Interview by SandHill.com on Big Data, Cloud Computing, and the Future of IT

Posted on August 19, 2011 | 1 Comment

[This is a re-post of a recent interview with me, authored by Darren Cunningham of Informatica.  The post originally appeared on SandHill.com where Darren writes a column on Cloud Computing.]

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The Cloud in Action

Big Data, Cloud Computing and Industry Perspectives with Dave Kellogg

BY Darren Cunningham

I had the pleasure of working with Dave Kellogg early in my marketing career and continue to learn from him as a regular subscriber to his popular blog, Kellblog. A seasoned Silicon Valley executive, Dave has been a board member (Aster Data), CEO (MarkLogic), CMO (Business Objects) and VP of Marketing (Versant and Ingres). I recently sat down with Dave to discuss industry trends. As always, he didn’t hold back.

Dave, you’ve written a lot about “Big Data” on your blog. Why is it such a hot topic in the world of data management?

First I think Big Data is a hot topic because it represents the first time in about 30 years that people are rethinking databases. Literally, since about 1980 people haven’t had to think much about databases. If you were an SMB, you went SQL server; if you were enterprise, you’d go Oracle or IBM depending on your enterprise preferences. But in terms of technology, to paraphrase Henry Ford: any color you want, as long it’s relational.

Overall, I think Big Data is hot for three reasons:

  • Major new innovation is finally happening with databases for the first time in three decades.
  • Hardware architectures have changed — people want to scale horizontally like Google.
  • We are experiencing a serious explosion in the amount of data people are analyzing and managing. Machine-generated data, the exhaust of the Web, is driving a lot of it.

I think Big Data is challenging on many fronts from the cool (e.g., analytics and query optimization), to the practical (e.g., horizontal scaling), to the mundane (e.g., backup and recovery).

What’s the intersection with Cloud Computing?

I think when people say cloud computing, they mean one of several things:

  • SaaS: The use of software applications or platforms as services.
  • Dynamic scaling: My favorite example of this is Britain’s Got Talent, which uses Cassandra. Most of the time they have nothing to do. Then one night half the country is trying to vote for their favorite contestants.
  • Service orientation: The ability to weave together applications by calling various cloud services — in effect using a series of cloud services as a platform on which to build applications.

I think Big Data intersects with cloud in several ways. First, the people running cloud services are dealing with Big Data problems. They are hosting thousands of customers’ databases and generating log records from hundreds of thousands of users. I also think Big Data analytics are very dynamic loads. One minute you want nothing, then suddenly you need to throw 100 servers at a complex problem for several hours.

How do you see these trends changing the role of IT?

I think corporate IT is constantly evolving because smart corporations want their internal resources focused on activities that they can’t buy elsewhere and that generate competitive advantage for the business.

IT used to buy and run computers. Then they used to build and run applications. Then they focused on weaving together packaged applications. Going forward, they will focus on tightly integrating cloud-based services. They will also continue to focus on company-proprietary analytics used to gain competitive advantage.

The other trend driving IT is consumerization. The Web sets expectations for functionality, user interface and quality that corporate IT must meet with internal systems. The bar has gone way up – people won’t tolerate old-school ERP-style interfaces at work when they’re used to Facebook or Yelp.

What does that mean for technology sales and marketing?

If Mr. McGuire in The Graduate were dishing out advice today, instead of saying “plastics,” he’d say “data science.” More and more companies will use data scientists to analyze their business and drive tactical operations. First you need to gather a whole bunch of data about your operations and customers. Then you need to throw world-class data analysts at it to get business value and to be sure you don’t draw false conclusions – e.g., mixing causality with correlation.

Today, most companies have their sales departments on salesforce.com. Leading marketing departments are on Marketo or Eloqua, but most marketers still don’t have much technology backing them. Going forward you will see a whole class of analytics applications vendors providing advanced analytics for Salesforce (e.g., Cloud9, Good Data) and the marketing automation vendors will move beyond lead incubation into providing overall marketing suites. I expect Marekto or Eloqua to try to do for the chief marketing officer what SuccessFactors did for the chief people officer – and if they don’t, then there’s a real opportunity for someone else.

Speaking of all things cloud, you often write about Silicon Valley trends. How would you characterize what’s going on in the market right now?

