Seeing Both Sides of an Issue

The ability to see both sides of an issue is a critical executive skill.  Yet, in typical corporate America culture, that skill is all too often lost.  Why?

  • Things get partisan:  sales wants X, marketing wants Y, finance wants Z.
  • Discussions turn blame-oriented.  Instead of working to solve problems, people work to avoid blame.
  • Managers lose interest in understanding the alternative positions.
  • People don’t listen to each other, often because they’re too busy thinking of what they’re going to say next.  (Resulting in what one friend calls “parallel independent conversations.”)

The solution is to force managers to articulate both sides of important issues.  If a person is advocating thing X instead of thing Y, I want them to be able to clearly and convincing explain the advantages of both.  The best decisions come, in my opinion, when you hold two opposing ideas in your mind at once, and then choose.

When done correctly, you will see:

  • A focus on solutions, not blame.  Example:  “help me understand how you want to solve the problem.”
  • Managers looking forward, not back.  This flows naturally from the prior point.
  • Managers practicing active listening, a great technique for trying to understand the other person’s point of view.  Example:  “so, Ted, you’re telling me that you think we’re doing too many tradeshows that result in poor quality leads — is that correct?”

But seeing both sides of an issue only gets you halfway to your goal.   In many big companies, the unintended dysfunctional consequence of doing so is passivity and fence sitting:

  • Well,we could do A or we could do B.  Frankly, I’m open.
  • The consensus in the meeting was that both A and B were good options.  (This hits my “launch” button!)
  • Well, there are certainly advantages and disadvantages to both options.
  • We should pick the option that keeps the most other options option.  (Also known as The MBA Credo).

Somewhere along the way in corporate America, managers forgot that they are paid to make decisions.  The point of seeing both sides isn’t to avoid decision making.  The point is to make better decisions.

To ensure a focus on decisions, I usually run a line of questioning that starts with the decision and backs up from there.

  • What do you think we should do?  (And push for a single answer)
  • Why do you think we should do it?
  • Why should we do the alternative?

If you’re already performing these techniques, great.  If you’re not, give them a try and let me know how it works.

Beware the Spectacular B-Round Valuation

Visualization tools startup Palantir announced a follow-on financing round yesterday, raising $90M at a claimed $735M valuation.  Since most people aren’t familiar with either finance or VC math, this can generate confusion so I thought I’d do a post explaining a few things.

The first is simple:  do not confuse valuation with revenue.  Valuation (or for public companies, market capitalization) is an implied metric based on per-share price and number of shares outstanding.  For example, a public company with 50M shares and a $20 share price has a valuation of $1B.  That alone says nothing about its revenue.   TechCrunch makes this mistake three times in the story, calling Palantir “the next billion-dollar company” in the headline, saying they’re a “near-billion dollar company” in the middle,  and at the end, saying they are close:

It’s hard to imagine a billion-dollar company without a sales team, but then again Palantir is getting pretty darn close.

This is simply not true.  By my guess, Palantir is doing somewhere between $25M and $50M in GAAP revenues — nowhere near $1B.  Furthermore, while I hate to be technical, I could easily believe they are doing less:  as I understand their model, recognizing GAAP revenues should be a nightmare — e.g., calling all field staff engineers and claiming no services business implies field-based R&D implying the need to defer revenues until product completion for a given customer.

The second confusion is more subtle and relates to a quirk in VC math that makes an early round investor, who believes in the company and has cash to put to work, valuation neutral on subsequent financing rounds.  In fact, you could argue that they’re not valuation neutral, but positively biased because they mark their existing shares to the new valuation when reporting back to their limited partners.

Reminder:  I am no longer talking about Palantir in specific because their capital structure is both private and presumably more complicated than I describe here.  I am trying to show, in general terms, how some quirks result in early-round investors liking higher subsequent-round valuations — even when they’re buying shares at those higher prices.

For a quick primer on VC math and terminology, go here.  Now, let’s examine a spreadsheet I built to concretely demonstrate the mechanics of what I’m talking about.

In my example, a hot company manages to raise a $24M A-round at a pre-money valuation of $36M.  This is unattainable for most entrepreneurs, but let’s say you made a lot of money on your last gig and thus have some friends in the venture capital community who believe in you.  Note that as part of this round, VC1 has invariably negotiated himself the right to avoid dilution in subsequent rounds.  Since he owned 40% of the company after the A-round, he thus has the right to purchase 40% of any new shares sold by the company going forward. This is called exercising his pro rata.

