Horrible Bosses: The Uber Micro Manager

I finished up a management training recently, and that got me thinking about my past bosses. I’ve worked for quite a few managers, some good, some bad, and two distinctively horrible. One was your classic horrible boss. He was incompetent, always looking for opportunities to steal other people’s credit, and a general scumbag. The other one was a more rare and interesting case. He was extremely logical to the point of being robotic and his issue was definitely not incompetence. He was the ultimate micro manager and had to control 100% of your effort, down to your thought process. I have to say working for him was the turning point of my career.

I was 25 years old and had 3 years of experience as an IT consultant at the company. I had moved back to Japan for this job and was getting comfortable with the culture and gaining confidence at work. When I was assigned to the project, my colleagues had warned me about the project manager. In the five years that he had worked there, he had sent numerous young consultants to therapy and a lot of them would never come back. He had a reputation of being too tough but he would get challenging projects done and the company valued that.

The first three months of the six months project was tough but bearable. It was a three person team and I would get yelled at sometimes but it wasn’t anything I couldn’t tough it out. After three month, the other member of the team had rolled off the project and from there, it was a living hell. There was not a day that went by without getting yelled at. Every powerpoint slide, every excel sheet, every word I mouthed, every output I created was absolute shit. Everything I did was illogical and wrong and everything I had ever done in my life was worthless. If this was just an asshole boss, I could have shrugged it off and bad mouthed him behind his back over beer to feel better. What really sucked about working for him was that he was always logical and every feedback he had was backed with facts. He had notes of my actions and words that he would pull out as evidence and he created an environment that forced me to face the fact that I was wrong, illogical, stubborn, immature, incompetent, and useless.

A lot of times when he asked me a simple question, something like “what happened to that meeting material?” and it would take me a split second to answer because some thoughts crossed my mind unconsciously. Before I could answer, I was getting yelled at again for the thoughts that he somehow knew was crossing my mind.He would be able to verbalize my thoughts better than I could. “When I asked you this, your initial thought was X and then you thought Y. Those thoughts are inefficient and worthless.”

After getting tired of giving me the same feedback over and over, he made a list of things he wanted me to be always aware of. Every morning I come into the work, I would spend the first 10 minutes reciting the list to him. It went something like: “I will listen to what you say. I will make sure I write down every instructions given to me. Before I ask for your review I will confirm that the output achieves the objective.” and so on. When I did something wrong during the day, which inevitably happened multiple times every day, I would have to go back to the list and recite again.

The most intense part of the project was only for three months, but it was the longest and toughest three months ever. I became the first person to go through a two person project with him and not end up in therapy, although I have to say I was pretty damn close. I definitely came out of the project stronger and a lot more humble (that’s what happens when every single non fact based confidence is shattered). Could I ever work with him again? Hell no! However, I do have a weird appreciation for what he had done, I guess it’s similar to Stockholm syndrome or maybe just the result of the brainwashing. After the project I did grow as a consultant and became a lot more disciplined. I also learned how not to manage a team and the importance of treating your team with dignity.

In my defense, I am a smart and logical professional (I swear!) and even back then I was a competent consultant. I consider this period as boot camp and I needed a little ass kicking because let’s face it, I was a spoiled brat. However, I believe extreme stress is not always the fastest way to grow or succeed. I don’t need to beat him as an individual (and I don’t think I can) but I hope to be a better manager and a more effective leader than him. I look up to him in many ways but at the same time, he is my anti role model as a manager.

Next Step for Ad Tech: Product Data Innovation

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We’ve reached the most granular level in online advertisement targeting technology: an SKU to an impression. So where will the next innovation come from? I’m thinking the next big step in ad tech will be on the product side, helping advertisers pick which SKU to show a particular impression, at a specific bid price.

An impression is more than just the age and gender of the person. It is the person at the exact time and place. It includes the demographic, psychographic, and geographic information, the taste, mood, and everything about who the person is, adjusted for the context of what she is looking at. We probably can’t combine all those data for a given impression yet, but we’ve made a lot of progress in painting a picture of this person at the exact state in time.

