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Why B players will not become A players

This post was originally on VentureBeat, and is a follow up to my original post:https://venturebeat.com/2013/03/13/why-b-players-will-not-become-a-players/

I recently wrote a post entitled “Hiring B players will kill your startup” and I got some great feedback, ranging from supportive to visceral. I would expect nothing less from a topic so important.  A few of the comments addressed a related topic — the growth and development of B players to become A players — so I decided to write a follow-up piece.

Let me start with a simple statement: B players will not become A players.

Why not? 

I make this statement because moving up is difficult, and it rarely happens.  B players in an organization either don’t have the right skills, the right drive, the right fit, or a combination of all these.

Does this mean if someone is an average employee, they can’t be a great person?  Of course not.  One of my favorite comments I received involved deciding on a brain surgeon. Would you opt for the best (the A player), or the average (C player) surgeon with better bedside manner?  I think nearly everyone would opt for the best surgeon.

If you need a specific set of skills, attributes and attitudes, and a person doesn’t have them, you will be hard-pressed to discover them hidden somewhere.

The best managers can’t optimize everyone’s performance 

Before the comments flow about how this is not black and white, let me delve into context.  I am fully aware that I am not talking about inanimate objects, and that these are not absolutes.  I’m also not going to try to argue with anyone about exceptions.  Of course there are exceptions.  The world doesn’t fit nicely into a bell curve.

That said, the world grades on a curve.  Valedictorian status is given to the best student, not to everyone for giving their best effort.  This isn’t Lake Wobegon — all employees are NOT above average.

Leadership, culture, and many factors contribute to each person’s performance, both in absolute terms, and on a daily basis.  There is no question that environment plays a big role.  There is a full nature versus nurture argument, but organizational culture rarely adapts and even the best managers are hard-pressed to optimize everyone’s individual performance. Many people believe that a great manager can make everyone perform at their best.  I totally agree, but the A players working for that manager will outperform the B players. The best teachers in the world still have some A students, some B’s and some C’s and below.

B players won’t become A players:

  1. Within the same organization;
  2. Within their role.

Suffice it to say here that taking someone who is coasting in one role and shifting them to another rarely turns them into your best employee.  How many great managers reading this post can relate to having one or two “go-to” people on the team who always rise to the challenge?

A Players versus B Players

The difference between B players and A players is not measured by intelligence, education or raw skill.  It isn’t about who went to Harvard, and who didn’t.  A players possess the rare combination of drive, intelligence and pride in their work that is above and beyond the norm.  They don’t associate their names with anything short of excellence.  The best of the best are those with the lethal combination of natural talent coupled with drive.

At the top of the spectrum, A players are dynamic leaders and visionaries — they take on huge challenges that would seem insurmountable by others. But A players can be great at any level, and in different roles.  We have all had the experience when we spoke to a great customer service person who went above and beyond.  A players tend to transcend roles; they excel, wherever they are.

As soon as I mention the term “A Player” most people have images of Michael Jordan, Jerry Rice, or Steve Jobs. These people are obviously A players, but the key to their success is only partially their innate abilities.  Renowned for their extreme drive, work ethic, and attention to detail, none of them wanted a flaw in their game or their products. A Players don’t have to be selfish, prima donnas, or arrogant.  Plenty are, but that isn’t what makes an A Player.  Some of the most accomplished people I know are humble team-players.

Some will argue that coaching and leadership can make B players into A players.  In some circumstances, that is true, but in most business cases, it just doesn’t happen.  Work ethic is tough to change.  Initiative doesn’t simply appear.  Attention to detail is not simple to coach.  Not saying these areas can’t improve, but you don’t normally see quantum leaps.

Bottom Line

Everyone cannot be an A player.  This is the harsh reality.  In the US we idolize people like Jack Welch, who famously advocates cutting the bottom 10 percent of an organization every year.  It gets more difficult when the worst people are already gone, but at the end of the day, even when it gets difficult, some people perform better than others.  In our competitive world, only a small percentage of people are truly A players, and moving into that echelon from below doesn’t happen often.

