it’s happening.
  2. Silicon Valley cools off a bit. Partial.  While IPOs were down, you couldn’t see the cooling in anecdotal data, like my favorite metric, traffic on highway101.
  3. Porter’s five forces analysis makes a comeback. Partial.  So-called “momentum investing” did cool off, implying more rational situation analysis, but you didn’t hear people talking about Porter per se.
  4. Cyber-cash makes a rise. CorrectBitcoin more doubled on the year (and Ethereum was up 8x) which perversely reinforced my view that these crypto-currencies are too volatile — people want the anonymity of cash without a highly variable exchange rate.  The underlying technology for Bitcoin, blockchain, took off big time.
  5. Internet of Things goes into trough of disillusionment. Partial.  I think I may have been a little early on this one.  Seems like it’s still hovering at the peak of inflated expectations.
  6. Data science rises as profession. Correct/easy.  This continues inexorably.
  7. SAP realizes they are a complex enterprise application company. Incorrect.  They’re still “running simple” and talking too much about enabling technology.  The stock was up 9% on the year in line with revenues up around 8% thus far.
  8. Oracle’s cloud strategy gets revealed – “we’ll sell you any deployment model you want as long as your annual bill goes up.”  Partial.  I should have said “we’ll sell you any deployment model you want as long as we can call it cloud to Wall St.”
  9. Accounting irregularities discovered at one or more unicorns. Correct/nailed.  During these bubbles the pattern always repeats itself – some people always start breaking the rules in order to stand out, get famous, or get rich.  Fortune just ran an amazing story that talks about the “fake it till you make it” culture of some diseased startups.
  10. Startup workers get disappointed on exits. Partial.  I’m not aware of any lawsuits here but workers at many high flyers have been disappointed and there is a new awareness that the “unicorn party” may be a good thing for founders and VCs, but maybe not such a good thing for rank-and-file employees (and executive management).
  11. The first cloud EPM S-1 gets filed. Incorrect.  Not yet, at least.  While it’s always possible someone did the private filing process with the SEC, I’m guessing that didn’t happen either.
  12. 2016 will be a great year for Host Analytics. Correct.  We had a strong finish to the year and emerged stronger than we started with over 600 great customers, great partners, and a great team.

Now, let’s move on to my predictions for 2017 which – as a sign of the times – will include more macro and political content than usual.

  1. The United States will see a level of divisiveness and social discord not seen since the 1960s. Social media echo chambers will reinforce divisions.  To combat this, I encourage everyone to sign up for two publications/blogs they agree with and two they don’t lest they never again hear both sides of an issue. (See map below, coutesy of Ninja Economics, for help in choosing.)  On an optimistic note, per UCSD professor Lane Kenworthy people aren’t getting more polarized, political parties are.

news

  1. Social media companies finally step up and do something about fake news. While per a former Facebook designer, “it turns out that bullshit is highly engaging,” these sites will need to do something to filter, rate, or classify fake news (let alone stopping to recommend it).  Otherwise they will both lose credibility and readership – as well as fail to act in a responsible way commensurate with their information dissemination power.
  1. Gut feel makes a comeback. After a decade of Google-inspired heavily data-driven and A/B-tested management, the new US administration will increasingly be less data-driven and more gut-feel-driven in making decisions.  Riding against both common sense and the big data / analytics / data science trends, people will be increasingly skeptical of purely data-driven decisions and anti-data people will publicize data-driven failures to popularize their arguments.  This “war on data” will build during the year, fueled by Trump, and some of it will spill over into business.  Morale in the Intelligence Community will plummet.
  1. Under a volatile leader, who seems to exhibit all nine of the symptoms of narcissistic personality disorder, we can expect sharp reactions and knee-jerk decisions that rattle markets, drive a high rate of staff turnover in the Executive branch, and fuel an ongoing war with the media.  Whether you like his policies or not, Trump will bring a high level of volatility the country, to business, and to the markets.
  1. With the new administration’s promises of $1T in infrastructure spending, you can expect interest rates to raise and inflation to accelerate. Providing such a stimulus to already strong economy might well overheat it.  One smart move could be buying a house to lock in historic low interest rates for the next 30 years.  (See my FAQ for disclaimers, including that I am not a financial advisor.)
  1. Huge emphasis on security and privacy. Election-related hacking, including the spearfishing attack on John Podesta’s email, will serve as a major wake-up call to both government and the private sector to get their security act together.  Leaks will fuel major concerns about privacy.  Two-factor authentication using verification codes (e.g., Google Authenticator) will continue to take off as will encrypted communications.  Fear of leaks will also change how people use email and other written electronic communications; more people will follow the sage advice in this quip:

Dance like no one’s watching; E-mail like it will be read in a deposition

  1. In 2015, if you were flirting on Ashley Madison you were more likely talking to a fembot than a person.  In 2016, the same could be said of troll bots.  Bots are now capable of passing the Turing Test.  In 2017, we will see more bots for both good uses (e.g., customer service) and bad (e.g., trolling social media).  Left unchecked by the social media powerhouses, bots could damage social media usage.
  1. Artificial intelligence hits the peak of inflated expectations. If you view Salesforce as the bellwether for hyped enterprise technology (e.g., cloud, social), then the next few years are going to be dominated by artificial intelligence.  I’ve always believed that advanced analytics is not a standalone category, but instead fodder that vendors will build into smart applications.  They key is typically not the technology, but the problem to which to apply it.  As Infer founder Vik Singh said of Jim Gray, “he was really good at finding great problems,” the key is figuring out the best problems to solve with a given technology or modeling engine.  Application by application we will see people searching for the best problems to solve using AI technology.
  1. The IPO market comes back. After a year in which we saw only 13 VC-backed technology IPOs, I believe the window will open and 2017 will be a strong year for technology IPOs.  The usual big-name suspects include firms like Snap, Uber, AirBnB, and SpotifyCB Insights has identified 369 companies as strong 2017 IPO prospects.
  1. Megavendors mix up EPM and ERP or BI. Workday, which has had a confused history when it comes to planning, acquired struggling big data analytics vendor Platfora in July 2016, and seems to have combined analytics and EPM/planning into a single unit.  This is a mistake for several reasons:  (1) EPM and BI are sold to different buyers with different value propositions, (2) EPM is an applications sale, BI is a platform sale, and (3) Platfora’s technology stack, while appropriate for big data applications is not ideal for EPM/planning (ask Tidemark).  Combining the two together puts planning at risk.  Oracle combined their EPM and ERP go-to-market organizations and lost focus on EPM as a result.  While they will argue that they now have more EPM feet on the street, those feet know much less about EPM, leaving them exposed to specialist vendors who maintain a focus on EPM.  ERP is sold to the backward-looking part of finance; EPM is sold to the forward-looking part.  EPM is about 1/10th the market size of ERP.  ERP and EPM have different buyers and use different technologies.  In combining them, expect EPM to lose out.

And, as usual, I must add the bonus prediction that 2017 proves to be a strong year for Host Analytics.  We are entering the year with positive momentum, the category is strong, cloud adoption in finance continues to increase, and the megavendors generally lack sufficient focus on the category.  We continue to be the most customer-focused vendor in EPM, our new Modeling product gained strong momentum in 2016, and our strategy has worked very well for both our company and the customers who have chosen to put their faith in us.

I thank our customers, our partners, and our team and wish everyone a great 2017.

# # #

 

Kellblog Predictions for 2016

As the new year approaches, it’s time for another set of predictions, but before diving into my list for 2016, let’s review and assess the predictions I made for 2015.

Kellblog’s 2015 Predictions Review

  1. The good times will continue to roll in Silicon Valley.  I asserted that even if you felt a bubble, that it was more 1999 than 2001.  While IPOs slowed on the year, private financing remained strong — traffic is up, rents are up and unemployment is down.  Correct.
  2. The IPO as down-round continues.  Correct.
  3. The curse of the mega-round strikes many companies and CEOs.  While I can definitely name some companies where this has occurred, I can think of many more where I still think it’s coming but yet to happen.  Partial / too early.
  4. Cloud disruption continues.  From startups to megavendors, the cloud and big data are almost all everyone talks about these days.  Correct.
  5. Privacy becomes a huge issue.  While I think privacy continues to move to center stage, it hasn’t become as big as I thought it would, yet.  Partial / too early.
  6. Next-generation apps like Slack and Zenefits continue to explode.  I’d say that despite some unicorn distortion that this call was right (and we’re happy to have signed on Slack as a Host Analytics customer in 2015 to boot).  Correct.
  7. IBM software rebounds.  At the time I made this prediction IBM was in the middle of a large reorganization and I was speculating (and kinda hoping) that the result would be a more dynamic IBM software business.  That was not to be.  Incorrect.
  8. Angel investing slows.  I couldn’t find any hard figures here, but did find a great article on why Tucker Max quit angel investing.  I’m going to give myself a partial here because I believe the bloom is coming off the angel investing rose.  Partial.
  9. The data scientist shortage continues. This one’s pretty easy.   Correct.
  10. The unification of planning becomes the top meme in EPM.  This was a correct call and supported, in part, through our own launch of Modeling Cloud, a cloud-based, multi-dimensional modeling engine that helps tie enterprise models both to each other and the corporate plan.  Correct.