What about the SKU side? When an impression shows up on a website, how much should an advertiser bid on this impression and more importantly, which product should he show?
I believe an impression has a fair intrinsic value that is a function of the predicted click through rate, conversion rate, the average order value, and how much % of sales the advertiser is willing to pay, adjusted for risk. In a formula, this looks like this:

I’ve outlined my thought process in a previous entry, found here.

My question is, of all the advertisers that are bidding on impressions, how many are looking at the product side on a data driven way? By data driven, I don’t mean “this product is designed for single urban males who like cars”. I mean “analyzing all the transaction history involving this product, the calculated CTR & CVR of this impression is X & Y, with standard deviation of Z”. The point is, advertisers are choosing which product to show without the rigorous past purchase analysis that should point them to the optimal SKU to show at the optimal bidding price. If you sell hundreds or thousands or even millions of SKUs how can you be sure that the ad you decide to serve is the best one in your product portfolio? Also if you are not amazon or Walmart do you have enough data to really make an intelligent decision?

The next innovation in ad tech will effectively collect these purchase data across merchants and transform it in a way that is useful to advertisers. With information asymmetry out of the way, advertisers will bid on impressions based on predicted CTR, CVR, and AOV. So what will win an impression when multiple merchants are selling identical products? It is the % of sales the advertiser is willing to give up thus ensuring the publisher will get the maximum $ for the impression. The user who will see the ad will see a calculated, optimized ad, which should match his profile so well that the ad will be less of a distraction and more of a content. Of course the advertiser who was willing to pay the most will get to show the ad, so we have a win-win-win situation between the user, publisher, and the advertiser. Moreover the product side innovation should drive automation even further. Ultimately, a user showing up to a website will trigger a process that will sift through millions of products across advertisers to find the optimal one. That sounds like a more efficient market to me.

Strategy Means Nothing without Operations

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” A vision without action is just a dream; an action without a vision just passes time; a vision with an action changes the world.” ~ Nelson Mandela

Substitute the word “vision” to “strategy” and “action” to “operations” and that’s your business quote of the day.

I like to use a bicycle analogy to talk about what strategy and operations are, and how they relate to each other. When you are riding a bike, you are performing two main tasks. Steering and pedaling. Obviously steering is strategy and pedaling is operations. In order to get to your destination quickly, you need both components performing. It is much easier to steer a company that is already pedaling well. When you try to shift the strategy of a wobbly bike, you risk falling flat on your face. Strategy means nothing without the operations to back it up.

So, what does it mean for a strategy to be backed up by operations? It means your resources are shifted towards the strategy. At the most granular level, it means your sales person is calling prospective client A rather than client B. It means your account manager is creating an additional slide and product manager is adding a few lines to the requirements document. Management is shifting some members from one team to another. In short, strategy is only effective when action takes place.

In a corporation, the way to ensure these actions happen is by reflecting the strategy into the budget. When you look at a company’s budget there should be a storyline. The numbers next to the line items needs to illustrate how the strategy is to be executed. If you can’t read your strategy in the budget, it’s not going to happen.

カルチャーはトップダウンで決まる

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（当ブログ内の英文記事をざっくりと翻訳して掲載しています。）

企業のカルチャーはトップダウンで決まります。どれだけ前向きな社員が集まっていたとしてもリーダー層の言動に反してよいカルチャーが根付く企業というのは存在しません。良いカルチャーはメンバー達にとってほしい行動をリーダー層が模範して示す場合にのみ築けます。リーダーが「なぜうちのチームは文句ばかり言うのかが理解できない」と文句を言うのは筋違いそのものです。

なぜでしょうか？人は基本的には成功したいですし、成功するためには自身の行動をある程度改めることができます。（もちろん例外な人もいますが、そういう人が組織内に入り込まないようにするのは採用の最低ラインです。）どれほどガツガツするかは人によりますが、大体の社員は昇格したいし、昇給もほしいものです。社員は上を見て自分もどのようにしたらよりよいポジションに就けるのか観察し、学びます。上位層が政治的に動き、評価されているのを見ると下位層でも同じような行動がとられ、政治的なカルチャーになります。逆にリーダー層がチームワークや誠意を見せ、評価されているのを見るとメンバー達も同様な行動をとり、良いカルチャーが醸成されます。

リーダーとして、よいカルチャーを築き上げたいと思うのであれば、末端層の行動を変えてもらう取り組みを考える前に、まずは自分自身と周りのリーダーの行動を見ましょう。組織全体のカルチャーを変えるために行動を変える必要がある人はトップのごく一部なのかもしれません。

Personnel Announcements as Communication Vehicle

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In the past couple of days, I talked about why office politics suck and how corporate culture is set top down. What’s also really interesting is HOW culture is communicated throughout the organization.