From my perception, the Silicon Valley innovation engine is running full out. Top VCs are raising new funds. I meet a few new startups every day. Of late, I’ve met fascinating companies in next-generation business intelligence, analytics, Big Data, social media monitoring and exploitation and Web application development. One of the more interesting things I’ve found is a VC fund dedicated to big data - IA Ventures (in New York). When I heard about them, I thought: oh, lots of Big Data infrastructure and platform technologies. Then I spent some time and realized that most of their portfolio is about exploiting new Big Data infrastructure technologies via vertical applications. That was really interesting.

People will debate whether we’re in a mini tech bubble or a social networking-specific bubble. Who knows? I just read an article in the The Wall Street Journal that argues $140B valuation for Facebook is realistic, and it was fairly convincing. So you can debate the bubble issue but you can’t debate that the IPO market has been closed for a long time. Now it is starting to open, and that’s a huge change in Silicon Valley.

Entrepreneurs have historically dreamed of creating $1B independent companies. I’d say for most of the last decade they’ve dreamed of getting bought for 5-10x revenues. Michael Arrington had a great quote a while back saying that “an entire generation of entrepreneurs [has been lost] building dipshit companies that sell to Google for $25M.” I think those days are over. When the IPO window opens, people dream of building stand-alone companies.

What advice do you have for both entrepreneurs and IT veterans?

Don’t build or run things that you can buy or rent. If you follow that mantra, you will follow market trends, and always stay at the right stack-layer to ensure that you are adding value as opposed to leveraging old skill sets. While you may know how to run a Big Data center, you can now rent time in one more cost-effectively. So either go work for a company that runs data centers (e.g., Equinix) if that’s your pleasure, or go leverage the people who do. Put differently, don’t be static. If you’re still using skills you learned 10 years ago, make sure that you’re not teeing yourself up to get left behind.

As always, great advice, Dave! Thank you.

Darren Cunningham is VP of Marketing for Informatica Cloud.

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[Notes:  Minor changes made from the SandHill post.  I added emphasis via bolding and I corrected the attribution of the famous lines "plastics" from The Graduate.  It was not Mr. Robinson, but Mr. McGuire, who said it.]

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Posted in Big Data, cloud computing, Information technology, Initial public offering, Innovation, IPO, NoSQL, Uncategorized, Venture Capital

HP Rumored To Be Buying UK’s Autonomy for $10.2B

Posted on August 18, 2011 | 7 Comments

Just a quick post to share the widely published rumors that HP is in discussions with Autonomy over an acquisition estimated to be about $10B.

Some quick thoughts on this:

  • It’s a great deal for Autonomy, price-wise.  Today’s market cap was £3.5B or $5.8B so it seems to represent a 71% premium to the market, if I’m doing the math correctly.  2Q11 revenues were $256M, so call it a $1B run-rate, which means the deal is proposed at 10x run-rate revenues.  That’s expensive for a company growing revenue at 16% year/year, but then again, Autonomy is very profitable with 45% operating margins, and they say that 62% of IDOL revenues are now done on a recurring model.  (Note:  recent Iron Mountain deal included in these numbers on a stub period basis only.)
  • Ever since Autonomy bought Verity, I have viewed them as a finance company dressed in (meaning-based) technology company clothing.  This seems a happy ending for that finance company.
  • Autonomy the finance company may have been running out of companies to buy on their buy-cheap and crank-the-recurring revenues model that worked so well for Verity, Zantaz, and probably the Interwoven acquisitions.  (It takes a pretty specific profile to make that strategy work:  big installed base, recurring revenue model, and a cheap stock price.)  To me, Autonomy seemed all dressed up with nowhere to go.  They sold about $800M worth of bonds in February, 2010, presumably to make a big acquisition and then did little or nothing until paying $380M for Iron Mountain’s digital assets in March, 2011.
  • HP wants to get more into the software business and, given the massive consolidation of the past decade, there aren’t that many $1B companies to buy.  At some point, they will probably acquire a mega-vendor (e.g., SAP), but the Autonomy deal might be a nice warm-up to that.
  • Autonomy stock was nevertheless off 8% on the day.