So, let’s it call it 7.5 out of 10.  Not bad, when you recall my favorite quote from Yogi Berra:  “predictions are hard, especially about the future.”

Kellblog’s Top Predictions for 2016

Before diving into these predictions, please see the footnote for a reminder of the spirit in which they are offered.

1. The great reckoning begins.   I view this as more good than bad because it will bring a return to commonsense business practices and values.  The irrationality that came will bubble 2.0 will disperse.  It took 7 years to get into this situation so expect it to take a few years to get out.  Moreover, since most of the bubble is in illiquid securities held by illiquid partnerships, there’s not going to be any flash crash — it’s all going to proceed in slow motion, expect for those companies addicted to huge burn rates that will need to shape up quickly.  Quality, well run businesses will continue attract funding and capital will be available for them.  Overall, while there will be some turbulence, I think this will be more good than bad.

2. Silicon Valley cools off a bit.  As a result of the previous prediction, Silicon Valley will calm a bit in 2016:  it will get a bit easier to hire, traffic will modestly improve, and average burn rates will drop.  You’ll see fewer corporate buses on 101.  Rents will come down a bit, so I’d wait before signing a five-year lease on your next building.

3. Porter’s Five Forces comes back in style.  I always feel that during bubbles the first thing to go is Porter five force analysis.  What are there barriers to entry on a daily deal or on a check-in feature?  What are the switching costs of going from Feedly to Flipboard?  What are the substitutes for home-delivered meal service?   In saner times, people take a hard look at these questions and don’t simply assume that every market is a greenfield market share grab and that market share itself constitutes a switching cost (as it does only in companies with real network effects).

porters-five-forces

4.  Cyber-cash makes a rise.  As the world becomes increasingly cashless (e.g., Sweden), governments will prosper as law enforcement and taxation bodies benefit, but citizens will increasingly start to sometimes want the anonymity of cash.  (Recall with irony that anonymity helped make pornography the first “killer app” of the Internet.  I suspect today’s closet porn fans would prefer the anonymity of cash in a bookshop to the permanent history they’d leave behind on Netflix or other sites — and this is not to mention the blackmailing that followed the data release in the Ashley Madison hack.)  For these reasons and others, I think people will increasingly realize that in a world where everything is tracked by default, that the anonymity of some form of cyber-cash will sometimes be desired.  Bitcoin currently fails the grade because people don’t want a floating (highly volatile) currency; they simply want an anonymous, digital form of cash.

5.  The Internet of Things (IoT) starts its descent into what Gartner calls the Trough of Disillusionment.  This is not to say that IoT is a bad thing in any way — it will transform many industries including agriculture, manufacturing, energy, healthcare, and transportation.  It is simply to say that Silicon Valley follows a predictable hype cycle and that IoT hit the peak in 2015 and will move from the over-hyped yet very real phase and slide down to the trough of disillusionment.  Drones are following along right behind.

6.  Data science continues to rise as a profession.  23 schools now offer a master’s program in data science.  As a hot new field, a formal degree won’t be required as long as you have the requisite chops, so many people will enter data science they way I entered computer science — with skills, but not a formal degree. See this post about a UC Berkeley data science drop-out who describes why he dropped the program and how he’s acquiring requisite knowledge through alternative means, including the Khan Academy.  Galvanize (which acquired data-science bootcamp provider Zipfian Academy) has now graduated over 200 students.   Apologies for covering this trend literally every year, but I continue to believe that “data science” is the new “plastics” for those who recall the scene from The Graduate.

the-graduate-plastics
7. SAP realizes it’s an complex, enterprise applications company.  Over the past half decade, SAP has put a lot of energy into what I consider strategic distractions, like (1) entering the DBMS market via the Sybase acquisition, (2) putting a huge emphasis on their column-oriented, in-memory database, Hana, (3) running a product branding strategy that conflates Hana with cloud, and (4) running a corporate branding strategy that attempts to synonymize SAP with simple.
SAP_logo

Some of these initiatives are interesting and featured advanced technology (e.g., Hana).  Some of them are confusing (e.g., having Hana mean in-memory, column-oriented database and cloud platform at the same time).  Some of them are downright silly.  SAP.  Simple.  Really?