The strongest messages from management to employees are delivered through personnel announcements. Promotions, demotions, disciplines, dismissals, transfers, etc. The message is stronger than any presentation or training because it is REAL.

We’ve all seen promotions that makes you say WTF? But there is a line of thinking and justification behind every single personnel move, and that is a manifestation of the leaders’ values and a representation of the corporate culture. No one ever gets accidentally promoted. Some may get an undeserved promotion, but even those are intentional.

A personnel announcement is essentially a list of who’s getting rewarded and who’s not. Team members know their leaders and fellow employees, and they share information amongst themselves. They know WHY each of the personnel changes took place or didn’t take place and this common understanding creates the foundation of culture. So if you want to create a certain culture in your organization, be careful of who you surround yourself with, because no matter what you say in your new employee training, your actions will speak a lot louder.

The Guess Why I’m Crying Game

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I have a two week old daughter. Yes she’s a bundle of joy and is without a doubt the cutest thing ever. She is also a very calm baby compared to others. But raising a baby is like playing a game of “Guess why I’m crying?”.

Here are the rules of the game for a newborn. I assume these will evolve as the baby grows and learns more curve balls to throw at you.

Baby will start crying. This can happen 24/7.
You have to guess why she is crying
She is either hungry, sleepy, in need of a diaper change, hot, cold, uncomfortable, in pain, gassy, burpy, in need of a hug, in a bad mood, or just messing with you because she can
If you get it right and take the proper action you win and she will quiet down unless she decides not to (because she can)
You cannot adjust the volume, in fact, she will cry louder as she grows
You don’t have an option to not participate in this game

Of course it’s all worth it. Except when you change her diaper and immediately she decides to poop while sitting on your lap. And then starts crying.

Culture is Top Down

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Corporate culture is determined top down. There is no such thing as great corporate culture despite the leaders. Great culture only exists when leaders exhibit the qualities they want to see from their teams. The worst is when managers complain about their own team culture. “I don’t understand why my team is always bitching and complaining!” Touche.

Why is this? It’s because people, for the most part, are coachable and want to succeed (I say “most part” because unfixable assholes do exist and that is a hiring problem). Corporations are organized in a way that incentives upward mobility. So for the most part, employees are looking up and learning what they need to do to go up. If they see leaders politicizing and getting rewarded, they will mimic those behaviors, creating a political culture. If leaders exhibit teamwork and integrity, that will trickle down the organization and create a positive culture.

So if you are a leader of an organization and want to build a good positive culture, first look at yourself and how your fellow leaders are acting. You may be able to fix your corporate-wide culture issue just within the leadership team.

Office Politics Suck

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Office politics suck. It sucks for the company and it sucks for the employees.

It sucks because it is so resource intensive. It takes time and effort to learn the dynamics of the organization (the rules of the game), play the game, and be good at it. This is time and effort that should have been used for more productive activities.

It sucks because the asset and skill set you build are not transferable. You are making your investment in people and how they perceive you, and people change in organizations. The boss may get transferred or fired or may hire a new favorite. The company you work for may go bankrupt. You and the investment you have made are at the mercy of these changes. Also, that nice title you got without the competency to back it up will bite you in the ass in the future (and everyone below you will be laughing).

So why do many (most?) companies fall into the trap of unproductive, political corporate culture? The answer is simple game theory. The team’s output is maximized when none of the members are playing politics. However, from an individual member perspective, if someone else is playing the game, you are better off playing, even at the expense of hurting the productivity as a team. Once the game starts, you can’t expect the members to take one for the team and get screwed over. As Ice-T once said, with office politics certainly on his mind, “Don’t hate the playa, hate the game”.