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Posted in autonomy, HP

Highlights from the Fenwick & West 2Q11 Venture Capital Survey

Posted on August 17, 2011 | Leave a comment

Each quarter the legal eagles at Fenwick & West run a great survey on the state of venture capital and write a brief report that rounds-up data from other sources and publishes their survey results.  Here are some quick highlights from the 2Q11 venture capital survey:

  • Total VC investment was $8.0B, a 20% increase compared to the $6.4B invested in 1Q11 per VentureSource.  Of this, $2.9B was invested in Silicon Valley.
  • 14 venture-backed companies went public in 2Q11, raising $1.7B.  In 1Q11 11 companies went public raising $700M, per VentureSource.
  • Venture capitalists raised $2.7B in funding in 2Q11, a 65% decline relative to the $7.6B raised in 1Q11, per Thompson/NCVA.
  • The Silicon Valley Venture Capitalist Confidence Index dropped to 3.66 out of 5.0, a sharp drop from the 3.91 recorded in 1Q11.  I added the red line to chart below which seems to indicate that confidence is about average since 1Q04.

  • 19% of financing rounds were series A, about normal for the past two years, somewhat contradicting the analysis in this recent TechCrunch story, The Series A Squeeze.  (Though it’s unclear how Fenwick handles seed fundings in their study.)
  • 61% of financing rounds were up-rounds, 14% were flat, and 25% were down.
  • The Fenwick & West VC Barometer, a measure of per-share pricing, was up 71%, with the software sector leading the way at 123% and internet / digital media at 115%.
  • 37% of rounds included senior liquidation preferences and, of those, 29% were multiple liquidation preferences.
  • 38% of rounds had participating preferences.
The full survey is available here.

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Posted in startups, Venture Capital

A Note to the Results-Oriented: Just Be Nice

Posted on August 12, 2011 | 3 Comments

The situation was clear.  The company had just brought in a new COO.  That person was band-leader, intent on bringing a slew of folks from his last company. My friend Pete, who worked for the new COO, had strong track record of delivering results, but the internal rap on him — in a full 360 sense — was mixed.

“How goes, Pete?” I said a few days into the transition.

“Pretty good, I think the new guy’s going to give me a chance.”

“Really?  I’m not so sure.”  Digging up one of my favorite corporate analogies  from The Sixth Sense, I say:  ”Pete, I’ve got to be honest.  I see dead people.  They … don’t … know … they’re dead.”

Normally, I’m open minded in such situations, but this time the data was clear. Someone needed to get through Pete’s optimistic head that he was dead.  No way, no how, you are going to survive this one.  Sorry.

It took about half an hour, but at some point it clicked.  ”Wow, there really is no way.  Shit.  Well, then, what do I do now?“

“I don’t know,” I said.  It hadn’t actually occurred to me that I might succeed in the primary mission and then have to offer advice on what to do next.

“Let’s think about it,” I said.  ”First, you need to keep delivering on your goals, so you can go out on top.  Second, you need to fire up a search process in the background — start taking calls.  Third, you need to recognize that there is only thing you want from every person in this building:  a positive reference.  So, to help ensure that, just be nice to everyone because you never know who they’re going to call.”

Pete found a great new job and continued his successful career.  A few years later we found ourselves having a beer.

“Dave, you remember when you told me to just be nice?”

“Yes, I do.”

“First, thank you because it was great advice for that situation.  I did need to focus 100% on ensuring that my internal relationships would give me strong references.  But you know what?  A funny thing happened.  We did end up delivering strong results during that transition period but I think the focus on being nice made me a much more effective manager as well.”

I love this story because successful business people are results-oriented.  That’s what we do.  Deliver results.  But sometimes the results-oriented among us can lose sight of the bigger picture of people and relationships.  Must we frame things as people-people vs. results-people or can we strive to be both?

I’ve never found a starker exercise to demonstrate this than Pete’s.  Assume you be fired in six months.  How would you think about your colleagues?  How would you change your behavior?

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Posted in management

Twelve Questions Executives Can Ask To Improve Decision Making

Posted on August 2, 2011 | Leave a comment

I first became interested in decision making more than a decade ago, back when I was running marketing at Business Objects.  My interest was prompted by the evolution of taglines among BI vendors.  In the early days, taglines were descriptive like First in Enterprise Decision Support or The Enterprise Data Mart Company.