Now it comes time to do the B-round.  Let’s say that things are going well and that the company somehow thinks it should be able to raise $30M at a $180M pre-money valuation. That’s scenario I in my spreadsheet.  Let’s see what happens.  (Click to enlarge.)

  • In the B-round, the company sells 5M new shares at $6/share for $30M.
  • VC1 chooses to fully exercise his pro rata and thus buys 2M shares for $12M.
  • That leaves 3M shares for the new investor, VC2, who pays $18M.

Seems like a pretty good deal, but wait. If you’re executing the go-big-or-go-home strategy which both you and VC1 agree is appropriate, then $30M isn’t enough.  You decide you need $90M.  That’s scenario II in my sheet:

  • You issue 15M shares at $6/share to get $90M.
  • VC1 exercises his pro rata and buys 6M shares for $36M.
  • VC2 buys 9M shares for $54M.

Everybody’s happy, but then you look at founders and employees whose ownership has dropped from 60% before the round to only 40% after.  Most people would call this a 33% dilution (20 divided by 60), though some would call it a 20% dilution (60 minus 40).  Either way, while this scenario raises the money needed, the team loses a lot of ownership in the process and doesn’t like that one bit.

Then, the creative type on the team says: “I can solve the problem.”  See scenario III:

Why sell 15M shares at $6 when we can sell about 4.3M shares at $21 to get the same amount of money?  We’re better off, keeping 52% ownership for ourselves, and the great part is VC1 doesn’t care.  No matter the valuation, if we’re raising $90M and if VC1 is exercising his pro rata, then he’s in for $36M– see the boxed cells on the spreadsheet.  All we need to do is to get together with VC1 and find some dumb money willing to pay $54M for 8% of the company.  There’s plenty of dumb money out there these days and if we can’t get it in one investor, then maybe we can build a little consortium of a few.

And while we might view VC1 as valuation-neutral from one perspective, we shouldn’t forget that he has a boss, too.  He reports back a few times / year to his limited partners.  If we do the deal at $630M pre-money, then he can mark up his A-round shares from $24M to $252M in value, showing a 10x paper return to his investors.

I am not saying this has or has not happened with any given company.  I would like to make the important note that the whole notion of “dumb money” is at odds with free market theory.  I’ll also add that I know some quality VCs advise limited partners to ignore investment marks-to-market, but I doubt they all do.  Nevertheless, I hope this story shows that there’s potentially more than meets the eye in the world of venture financing, driven largely by the dual role (owner and seller) played by the existing VCs and founders/employees.

So what do I think it really means when a company announces a big round at a high valuation?  I think it means that:

  • The company is trying to build and/or sustain a hype bubble and wants to be seen as hot.  Most VC-backed companies do not disclose valuations.
  • The company is executing a “go big or go home” strategy that I’d argue increases the risk for its customers. Remember, Amazon went big.  Webvan went home. See the Fit or Fat Startup Debate launched by Ben Horowitz and countered by Fred Wilson for an examination of such strategies from the VC point of view.  In my estimation, sometimes they produce a great result, often a great crater, and rarely a great business.  Ironically, you can get nice exit valuations off such strategies but not great multiples.
  • The company has a supportive A-round investor willing to invest real money and who believes in the go-big strategy.
  • The company intends to spend the money, either because it must in order to sustain the current burn rate or because it wishes to expand into other areas.  The former signals unsustainable situation, the latter signals a potential loss of focus.
  • If things don’t go as the company plans, the dumb-money will put constant pressure on management to be aggressive, reminding everyone of the expectations they bought into.  This can make it hard to back off and change direction in the event of bumps along the way.
  • The company could have trouble exiting at otherwise reasonable valuations, especially if the dumb-money controls a class of stock.  Think:  “I need at least a 2-3x on this investment.”

Six Thoughts on The NoSQL Movement

We are in the middle of one of our periodic analyst tours at MarkLogic, where we meet about 50 top software industry analysts focused in areas like enterprise search, enterprise content management, and database management systems.  The NoSQL movement was one of four key topics we are covering, and while I’d expected some lively discussions about it, most of the time we have found ourselves educating people about NoSQL.