While I admire SAP for their execution commitment  — SAP is clearly a company that knows how to put wood behind an arrow — I think their choice of strategies has been weak, in cases backwards looking (e.g., Hana as opposed to just using a NoSQL store),  and out of touch with the reality of their products and their customers.

The world’s leader in enterprise software applications that deal with immense complexity should focus on building upon that strength.  SAP’s customers bought enterprise applications to handle very complex problems.  SAP should embrace this.  The message should be:  We Master the Complex, not Run Simple.  I believe SAP will wake up to this in 2016.

Aside:  see the Oracle ad below for the backfire potential inherent in messaging too far afield from your reality.

 

powered by oracle

8.  Oracle’s cloud strategy gets revealed:  we’ll sell you any deployment model you like (regardless of whether we have it) as long as your yearly bill goes up.  I saw a cartoon recently circulated on Twitter which depicted the org charts of various tech megavendors and, quite tellingly, depicted Oracle’s as this:

oracle-org-chart-300x195

Oracle is increasingly becoming a compliance company more than anything else.  What’s more, despite their size and power, Oracle is not doing particularly well financially.  Per a 12/17/15 research note from JMP,

  • Oracle has missed revenue estimates for four quarters in a row.
  • Oracle provided weak, below-expectations guidance on its most recent earnings call for EPS, cloud revenue, and total revenue.
  • “While the bull case is that the cloud business is accelerating dramatically, we remain concerned because the cloud represented only 7% of total revenue in F2Q16 and we worry the core database
    and middleware business (which represents about half of Oracle’s revenue) will face increasing competition from Amazon Web Services.”

While Oracle’s cloud marketing has been strong, the reality is that cloud represents only 7% of Oracle’s total revenue and that is after Oracle has presumably done everything they can to “juice” it, for example, by bundling cloud into deals where, I’ve heard, customers don’t even necessarily know they’ve purchased it.

So while Oracle does a good job of bluffing cloud, the reality is that Oracle is very much trapped in the Innovator’s Dilemma, addicted to a huge stream of maintenance revenue which they are afraid to cannibalize, and denying customers one of the key benefits of cloud computing:  lower total cost of ownership.  That’s not to mention they are stuck with a bad hardware business (which again missed revenues) and are under attack by cloud application and platform vendors, new competitors like Amazon, and at their very core by next-generation NoSQL database systems.  It almost makes you feel bad for Larry Ellison.  Almost.

8.  Accounting irregularities are discovered at one or more unicorns.  In 2015 many people started to think of late-stage megarounds as “private IPOs.”  In one sense that was the correct:  the size of the rounds and the valuations were very much in line with previous IPO norms.  However, there was one big difference:  they were like private IPOs — but without all the scrutiny.  Put differently, they were like an IPO, but without a few million dollars in extra accounting work and without more people pouring over the numbers.  Bill Gurley did a great post on this:  Investors Beware:  Today’s $100M+ Late-Stage Private Rounds are Very Different from an IPO.  I believe this lack of scrutiny, combined with some people’s hubris and an overall frothy environment, will lead to the discovery of one or more major accounting irregularity episodes at unicorn companies in 2016.  Turns out the world was better off with a lower IPO bar after all.

9. Startup workers get disappointed on exits, resulting in lawsuits.  Many startup employees work long hours predicated on making big money from a possible downstream IPO.  This has been the model in Silicon Valley for a long time:  give up the paycheck and the perks of a big company in exchange for sleeves-up work and a chance to make big money on stock options at a startup.  However, two things have changed:  (1) dilution has increased because companies are raising more capital than ever and (2) “vanity rounds” are being done that maximize valuation at the expense of terms that are bad for the common shareholder (e.g., ratchets, multiple liquidation preferences).