If you want to build a productive organization you need to prevent the game from starting by taking these two steps. First, you have to hire the right people. One bad apple can really mess things up, especially if that person is higher ranked. Trustworthiness is more important than experience and knowledge. Second, as a leader of a team, you have to stay disciplined. Management laziness and ignorance creates a breeding ground for misaligned incentives. If you can’t see through the bullshit your reports present you with, you don’t deserve to be overseeing that area. If you see a bad apple, you need to have the discipline to fix the problem.

In The Five Dysfunctions of a Team Patrick Lencioni illustrates a pyramid that summarizes the essential components of a productive team. Not surprisingly, trust is the base of everything. Team members trusting each other that they won’t play politics will ensure a bullshit free (not conflict free) environment, leading to a more productive team.

An Efficient Market for Online Ads

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This is another old post from Tumblr.

In my last post, my argument was essentially: The difference of CPM/CPC/CPA is risk transfer and the fair price can be determined by looking at the mean and standard deviation of the three risks that are being shared between the advertiser and the publisher. The three risks being: click through rate (CTR), conversion rate (CVR), and average order value (AOV).

I was thinking option pricing may work to get to the right price but upon further thinking, this looks more like a job for crystal ball or some statistical simulation tool. So, if you have all the data points, you can plug them in and boom, you should have an idea of fair relative price for the each model. If you are bidding on an impression at a certain price, how much should you be willing to pay in CPA? This equation can be expressed like this:

This assumes that whatever bid price you have for an impression is the right price. In a perfectly efficient market where the bid price is always right, this makes sense. But we live in a imperfect world and advertising is especially an inefficient market, so this should be the other way around. Our bid price for an impression should be driven by how much % of sales for this certain product you are willing to give up in order to show an ad in front of this person. So the equation that we are actually trying to solve should be:

If I am making 5% gross profit margin on a speaker, I am only willing to give up 0.5% of the price. But if I sell my own brand of super expensive shoes at the GP margin of 70%, I may be willing to pay 10% of sales. So the % of sales you are willing to give up is purely an internal decision driven by the nature of the product and your risk adversity. Let’s say for this one user looking at this blog, I know the likelihood of him clicking on the ad is, the likelihood of him buying something is, and know how much he will spend, plus I know I am willing to pay 10% of sales to get this guy to purchase my product, then I know exactly how much this impression is worth to me and how much I should bid.

The only problem is, we don’t know the exact CTR and CVR and have no idea on their standard deviation. This is where big data comes in. If we can identify this user and look at his past behavior, we can make an intelligent guesstimate of the variables. We may also take context into consideration. If you are looking at a funeral website, you probably won’t be clicking on an ad for a sports car. But what is the problem we are trying to solve? It’s not just that the more data the better. We need to predict this user’s behavior as accurately as possible.

So the point of this post boils down to this. The holy grail of online advertisement is predicting intrinsic demand.

That means I want to show you an ad with a product that:

You don’t already have
You don’t know you want (because you would be on Google or Amazon searching for that product if you wanted it now)
You really really want

I think in the online advertisement market, we are finally trying to figure out #3. Retargeter do this by saying, “hey you almost bought this product, maybe you would actually buy it if I give you free shipping”. The problem with that is scale. You don’t abandon shopping carts everyday so the amount of ads you can serve with this method is limited or you will be annoyingly repetitive. So, in order to understand what you really really want that you don’t know already, we want to understand who you are and your taste.

Let’s say I sell leather pants (which I don’t and have no plans to). There is a user looking at a blog and I have an opportunity to show an ad.
Here is the user profile:

Male
30′s
stable job
married with children

I’m quite indifferent about this guy. Not willing to pay much at all.
But what if we also find out he loves metal, Harley Davidson’s, and wears leather jackets? This is a guy I want my ad to be shown to and I am willing to pay for it. So the more specific information I have about this guy and the more match I see with my product, the more I am willing to pay.

The race for the new new thing in online advertisement is, who can predict a user’s taste and match that impression to the advertiser with a product that maximizes his desire. At this point, advertisements should become less of an annoyance and more of a content. Amazon has a whole bunch of information on what you’ve bought before and can infer what you might like. But the cool thing about Pinterest is that it can connect a whole bunch of seemingly random products that you like, or someone similar to your taste likes and create a taste map. This can be used to understand the user but also to understand the product.