Over time, pressure mounted on marketing to pitch benefits — the message shouldn’t just be about getting people information, but the benefit of having it.  Slogans evolved accordingly:  Now You Know, The Power To Know, and Business Intelligence:  If You Have It, You Know.

But was knowing enough of a benefit?  You could certainly take it up a level, and Cognos did:  Better Decisions Every Day.  For a marketing slogan it was good enough, but was it true?   Did providing better access to corporate information  invariably improve decision making?  It seemed like a leap so I decided to research it.

I’ll never forget when Cornell professor Jay Russo told me, “the primary use of new information is selective filtering to justify previously established conclusions.”  So, despite the commonsense appeal of the Cognos tagline, you most certainly could not draw a straight line from “more information” to “better decisions.”

I studied how individuals and groups  made decisions.  I read interesting books like Russo’s Decision Traps (later positively reframed into Winning Decisions) and Smart Choices.  Years later I became interested in mass decision making  in The Wisdom of Crowds and behavioral economics in Predictably Irrational and Why Smart People Make Big Money Mistakes.

I remember asking Russo why decision making wasn’t more of a focus in business schools.  His answer came down to two things:

  • If you can’t measure it, you can’t manage it.  Until corporations want to start measuring decision making, you can’t focus on improving it.  (I remember once suggesting a BI product that tracked votes on strategic decisions, evaluated their success years later, and calculated batting averages for team members.  The idea was shot down as my colleagues imagined executives fleeing like cockroaches under an illuminated light.)
  • Executives perceive their jobs as decision-making and themselves as experts.  Think:  Why would I need a class in decision making?  I make decisions for a living and my success in rising up this organization is proof that I am good at it.

But if quenching thirst is the ultimate benefit of Coke, improved decision making really is the ultimate benefit sought by BI consumers.  The problem was  – and is — that BI software can’t deliver it.

So if you want to improve your decision making, then you’re going to have to read up a bit, either through the books I’ve referenced above or via a recent article in Harvard Business Review entitled Before You Make That Big Decision, which provides 12 questions that senior executives can ask about decisions and decision-making processes to avoid the most common errors.

Here are those 12 questions and the biases that they are trying to detect:

  1. Is there any reason to suspect motivated errors, or errors driven by the self-interest of the recommending team?  (self-interest bias)
  2. Have the people making the recommendation fallen in love with it?  (affect heuristic)
  3. Were there dissenting opinions within the recommending team?  (groupthink)
  4. Could the diagnosis of the situation be overly influenced by salient analogies?  (saliency bias)
  5. Have credible alternatives been considered?  (confirmation bias)
  6. If you had to make this decision again in a year, what information would you want and can you get more of it now?  (availability bias)
  7. Do you know where the numbers came from?  (anchoring bias)
  8. Can you see a halo effect? (halo effect)
  9. Are the people making the recommendation overly attached to past decisions?  (sunk-cost fallacy, endowment effect)
  10. Is the base case overly optimistic?  (overconfidence)
  11. Is the worst case bad enough?  (disaster neglect)
  12. Is the recommending team overly cautious?  (loss aversion)
The full article is here.

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Posted in business intelligence, decision making, management

Bobby Fischer Applied to Silicon Valley: Pattern Matching vs. Good Moves

Posted on July 26, 2011 | 4 Comments

When asked why he won so many matches, chess grandmaster Bobby Fischer would reply:  ”all that matters on the chessboard is good moves.”

That is, winning is all about the moves.  And moves, in turn, are all about the situation.  Contrast this to today’s Silicon Valley fashion of “pattern matching” which seems the opposite — all about the players and not so much about the moves.

Consider Blippy, a bad idea if there ever was one, which created a $13M VC sinkhole for a service to share credit card receipts on your social network.  Let’s look at the founders:  two recent Stanford engineering grads and an experienced entrepreneur, Philip Kaplan (most famous for bubble-era website,  F**kedCompany).

How about Cuil?  (Pronounced coo-il.)  Cuil launched in July, 2008 claiming to be the next Google with superior indexing and operational cost advantages.  It seemed clear to me (and the world) that from the start, Cuil wasn’t any better than Google.  They burned $33M in VC and entered theTechCrunch deadpool in Sept, 2010.  Let’s look at the founders:  three ex-Google engineers, two of them PhDs and one from Stanford.