In extreme cases this can wipe out the value of the common stock.  In other cases it can turn “house money” into “car money” upon what appears to be a successful exit.  Bloomberg recently covered this in a story called Big IPO, Tiny Payout about Box and the New York Times in a story about Good Technology’s sale to BlackBerry, where the preferred stock ended up 7x more valuable than the common.  When such large disparities occur between the common and the preferred, lawsuits are a likely result.

good

Many employees will find themselves wondering why they celebrated those unicorn rounds in the first place.

10.  The first cloud EPM S-1 gets filed.  I won’t say here who I think will file first, why they might do so, and what the pros and cons of filing first may be, but I will predict that in 2016 the first S-1 gets filed for a cloud EPM vendor.  I have always believed that cloud EPM is a great category and one that will result in multiple IPOs — so I don’t believe the first filing will be the last.  It will be fun to watch this trend and get a look at real numbers, as opposed to some of the hype that gets circulated.

11.  Bonus:  2016 proves to be a great year for Host Analytics.  Finally, I feel great about the future for Host Analytics and believe that 2016 will be a wonderful year for the company.  We have strong products. We have amazing customers.  We have built the best team in EPM.  We have built a strong partner network.  We have great core applications and exciting, powerful new capabilities in modeling. I believe we have, overall, the best, most complete offering in cloud EPM.

Thanks for your support in 2015 and I look forward to delivering a great 2016 for our customers, our partners, our investors, and our team.

# # #

Footnotes

[1]  These predictions are offered in the spirit of fun and I have no liability to anyone acting or not acting on the content herein.  I am not an oracle, soothsayer, or prophet and make no claim to be.  Please enjoy these predictions, please let them provoke your thoughts, but do not use them as investing or business consulting advice.  See my FAQ for additional disclaimers.

Kellblog Ten Predictions for 2015

As we move into the third week of January, I figured it was “now or never” in terms of getting a set of predictions out for 2015.  Before jumping into that, let’s take a quick review of how I did with my 2014 predictions and do some self-grading.

  1. 2014 to be a good year in Silicon Valley.  Correct.
  2. Cloud computing will continue to explode.  Correct.
  3. Big data hype will peak. Gartner seems to agree, placing it in August midway past peak on the way to trough of disillusionment. Correct.
  4. The market will be unable to supply enough data science talent. Mashable is now calling data scientist 2015’s hottest professionPer McKinsey, this is a problem that’s going to continue for the next several years. Correct.
  5. Privacy will remain center stage.  Correct.
  6. Mobile will continue to drive both consumer and (select) enterprise. I got the spirit correct on this one, but I think the core problem is probably better thought of as multi-device access to cloud data than mobile per se.  That is, it’s not about using Evernote on my phone, but instead about uniform access to my cloud-based notes from all my mobile (and non-mobile) devices. Basically, correct.
  7. Social becomes a feature, not an app. Correct again.  The struggles of companies like Jive only validate that (enterprise) social should be a feature of virtually all apps, and not a category unto itself.
  8. SAP’s HANA strategy actually works. Well SAP didn’t seem to agree with this one, when Hasso Plattner wrote a post blasting customers for not understanding its business benefits.  But my angle was more – the merits of the strategy aside – when a company the size of SAP shows total commitment to a strategy it’s going to get results.  And it has.  And SAP continues to drive it.  Mostly correct.
  9. Good Data goes public. While this didn’t happen, I continue to believe that Good Data has a smart strategy and a solid product.  They raised $25M in September.  Maybe this year they will make me an honest man.
  10. Adaptive Planning (now, Adaptive Insights) gets acquired by NetSuite. This didn’t happen, either.  The prediction was based on the fairly well known play of OEM-ing something before acquiring it.  Time may well prove me right on this one, but a swing-and-a-miss for 2014.

Our “bonus” prediction last year was that my company, Host Analytics, would have a great year and indeed we did.  We grew new subscriptions well in excess of 100%, making us, I believe, the fastest growing company in the category.  We launched a new sales planning solution as part of our vision to unite financial and operational planning.  We hired scores of great new people to join us on our mission to create a great EPM company, one that transforms how enterprises manage their financial performance.  And we raised $25M in venture capital to boot.

So, all in all, for the 2014 predictions, let’s call it 8.5 out of 11.

Here are my predictions for 2015.