Barca-Madrid, and by the way, Mobile World Congress

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I just got back from Barcelona and Mobile World Congress.  I believe it was the biggest show yet, and felt quite different this year.  For one thing, it was freezing cold by Barca standards.  Between zero and 7 Celsius every day is NOT what you expect in that part of Catalunia, even in February.  MWC moved to a new location this year, which was bigger, and could accommodate the show more easily.  But, it was more like being at the convention center in Las Vegas than it was being in Barcelona, and for me it lost the magic of the old Fira.  My informal surveys got 100% agreement that people missed the old location.  Transport was more difficult—the trains were packed to the point that they were not letting people on for long periods of time, and in a city where every second car is a cab, there were times where none could be found, even if you were using the MyTaxi app.

I always get asked “What did you like best at MWC?” or “What was the theme of the show this year?”  I always have trouble answering because, for one thing, being on the ground, I don’t see all of the talks, and I don’t necessarily read the headlines.  I am there meeting people and I have my own agenda, which is not usually tied to the major themes.  That said, in my interactions, this year the theme seemed to be about “big.”  The major handset makers were there in force, aside from Apple of course.  Samsung, LG, HTC, ZTE, Qualcomm, Nokia—Halls 2 & 3 were basically owned by a few big guys.  And of course, there was Huawei with seemingly their own city, as always.  One of my friends joked, “Huawei offered to buy the whole Congress with all the little companies inside.”

There was a lot of NFC this year, and that had been more absent in recent years.  The App Planet hall lost a little magic in my eyes this year.  Fewer small players and startups, although they could be found in other places.  Country booths were good this year, with some very strong global representation, and that was where I saw the best new startups.

This year for me was special.  I was invited to an event at the Barca-Madrid football match, which is unlike any other game on the planet, and it happened to be on my birthday.  Spain takes its football more seriously than just about anything, including possibly its economy, and the day of the match, it was the #1 topic on everyone’s tongues.  Barca recently lost to AC Milan, and there was a question of whether they would recover against their bitter rivals.

The air was alive ahead of the game, and not just with the freezing breath of the 100,000 people present.  Have I said that it is a marvel to me how efficiently 100,000 people can get into and out of a stadium in Barcelona when we get hours of traffic jams in the US?  Digression.  I love the singing at soccer matches; 100,000 flags waving in time to song.  This time I got another new and fairly unique experience, sitting near the visitor section.  This is not the same as the US, even compared to Raiders Stadium.  The visitor section is tiny, and has netting all around it, and bars so that people can’t get in and out.  Didn’t prevent the endless banter in language I won’t repeat here, the attempts to throw things both directions, and even one firework that was lighted, and thrown into the visitor section (successfully), then returned (also successfully).

The game itself was a disappointment for the home team.  Barca was outplayed by Madrid, and even if the penalty shot given the Ronaldo should not have been called, Madrid still stifled the Barca offense, had strong counters, and would have won.  It was the one disappointment .  The palpable energy in the city after a win is something special—I saw it last time I was in Barcelona.  After this match, the city was still alive, but the energy was not quite the same. 

Maybe not all bad because the meetings the next day start at the same time regardless of how late the parties go.

Try the Black Diamond

I took my two daughters skiing this weekend, and it was a welcome break from the daily grind. My daughters are 10 and 6. Both of them are skaters, so skiing is not so physically difficult for them, but the intimidation of looking down a steep slope creates a real mental challenge.

They did lessons the first day. Lessons can be a mixed bag, especially the group lessons, because you don’t know the mix you will get. This time, both of them were very fortunate, and had only two people in their classes; they got individual attention and they made fast friends, which always helps. The teachers supported them, but continued to push, which is not always the case. In group lessons, and often in many classes, the lowest common denominator determines the level. Both Nadia and Melina found good matches in this case, and both girls finished the day completely excited about their new friends and the runs they had completed (including the first black diamond for each).