When pattern matching is the rage, when the moves are so obviously bad, and when the players so clearly match the pattern, I’d argue that Blippy and Cuil broke Fischer’s law.  They weren’t about the moves; they were about the players.

I used to joke that if you wanted to raise money in Silicon Valley you should be aware that VCs see people in one of four buckets:

  1. Made me money before.
  2. Made someone money before.
  3. Went to Stanford
  4. Everybody else

Now, make no mistake, the team is has always been a key factor in venture capital investment.  But I think the historical approach was to see the team as de-risking element for the idea.  Put differently, we are investing in a market opportunity and we would like to isolate as much risk as possible to the market opportunity.  How do we do that?  By getting an experienced executive team to reduce execution risk, by hiring experienced engineers to reduce product development risk, etc.  That is, as VC founding father Don Valentine used to say, “great markets make great companies.”

(Asides:  [1] Irony alert in the above video where Don tells a bunch of Stanford graduate students it doesn’t matter where they go to school and [2] note further that Valentine was a pithy quote machine, coming up with such classics as “I am 100% behind my CEOs up until the minute I fire them” and “all companies that go out of business do so for the same reason – they run out of money.”)

Somehow I wonder if things haven’t gotten upside-down of late:  where the players matter more than the moves.  I’d argue that Silicon Valley used to be about the moves (the strategy and market opportunity) and VCs sought experienced players as a risk reduction technique.  Now, it appears to be about the players and the implicit assumption that those who match the player-pattern can win any match, regardless of the moves.

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Posted in strategy, Venture Capital

Some Fun Analysis with Indeed.com Job Trend Mapping

Posted on July 24, 2011 | 5 Comments

Indeed.com, an up-and-coming job search website, has an interesting trends search feature.  Because you easily argue that the rational side of Silicon Valley hype waves is driven by jobs/employment, one great way to analyze these technology waves is to analyze job postings.  Let’s have some fun.

First, let’s look at some web application development technologies:

Note how HTML5 (in yellow) is flying up the rankings. Now, let’s take a look in database-land.

Now, let’s take a look in NoSQL land.

I’m not surprised to see MongoDB and Hadoop shooting up the charts.  Frankly, I thought Cassandra had lost some momentum, but I guess not.  Finally, let’s take a look in semantic web-land.

I don’t actually view XQuery as a semantic web technology — I just threw it in for fun — and was surprised to see that XQuery generally correlates better with semantic web than actual semantic web technologies like RDF or OWL!

Finally, note that the scales are not the same.  The first two charts are in percent of job postings, the third is in tenths of a percent, and the fourth is in hundredths of a percent.  So the sobering example is to take the top trend from each of our four charts and graph them together.

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Posted in Uncategorized

Marketing Vision While Selling Product: The 3+1 Repositioning

Posted on July 15, 2011 | 1 Comment

This post was inspired by a recent beer with long-term colleague, friend, and fellow volleyball dad, Paul Albright, now chief revenue officer at Marketo.

The question we discussed was how can a company sell current product capabilities but also market vision at the same?  (For brevity’s sake I mean “product” to include either traditional software products or SaaS / cloud services.)

Most companies simply market their current product capabilities:  Here we are.  This is what we do.  Here are the benefits of using it.  Wanna buy one?

While this isn’t bad — particularly if you don’t forget step 3 (benefits) — you can do better.  How?  Say, for example, your competition sells an offering similar to yours and they sell using a current capabilities patter similar to the one above.  Now you show up selling something bigger:

 This is our current offering and it includes area 1 (which the other guy is pitching), but also areas 2 and 3, and the vision for our company is not just about having the best area 1, but instead to pursue a capstone vision that includes areas 1, 2, and 3.

Ceteris paribus, who do you think wins?  You do.  Why?  Because you completely enveloped the other guy’s message.    You neutralized him on area 1, you one-upped him in areas 2 and 3 (even if your current offering is anemic on an absolute basis), and then you made the customer feel both more aligned with and safer buying from your company because you are pursuing the bigger vision.

I call this a 3+1 repositioning.