  1. The good times continue to roll in Silicon Valley. If you feel “bubble,” remember that unlike in the dot-com days that most companies experiencing great success today have real, often recurring, revenue and real customers.   From a cycle perspective, to the extent there is a bubble coming, I’d say we’re in 1999 not 2001.
  1. The IPO as a down-round trend continues. One of the odder things about this time period is that I’m repeatedly hearing that successful IPO companies are pricing at down-rounds relative to their last private financings.  This doesn’t spell danger in general – because the public market valuations are both healthy and supportable – it just suggests a highly competitive later-stage private financing market is overbidding prices.  I suspect that will calm down in 2015 but down-round IPOs will continue in 2015.
  1. The curse of the megaround will strike many companies and CEOs. As part of the prior bullet companies are now often able to raise unprecedented amounts of capital at high valuations.  While those companies today may celebrate their $100M, $150M or $200M+ financing rounds, tomorrow they will wake up with a hangover that looks like:  huge pressure to invest that money for growth, even in dubious growth opportunities; anxious board members who need a 3x return in three years atop already stratospheric valuations; companies missing plan when the dubious growth opportunities don’t deliver; and CEOs who get replaced for missing plans that were unrealistic in the first place.  Before you take a megaround, be careful what you wish for — you sometimes get it.
  1. Cloud disruption continues. Megavendors will continue to wrestle cloud disruption and their cloud strategies.    They will continue to talk about success and high growth in the 10% or less of their business that is cloud, while asking investors to ignore the lack of health in the 90% that is non-cloud.  As part of a general Innovator’s Dilemma problem, they will be forced to explain and defend cloud strategies that will hopefully help them long term but depress results in the short term (as SAP had to do last week.)
  1. Privacy becomes a huge issue. People who were once too busy to care when Facebook changed their security setting are now asking who can access what and how.  The Internet of Things will only exacerbate this focus as more data than ever will be available.  In the past, you could see my pictures and status updates.  Now you can know where I am, when, how many hours I sleep at night, when I exercised, what temperature I set my thermostat to, and when I’m home.  The more data that becomes available, and the more readily you can be de-anonymized, the more you will start monitoring your privacy settings and previously unread site terms and conditions.
  1. Next-generation apps continue to explode. Apps like Slack and Zenefits will continue to redefine enterprise software.  While Slack is a technology, design, and integration play in the collaboration space, Zenefits is more of a business-model disruption play (i.e., give us the rather large commissions you rather invisibly paid your health insurance broker and we’ll give you free, high-quality HR software).  Either way, consumerization, design, and the search for new business models / revenue opportunities will continue.
  1. IBM software rebounds. IBM used to be a stronger player in software than it is today (e.g., recall that they invented the relational database). Watson aside, things have been pretty quiet on the IBM software front. Cloud-wise, while they claim to have a $7B business, it’s pretty invisible to me, and it does seem that Amazon has beaten them in low-level categories like IaaS.  While I’m not sure what happened – I don’t track them that closely – they do seem to have just faded away.  Once thing’s for sure – it can’t continue.  While there are contradicting stories in recent press, IBM does appear to be in the midst of a large re-organization, and I’m going to bet that, as a result, they come to market with a stronger software and cloud story.
  1. Angel investing slows. Much has been written about the financing chokepoint where tens of thousands of angels are funding companies that then need to get in line to get funded by the approximately 100 or so VCs who do A rounds.  The first-order result is that many companies think “wow this is easy” on raising a angel round only to die 12-18 month later when they fail to raise VC.  The second-order result, which I think will start kicking in this year, is that angel money will be harder to come by as the system corrects back to a balanced state.
  1. The data scientist shortage continues. With more “big data” and a huge supply of analytic tools and computing power, the limiting factor on analysis-driven business is neither data nor technology.  It’s our ability to find people who can correctly leverage it.  Tell every college kid you know to take lots of stats, analytics, and computing classes.  Or better yet, to go get a degree in data science.
  1. The unification of planning becomes the top meme in enterprise performance management (EPM). EPM has a long history of helping finance departments prepare annual operating budgets and financial reports, but increasingly—in recent years – planning has quietly decentralized to the various departments and divisions within the enterprise.  For example, sales ops increasingly builds the sales plan, marketing ops the marketing plan, and services ops the consulting and professional services plan.   (This is why I sometimes call this trend the “rise of the ops person” as they are increasingly acting as stealth FP&A.)  What’s needed is to unite all these plans and put them on a common planning framework so the CFO and CEO can do what-if analysis and scenario planning holistically across the organization.