The next day was family ski day, and Mari and I took them up the mountain early in the day. They have skied about 5-6 times before, so they are competent skiers, but it is always interesting to see how much progress has been made in lessons. We decided to start on a blue that was in range of what they had done the day before. There was one steep section at the top, and Nadia immediately said she couldn’t do it. I of course reminded her that she had done more difficult runs the day before, but she was not swayed. Melina went ahead cautiously, but was not particularly happy either. After side-slipping with Nadia for a while, I had her look up and see what she had just accomplished. “Yeah, but I don’t want to do it again,” she said. “But, you did it no problem,” said the dad who always wants his child to take on challenges. We got to the bottom without incident.

The next run had only slightly less slope, and they both went down with no problem. The third run, I had to work to keep up with them, especially Melina. By lunch, they were totally comfortable and looking for new runs, including more challenging runs. They had found a comfort zone with the standard blues, and were willing to keep pushing. When Nadia got home and saw her grandparents, the first thing she said was “I went down a black diamond.” Huge accomplishment. Not easy for a young child, and often more difficult for adults.

The biggest thing was overcoming the initial fear. Looking at a steep section of a mountain from above, you can’t see what is ahead– it could be a cliff or just a slightly steeper slope. You don’t know. Intimidating. As you get closer, or get to the edge, it can still be frightening, and it always looks steep from above.

Taking the plunge over the edge takes courage, and is not unlike taking challenges in life. Carol Dweck, in her book

    Mindset: The New Psychology of Success

captures this better than anyone I know. Challenging oneself to grow is the best way to achieve success. Just as I told Nadia to look back up the hill after she had come down, it is true in life that looking back, things look much less intimidating. The key is remembering the fact that you tried the Black Diamond, and you made it.

Why I’m skeptical the Moneyball strategy will work in early stage VC

This is a post I did for VentureBeat in December. I have always been a numbers and stats person, and I enjoy digging into models, so the whole concept of finding signal in the noise is interesting, even if I’m very skeptical that it works for early stage venture investing. I do believe that data is a critical input, and the better the data, the better the potential to help. https://venturebeat.com/2012/12/23/venture-moneyball/

Venture capitalists picking up the Moneyball strategy. It’s a fascinating idea, and I know plenty of my peers are working on algorithmic approaches to better their craft and gain an edge. As I see innumerable pitches that leverage “big data” as a key aspect of a business, and read about all of the ways that big data is changing the world, it seems natural that it will infiltrate the world of venture capital. Whether it works or not remains to be seen.

As someone who has worked at both ends of the spectrum — as a CFA performing public equity analysis, and an early stage investor — this is more than just a passing interest for me. I pay close attention to data, and I firmly believe that people who understand the numbers better than their competitors, will ultimately win. In public equities, some groups have clearly found ways to outperform using algorithms over time periods.

Are algorithms the future of VC?

In VC, we know the stats; a large percentage of companies fail, and returns have lagged over the past several years (although some firms have continued to outperform). Is data analytics the answer as some have suggested? Is it key to success in our industry, which is clearly changing? I have to say no, but will qualify my answer.

At the early stage where I invest, I am often assessing a team with a product that is not yet in the market, with no revenue, and with plans to hire some significant team members within the first year. Small data. There are very, let me stress VERY, few data points. And most of the data points that are there are qualitative, and there is plenty of noise. It hasn’t stopped me from building a few models along the way to see if I can glean some insight, but I can tell you what the models yield — garbage in, garbage out.

One might argue that algorithms can help predict markets, and I believe that could be true, but the size of the market opportunity for most companies is defined not by the actual size of the market, but by the team’s ability to address the market. It is SAM, not TAM. Let’s say a model detects that a market is developing, can the model help select the team that will win in that market? Revenue and growth are tightly coupled with a team’s ability to understand the needs of their customers and to fulfill those needs. It comes down to the team. I have yet to see a model that can tell me that a Mike Lazerow, Jason Goldberg, or Joe Lonsdale are better at figuring out their markets than others, but I can tell you that if you meet with any of them in person, you will know.

Early-stage vs. later-stage investing

That said, I do think they can be helpful in some ways, especially in later stage investments. One of my toughest challenges is assessing opportunity cost. If an algorithm can help me decide which of several investments has the best potential, then it can be valuable. But, in my experience, the value is directly linked to the maturity of the company, as small data becomes bigger data. And the breadth of the comparison set is critical to get a good signal; any bad data in these models can really skew results.