I did my first 3+1 repositioning  back in about 1989 when I launched Ingres 6.3.  Prior versions Ingres were just for data management, but with release 6.3 we not only improved data management, but added knowledge management and object management capabilities and introduced the vision of an intelligent database system.  So area 1 = data management, area 2 = knowledge management, area 3 = object management, and the capstone vision was the intelligent database.  While it was a well-executed launch, it was a long time ago, Ingres had many other problems, and the ending wasn’t terribly happy.

So let’s look at some more recent examples.  SuccessFactors (where Albright was CMO and GM for several years) started out as a SaaS provider of performance reviews. How do you broaden that vision?  Well let’s look at what they say now:

Now let’s take a look at Marketo, a firm that I have traditionally thought of as about lead nurturing and incubation.

The magic of the 3+1 repositioning is:

  • It paints a broader vision, enveloping your competition
  • It provides a simple, memorable three-point message.  (Heck, I launched Ingres 6.3 more than 20 years ago and still remember the message!)
  • It lets you call higher, getting access to more power within the organization
  • It positions your company as a thought leader, someone defining the future of the market
  • It takes for granted your ability to neutralize any features du  jour in the core area.  (Oh, yes, we’re committed to having top-end lead management, but that’s just one part of the picture.)
  • It rallies your company, providing a North star towards which everyone can navigate.

The perils of a 3+1 repositioning are:

  • It can’t be done solely are a marketing exercise; it must be a company strategy and some resources must be invested in areas 2 and 3.
  • You can easily oversell areas 2 and 3, ending up with disappointed customers.  Remember the bear joke:  you just need to run faster than the other guy, so don’t overset expectations.
  • It can make your accountants nervous because there is a distinction between buying today’s product and buying into a (disclaimed) future vision and buying tomorrow’s product.  The latter tends to have negative revenue recognition issues.

In the end, I am a big fan of this 3+1 formula and encourage marketers everywhere to keep it in your toolbox.

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Posted in Marketing, strategy

The Silicon Valley Strategic “Pivot”

Posted on July 13, 2011 | 6 Comments

The first time I heard the word “pivot” in the context of business strategy was about nine months ago.  As a student of language, my ears perked up when I heard it.  I remember thinking, “pivot … interesting, haven’t heard that one before, … strong buzzword potential, … nice metaphor, with one foot stationary and the other moving.”

Silicon Valley being Silicon Valley, with more fashion around language than clothing, today you hear it all the time.  Some sample usage:

  • “Yeah, dude, we had to pivot after our A-round, but after that we really got traction.”
  • “I think you know like, we’re running on our 401k round, just trying to figure out the core product, then we’ll expose it to the market, through a pre-alpha and pivot from there.”
  • “Like, you know, every startup needs to  pivot like two or three times before locking-in on its final strategy.  That’s the nature of innovation.”

Extending the metaphor, one wonders in the last example if your board can call the CEO for strategic traveling.  

Despite my general buzzword aversion, I like the pivot metaphor precisely because one foot is stationary.  A complete strategy change is therefore not a pivot but a traveling violation because you entirely abandon the old strategy as opposed to changing direction in a way that leaves one foot in the old strategy and one foot in the new.

I also like the pivot metaphor because I agree with the idea that from inception to $100M that a company will need to pivot and probably a few times.  (Think pivoting multiple times in a game, but not on one ball.)  That truly is the nature of innovation and Silicon Valley companies do it all the time.

The two interesting questions then become:

  • How do you know if you’re traveling vs. pivoting?
  • How you know if the pivot worked?

I answer the first question by evaluating the degree of continuity between the old and the new strategy.  I’d evaluate the second question by the revenue and margin contribution of the old strategy vs. the new one.  If the old strategy is driving all the revenue, then you may have pivoted, but it’s not working.  If the new strategy is driving the lion’s share of revenue and margin, then — and only then — have you done a successful pivot.

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Posted in Silicon Valley, strategy

What the CEO Really Thinks of Marketing (And 5 Things You Can Do About It)

Posted on July 12, 2011 | 3 Comments

As a marketing guy turned CEO, I have the relatively rare experience of having seen marketing from inside the organization as well as from above it.  Yesterday, the SV Forum Marketing SIG invited me to give a presentation where I discussed marketing from the CEO’s perspective.

I’ve embedded the slides below for your viewing pleasure.

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Posted in Marketing