With the granularity of decision making reaching the logical extremes of “one impression” to “one product”, it looks like the field is finally set to start the data collection & algorithm battle. There is so much inefficiencies for companies to profit from and it will be interesting to see if giants like Google/Amazon/eBay will figure it out first or a new comer like AppNexus/Pinterest will come out on top. I’m excited to see Pinterest taking a stab at this with their unique asset.

CPM, CPC, CPA, and the Transfer of Risk

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This is a post I wrote on Tumblr a long time ago (July 2011!) but no one read it.
The point is still valid, so I’m copying it here with slight updates.

I am currently employed in the CPA side of the online advertisement industry, putting me solidly in a minority. There are millions of sites that explain the definition of CPM, CPC, and CPA individually, but not many describe them relative to each other. Just to go over the basics:

CPM: Cost Per Mille. Advertiser pays the publisher per 1000 of visitors who the advertisement is shown to. Cost = # of Impressions / 1000 * CPM
CPC: Cost Per Click. Advertiser pays the publisher for each click on the advertisement. Cost = # of Clicks * CPC
CPA: Cost Per Action. Advertiser pays the publisher for each desired action such as a percentage of sales or a filled out form. Cost = # of Actions * CPA

So how do these different pricing models relate to each other?

# of Clicks = # of Impressions * Click Through Rate (CTR)
# of Actions = # of Clicks * Conversion Rate (CVR)
So, # of Actions = # of Impressions * CTR * CVR

If you are paying $100,000 for a campaign and you get 1,000,000 impressions, CTR = 10% and CVR=10%, what are the CPM, CPC, and CPA?

CPM = $100,000 / (1mm / 1000) = $100 (or $0.1 per impression)
CPC = $100,000 / (1mm*10%) = $1
CPA = $100,000 / (1mm*10%*10%) = $10

This means we can relate the three this way:
CPM/1000 = CPC/CTR = CPA/CTR/CVR

Except, we did not consider one thing, and that is this guy…

Risk.

Both click through rate and conversion rate will have a standard deviation, meaning those numbers are never constant.Sometimes the numbers will be above average and sometimes will fall below average. Even if you know the median CTR and CVR for the publisher, advertiser, and the advertisement, that’s not always going to happen (in fact that will almost never happen). The wider the distribution curve, the more likely the CTR and CAR will diverge from the median, which means higher risk for either the advertiser or the publisher.

Changing the pricing model from CPM to CPC to CPA is the act of transferring risk from the advertiser to the publisher. Let’s take a leap of faith and assume that the advertiser wants to drive sales.

In a CPM model, the advertiser is bearing both the risk in CTR and CVR. From the publisher’s perspective, all you need to do is drive traffic and you’ll get paid. If you decide to run a yamaka ad on a mormon website, you’ll still get paid. The advertiser is bearing all the risk.

In CPC, the advertiser transfers the CTR risk to the publisher. Now that yamaka ad is not going to do too well. The incentive for the publisher is to show advertisements that is relevant to the audience so they can generate clicks.

In CPA, the advertiser transfers not only the CTR risk but also the CVR risk. So even if the publisher is able to generate traffic to the advertiser website, they won’t get paid unless the user actually purchases something or fills out a form.

That is asking a publisher to do a lot. If you think about a percent of sale offer, the publisher is taking more risks than just CTR and CVR. If the user only spends $2 on the website, the publisher will only get a tiny pay. So the publisher is also taking on the risk of the average order value (AOV). In fact, CPA is basically riskfree for the advertiser and it should not even be considered a marketing expense. It is more of a cost of goods sold expense.

So, in order for the publisher to take on more and more risk, the below formula must hold true.
CPM/1000 < CPC/CTR < CPA/CTR/CVR
The publisher must be rewarded with a higher payday with CPA compared to CPC, which in turn will be more expensive than CPM.

Exactly how much more expensive should CPA be? That’s the million (billion?) dollar question. We are valuing risk based on standard deviation which from my knowledge, sounds awfully like an option…