One algorithmic approach that I believe has potential is employed by Correlation Ventures. They analyze investments made by other VC’s using their proprietary algorithm, and join some of the rounds. Just the fact that they are leveraging the work done by other VC’s gives them an inherent advantage in selection — they add another layer to existing analysis.

Data won’t help us find the next Zuckerberg

The combination of human and algorithmic analysis is the best way to use data analytics. But data analytics won’t help us score the home run hits that are absolutely essential. The Moneyball approach simply doesn’t work because hit rates are not high enough to manufacture returns by getting on base. The key is swinging hard every time you step up to the plate — a Facebook home run is like hitting the ball OVER McCovey Cove and getting 10 runs for it.

So when I look at how data analytics will impact VC, do I realistically think algorithms will give me a competitive advantage? No. These are not liquid markets, and there are very few good data points. Will it help with due diligence and adding a few data points for my analysis? Maybe. Will it help identify target markets? Potentially. Will it make me a better investor? Doubtful. Will it help me win deals versus our competitors? No. Will it help raise money? To be determined.

To quote one of my mentors, Wharton Faculty member Dave Pottruck, “Go with your gut, but always crunch the numbers first.” But in the absence of all that much valuable data, VC’s need to rely on old school-hustle, homework, and instinct.

 

Why hiring B players will kill your startup

This post was originally written as a guest post for VentureBeat: https://venturebeat.com/2013/02/06/why-hiring-b-players-will-kill-your-startup/

B players and C players are far worse than D’s and F’s. In fact, in my experience, B players are the worst hires you can make.

Before getting into the details, it may be useful to level-set and explain what I mean by these employee stereotypes (although there have been some differences of opinion over the years.)

A player: Fully self-sufficient and takes initiative that positively impacts the company.
B player: Does some things well, but not fully self-sufficient, and not consistently strong.
C player: Just average, and does not excel in any area.
D player: Poor performer, and shouldn’t last long if you are a half-capable manager.
F player: Should be out…like yesterday.

Good Enough is the Enemy of Great

When you have someone on your team that you think is doing well enough, you will likely trust them with mission-critical tasks like hiring or pushing code. This will impact the entire evolution of your company. If you entrust important decisions to someone who is just “good enough,” you will watch the opportunities pass.

This is why hiring B players will kill your company. The work will be good, but not great. They will deliver on time most of the time, and hustle sometimes, but not always.

Let’s say you are in a startup, and you have a B player as your vice president of sales. The person will close a good account, but won’t consistently beat targets. If they go head-to-head against a competitor with better salespeople, this person (and potentially the whole startup) will lose. If you’re an early-stage startup, you are walking dead. Raising the next round will be like selling against a stronger competitor — you won’t ultimately win.

I have built multiple engineering teams from the ground up, and I always started with an anchor rock star.  The engineer that everyone wanted to work with, and whose work was so solid that he or she made everyone else more efficient and effective.  I’ve been asked before how many engineers it would take to replace someone like that, and the correct answer is that there is no way to replace a person like this.  Even if I could hire 10 B player engineers for the same price, I would never do it.  The product quality would suffer and the time-to-market would slow; you simply can’t replace skill with numbers.

Lessons learned

My opinions on hiring and people haven’t come by accident. I’ve got scars from my career (and I’ve seen it from many angles — founder, executive, consultant, investor). I’ve made some pretty bad hires along the way. The really bad hires are the easy ones — it is obvious when someone fails or is clearly the wrong fit. You wonder what you were thinking, but at the end of the day, you can reverse these mistakes quickly and efficiently.

I have needed to fire a fair number of people as well, and I will say this is one learning from my experience — I have never felt that I fired someone too soon.