In this post, I’ll share the six key points we’re making about NoSQL on the tour.

Our first point is that NoSQL systems come in many flavors and it’s not just about key/value stores.  These flavors include:

  • Key/value stores (e.g., Hadoop)
  • Document databases (e.g., MarkLogic, CouchDB)
  • Graph databases (e.g., AllegroGraph)
  • Distributed caching systems (e.g., Memcached)

Our second point is that NoSQL is part of a broader trend in database systems:  specialization.  The jack-of-all-trades relational database (e.g., Oracle, DB2) works reasonably well for a broad range of applications — but it is a master of none.  For any specific application, you can design a specialized DBMS that will outperform Oracle by 10 to 1000 times.  Specialization represents, in aggregate, the biggest threat to the big-three DBMS oligopolists.  Examples of specialized DBMSs include:

  • Streambase, Skyler:  real-time stream processing
  • MarkLogic:  semi-structured data
  • Vertica, Greenplum:  mid-range data warehousing
  • Aster:  large-scale (aka “big data”) analytic data warehousing
  • VoltDB:  high volume transaction processing
  • MATLAB:  scientific data management

Our third point is that NoSQL is largely orthogonal to specialization.  There are specialized NoSQL databases (e.g., MarkLogic) and there are specialized SQL databases (e.g., Aster, Volt).  The only case where I think there are zero examples is general-purpose NoSQL systems.  While I’m sure many of the NoSQL crowd would argue that their systems can do everything, is anyone *really* going to run general ledger or opportunity management on Hadoop?   I don’t think so.

Our fourth point is that NoSQL isn’t about open source.  The software-wants-to-be-free crowd wants to build open source into the definition of NoSQL and I believe that is both incorrect and a mistake.  It’s incorrect because systems like MarkLogic (which uses an XML data model and XQuery) are indisputably NoSQL.  And it’s a mistake because technology movements should be about technology, not business models.  (The open source NoSQL gang can solve its problem simply by affiliating with both the NoSQL technology movement and the open source business model movements.)

As CEO of a company that’s invested a lot of energy in supporting standards, our fifth point was that, rather ironically, most open source NoSQL systems have proprietary interfaces.  People shouldn’t confuse “can access the source code” with “can write applications that call standard interfaces” and ergo can swap components easily.   If you take offense at the word proprietary, that’s fine.  You can call them unique instead.  But the point is an application written on Cassandra is not practically moved to Couch, regardless of whether you can access the source code both Couch and Cassandra.

Our sixth point is that we think MarkLogic provides a best-of-both-worlds option between open source NoSQL systems and traditional DBMSs.  Like open source NoSQL systems, MarkLogic provides shared-nothing clustering on inexpensive hardware, superior support for unstructured data, document-orientation, and high-performance.  But like traditional databases, MarkLogic speaks a high-level query language, implements industry standards, and is commercial-grade, supported software.  This means that customers can scale applications on inexpensive computers and storage, avoid the pains of normalization and joins, have systems that run fast, can be implemented by normal database programmers, and feel safe that their applications are built via a standard query language (XQuery) that is supported by scores of vendors.

Questioning the Tech Wunderkind Image

One of the things that irritates me about Silicon Valley culture is its blatant ageism.  I dislike it for several reasons:

  • Let’s start with the easy one:  it’s illegal.  As an employer you should be looking for someone qualified to do the job, not someone of a specific age.  While certain job requirements may end up setting a de facto lower bound on age (e.g., it’s hard to have a top MBA and 5 years of second-line management experience before you’re 30), age is not something you should talk about in the recruiting or management process.  People who would never say “let’s go find a Baptist to do this job” or “let’s go find a woman” will say things like “let’s go find a 32-year-old,” seemingly unaware it’s the exact same kind of discrimination.
  • In addition to over-promoting the whiz kids, the media almost never does any follow-up, telling us what became of the wunderkinds ten or twenty years later.  That’s why I was surprised to see this story in today’s New York Times, For A Mogul Money and Magic Have Limits, which details the dog’s breakfast whiz kid Halsey Minor has made of things since making a fortune off CNet during the Web 1.0 era.  Find the lessons in this quote:  “he thought he was a billionaire, spending far more than he had … but he really was a multi-millionaire always thinking I’m going to make the big score.”
  • The asymmetric media coverage gives people a distorted sense of reality:  (1) that they must start a company before they’re 30 or they never will, (2) that after 30 they are washed up, (3) that the odds of succeeding in a venture are way higher than they are, (4) that skills are more the determinants of success than luck, and (5) that youth/energy are more important than experience.
  • Point 4 is the Fooled by Randomness effect.  We don’t worship lottery winners, we just consider them lucky.  In business, we tend to equate financial success with skill and further sense that each idiosyncrasy is a cause of success.  If Google has free lunch, we’ll have free lunch.  If Steve Jobs wears jeans and a black t-shirt, then we should wear jeans and black t-shirts.  All notions of luck and causality get confused in the business media.
  • Regarding point 5, I’d like to ask the freshly-minted MBAs in my readership to ask themselves a question:  do you believe that you will be a better manager now or twenty years in the future when you still have the same degrees, the same intelligence, but twenty years of management experience?