At one of my startups, I fired my entire QA department and made the engineers do all their own QA. The result: better quality product, released faster. The QA department had become a bottleneck, and they weren’t doing quality work. The engineers weren’t happy, the product management team wasn’t happy, and the product suffered. I saw the release cycles slowing down, and saw some of the tension between the QA and Engineering departments. As I dug in, my conclusion was one I had not originally wanted to see — I had a B player at the top of the QA department, and the rest of the department was B and below. It was killing us. My biggest mistake was not recognizing it sooner.

When I was a little boy, my uncle used to tell me “he who hesitates is lost.” Those are words to live by.

I have plenty of individual examples as well, and the toughest ones are always the ones who are doing fine. Managers often blame themselves. Is the job not well-defined? Does the person have enough support? Maybe they just need more time, and they will improve. It isn’t easy to find great people, so why let the decent person go hoping to find someone better?

There is an opportunity cost to keeping someone when you could do better. At a startup, that opportunity cost may be the difference between success and failure. Do you give less than full effort to make your enterprise a success? As an entrepreneur, you sweat blood to succeed. Shouldn’t you have a team that performs like you do?

Every person you hire who is not a top player is like having a leak in the hull. Eventually you will sink.

Passing on a Great Deal Sucks

This week has been a painful one for me from an investment perspective. I had to pass on more than one company that I “know” will be extremely good. Intangible reasons, unquantifiable measurements, incongruent comparisons and divergent opinions litter the trail to the final decision. In the end, it is a simple yes or no.

The Process
At Blumberg Capital, we make decisions as a team. It doesn’t mean that we always have unanimous agreement, but we generally have enthusiastic support from at least part of the team, and acceptance from the rest of the team. When we have everyone lined up behind a deal, that either means we have found something special, or we have a bad case of groupthink. Some level of disagreement or hesitancy is by far the most common scenario, and I have to say that some of our best companies did not have unanimous support at the time of decision. The consensus-driven decision making process has pros and cons, but generally, if you have the right people in the room, it should yield good decisions more often than bad ones.

How Do I “Know” the Company Will Be Great?
Of course, I don’t know for sure that a company will be great. They say that this is a pattern recognition business, and there is at least some truth in that– you will know for sure if I am good at choosing companies in about 10 years. Hopefully a bit sooner if I outperform :-). That said, there are times when the writing is on the wall, the patterns obvious, and the main question is how big can the company become. In a particular case this week, one of the companies is the early market leader in its territory, scaling much faster than the next player, and there isn’t much competition yet. There is operational history demonstrating that this team knows how to build a very sound company. But, it is all relative...

If I KNOW the Company Will Be Success, Why am I Stupid Enough to Pass?
There isn’t a great answer to this question except to say that our decisions are based on making estimates several years out. Not easy. We attempt to understand market evolution, assess company execution, estimate competitive forces, determine capital needs and the ability to raise capital, and project dilution and ultimately exit. Boil it all down to “yes” or “no.” Sometimes there are “maybe” or “wait and see” decisions, but I will cover those in a separate post. Inexact science. We compare apples to oranges, and hope to yield the best fruit crop we can for our investors. Sometimes we get orchards, and sometimes lemons.

Opportunity Costs
The most difficult decisions are between companies where we are quite convinced they will be successful. We have limited capital and team bandwidth, so we simply can’t invest in every company that we believe will be successful. We are trying to determine which will be MORE successful, and will generate the best returns for our investors. And, there are times when we are looking at several companies that we really like, and we simply can’t invest in all of them. This has been one of those weeks. It is a champagne problem as an investor to be choosing between companies we believe will all be very successful, but sometimes the champagne tastes bad.

Why I like Financial Services in 2013, and in 2014, 2015…

When I look at financial services, I see opportunity. Period.

Industries that Need to Change
Companies that literally handle the money, and most haven’t changed much in 30-40 years. Do you know how many major financial services companies are still running programs on mainframes from the 70’s? You should be frightened. I have worked in multiple financial services firms, and seen a lot of dysfunction– my years at Ditech were most illustrative of why I see so much opportunity; they were the most frustrating, stagnant years of my life. (Others high on the frustration meter include my stints in investment management, banking, consumer lending and insurance). And Ditech was considered the most “innovative and leading” in the mortgage industry.

Ditech was ahead of the curve– 70% of our applications originated online, and it is one of the few companies that was solid through the crash. All that said, I felt like I was in the stone age. We had just figured out how to build simple tools. When I joined, we had over 200 software applications in production, some that did almost nothing, but were integrated into a spiderweb so ugly, it was almost impossible to sort. We had critical systems built in Delphi (look it up :-)). A huge accomplishment for us was moving to Java, and retiring well over 100 applications, getting down to only a handful of critical systems. But candidly, we didn’t innovate; we didn’t change the way we did business. We made one giant effort to adapt our business as other mortgage companies were swimming in subprime profits. We tried hard to launch subprime lending back in 2004-5 from our historical base of doing A paper mortgages. The customers were different, the processes needed to change, and our agents needed to change to address the different section of the market. We couldn’t. We failed miserably, and did only a handful of subprime mortgages, which was a blessing we didn’t realize at the time. Bottom line is we performed our normal operations well, but we couldn’t change. And we didn’t really have any pressure to change.

In the mortgage industry, the biggest innovations in the past 30 years have been DU (Desktop Underwriter – note the name) from Fannie Mae, and mortgage-backed securities. Not bad ideas, but missed a few details on the implementation (see 2008). This is just one industry under the financial services umbrella, and there is plenty of room for change.

My Fin Serv Investments
From banking and asset management to consumer lending and insurance, my career has led me through several financial services industries, and this is a key area of expertise and focus for me at Blumberg Capital. We are very active investing in financial services. I closed 9 investments in the past 18 months, and all of them have one thing in common: they are trying to change their industries and attacking outdated systems and capabilities:

– Addepar – next generation wealth management
– Credorax – acquiring bank built as a technology platform
– Lenddo – emerging market lending using social media
– Coverhound – car insurance 2.0
– ZipZap – global cash payment network (pay cash for online purchases)
– PaidPiper – payment messaging system
– Zanbato – infrastructure investment software platform
– Kreditech – advanced short-term loans using big data
– Paymill – simplest payment solution for merchants globally

And there may be one or two more coming :-).

Just Getting Started
This is just the beginning, and I’m not the only one thinking this way. When I speak with the big incumbents, they know. These are huge markets, and financial services is by definition in the flow of money– very attractive targets for entrepreneurs. As I said above, there isn’t much innovation from incumbents. Turning an aircraft carrier is not easy, especially if the steering is old. The most forward-looking financial services firms are spending a lot of time with entrepreneurs, seeking new opportunities for their businesses. If you think for a minute that financial services will look the same in 2020 as it does today, you are mistaken.

Opportunities for Entrepreneurs
Financial Services is a complex arena, full of regulatory pitfalls, difficult customer patterns, and structural roadblocks. These complexities make it difficult for new companies to succeed, and there are more than a few failures that burned through inordinate amounts of capital without success, plus a few public companies that are now roadkill.

However, the structural, regulatory, and inertial challenges make financial services a very attractive market. Sure, you have to run through a few brick walls, but mortar loosens with hammering. And, the same challenges make it very difficult for competitors (it’s like the walls reappear). The incumbents don’t innovate much, and the markets are huge, so if you have the guts to take on the establishment, there are some massive opportunities.

In each industry I’ve mentioned, the potential for game-changing innovation is off-the-charts. Underwriting needs to change. Lending and access to capital needs to change, both for businesses and individuals. Emerging markets are completely under-served. Insurance has plenty of room to improve, and asset management, for all of the complexity it has at some levels, is still using Excel in many areas.

If I am an entrepreneur looking to build a very big business and change the world, financial services is a great place to look. These markets are measured in trillions of dollars globally, and there are myriad places to find people who are under-served. You don’t need to displace a huge incumbent or take huge market share to build a great business. That said, if you can really disrupt the industry, you will be a huge company. HUGE.

The opportunities are flat out immense, and a few of us are looking carefully for people who want to take these challenges and build the next generation of financial services companies.

In future posts, I will talk more about some specifics, but suffice it to say that as an investor, I love financial services!