But the thing that most amazes me about Silicon Valley ageism is that it’s often practiced by the 40+ crowd.  Here, neither self-interest nor logic prevail, just — I suspect — intellectual laziness.

Marketing Abuse: The Word "Partnership"

Dear Marketer:

I get about 5 of these emails a day.

Subject:  Partnership Proposal-Damco Inc.

Dear Dave,

Hope you are doing great.

Damco has vast experience in providing high quality and cost effective data processing services to its clients globally. Since its inception in 1996, Damco has honed its level of expertise and built robust processes and methodologies ensuring quick turnaround times, confidentiality and data security. Damco’s offshore delivery centres are ISO 9001:2000 and CMMI Level 3 certified and in addition we are fully compliant with BS7799 security standards and Data Protection Act 1998.

Damco has already delivered its data processing services to leading organizations in various industries including – Publishers, Libraries, Law Firms, Insurance Companies, Credit Card Companies, Market Research Companies, Healthcare Providers, Universities, Hospitality, Airlines, Banks, Registration companies, Government.

Highlights of our offerings are:

a) Up to 50% Cost Saving from Outsourcing
b) Domain Experience & Technical Expertise
c) High Quality standards in accordance with ISO 9001:2000
d) Well defined processes and methodologies
e) Data Protection, Confidentiality and Service Level Agreements
f)  State-of-the-art Communication Facilities

[Next 5 paragraphs omitted]

I have many objections to these emails, which typically come from off-shoring companies.  Let’s share some lessons about what’s wrong with them.

  • First, they are deceptive.  They are not about “partnership” (unless of course you define partnership as “I give you money” and you give me offshore developers, which I don’t).
  • They start business relationship based on a lie.  Credibility should be the top priority for the marketing department.  With these mails you first get my attention and then immediately destroy your credibility — the equivalent of expending great energy to shout:  I’M DAVE AND I SUCK.  (Why say anything at all?)  I know very little about Dacom or Damco or whoever they are, but I do know one thing:  they are willing to send misleading emails to increase lead conversion rates and therefore I want nothing whatsoever to do with them.
  • They bury me in useless facts that neither differentiate the offerings nor make me interested in doing business with the company:  they mails are– quite literally — all the same.  Everyone is CMMI this and ISO that.
  • They are mis-leveled.   They go to the trouble of renting a CEO mailing list and then write copy is neither CEO-level nor designed for the #2 thing CEOs do with email:  forward them to a direct report. (The #1 thing is delete and junk-list the sender.)  Done correctly, the starting copy would be written to make me want to forward the mail to my VP of Engineering and the rest of the copy would be written for him.

You could preserve your credibility and try to find a more strategic marketing angle with a subject like:

  • Outsourcing:  Five Things You Didn’t Know
  • Finally, Something Different in an Outsourcing Vendor
  • Yet Another Outsourcing Mail, Not.  Three Reasons Acme’s Different

Or, apply some of Porter’s generic strategies and head along one of two primary dimensions:

  • Outsourcing At Rock-Bottom Cost, Here’s How We Can Do It (cost leadership)
  • How Thing X Makes Vendor Y Unique in Outsourcing (differentiation)

But no matter your chosen angle, Dear Marketer, please remember this:  do not start a business relationship with a lie.

The relationship will last only as long as it takes to hit “junk sender” and you will be permanently muted thereafter.

Cheers,

Dave