The quote is management dogma. It makes sense. How do you measure success? How do you quantify what needs to be improved? What is a metric everyone can work towards?
In many ways, measurement is a proxy for intuition, trust, and complexity. Most of us have crappy intuition (checking my dating history). As for trusting data, “There are three kinds of lies: lies, damned lies, and statistics.” Complexity is increasing at an exponential rate. A hundred years ago, two brothers built an airplane. Nowadays we don’t fully understand how AI makes decisions. So we boil everything down to a few numbers.
That’s why Goodhart’s Law is important. It states “When a measure becomes a metric, it ceases to be a good measure.” More specifically, “Any observed statistical regularity will tend to collapse once pressure is placed upon it for control purposes.”
Measurements lose or hide fidelity. There are components we don’t understand or are black boxes (see any ad tech platform) or have secondary or tertiary level interconnectedness we cannot see. Plus we don’t fully understand causal relationships between people (their intentions and behaviors) and the interactions with systems. Yet, we are required to make decisions based on the ambiguity. We align incentives with the direction we want the metric to go.
As a slight tangent, we have the McNamara Fallacy, where one makes decisions based on easily identifiable numbers, and disregarding what cannot be easily measured. That is all of digital marketing. Digital-only marketing proponents keep pushing the idea that it is better because it is measurable. Not true. Easy measurement of digital does not mean it is more efficient. Not being easily measurable does not mean it is not relevant. In online advertising, all we hear about is CTR, CRO, CPM, CPC, CPA, confidence levels, etc., creating an industry of spreadsheet junkies that eventually lead to:
The danger is in choosing the wrong metric.
Let’s take Facebook as an example. Their measurement of success is making sure Facebook stock price goes up constantly. This is driven by increasing the number of clicks (oh oops, “engagement”) with ads or publisher content. The platform needs to predict what content a user will click on. Humans are tribal creatures. We look for ways to re-affirm our beliefs and social structures. The success of Facebook inherently generates and amplifies our reptilian instincts. Is it possible for any social platform to not become a channel for culture wars when the ultimate metric is clicks?
Similarly, if you are YouTube, and creators have to play the SEO game for revenue, you end up with garbage. (We will ignore the fact if PBS had done this, they would have been de-funded already. The consequences for Google? Nada. But, you know, Facebook and Google aren’t media companies, they are technology companies.)
Another tangent, the Streetlight Effect where people look where it is the easiest to look. The joke:
A police officer sees a drunken man intently searching the ground near a lamppost and asks him the goal of his quest. The inebriate replies that he is looking for his car keys, and the officer helps for a few minutes without success then he asks whether the man is certain that he dropped the keys near the lamppost.
“No,” is the reply, “I lost the keys somewhere across the street.” “Why look here?” asks the surprised and irritated officer. “The light is much better here,” the intoxicated man responds with aplomb.
From François Chollet’s The impossibility of intelligence explosion:
“And what is the end result of this recursively self-improving process? Can you do 2x more with your the software on your computer than you could last year? Will you be able to do 2x more next year? Arguably, the usefulness of software has been improving at a measurably linear pace, while we have invested exponential efforts into producing it. The number of software developers has been booming exponentially for decades, and the number of transistors on which we are running our software has been exploding as well, following Moore’s law. Yet, our computers are only incrementally more useful to us than they were in 2012, or 2002, or 1992.”
Who is this François guy? An AI researcher at Google who created one of the most popular Deep Learning frameworks.
In the context of digital, it is fascinating to realize that digital hasn’t changed how we live our lives. We buy/rent a house or apartment. We drive our cars or ride the train to work. We push digital paper around at work. Netflix made TV a better experience, but it is still watching TV. Airbnb made it easier to book an exciting home somewhere, but it hasn’t changed travel. The channels and tools have changed, lessened the friction we have to deal with, maybe made us more productive, but at a fundamental level, our activities have not changed.
And that’s ok. The problem is that our expectations are out of whack: we think every new piece of technology is life-changing. All information gets broadcasted at hyper-speed and hyper-volume now. We have no practical way to filter and process. We end up thinking and treating everything equally important all time.
Of course, we can see this in its full glory with bitcoin and blockchain technology today. I ran into this visual earlier in the week:
From an AngelList newsletter:
“Key takeaway: Blockchains are the biggest technological breakthrough since the Internet.”
Now, I have nothing against blockchain and bitcoin. There are extremely promising uses for it, but every time I see a ‘once in a generation’ type statement, I’m reminded of Roy Amara’s quote:
“We tend to overestimate the effect of a technology in the short run and underestimate the effect in the long run.”
Very few companies have gotten big data right. Most current applications of AI, more specifically supervised learning, requires large amounts of clean data. So that is going to be a challenge. And instead of figuring out all that, we will be moving on to the blockchain. Funny. Or not.
Read about the type of discussion McKinsey is having with clients about digital and marketing. Is your data in silos? Do you have to re-orient employee mindsets to put customers at the center?
It is almost 2018. Why are we still having these types of discussions?
Back to AI. Like most executions of digital which have focused on process, efficiency, and cost, instead of being transformational, AI might be the same. Check out Andreessen Horowitz’s State of AI video. Lots of examples of reducing friction and doing existing activities better and faster, but nothing new.
It is not to say that old economy jobs won’t be destroyed and supplanted with new ones. Or existing companies will not get wiped out and new ones created. As an example, listen to episode 27 of Rad Awakenings podcast where they discuss a new company that arbitrages interest rates, other macroeconomic information, and payment terms to elicit discounts from vendors. This is possible now that we have the computational power and ability to massively aggregate amounts of data.
AI is not earth shattering as harnessing electricity or practicing agriculture for the first time. We expected flying cars by now. Instead, we got electric cars.
Social networks facilitate and magnify identity politics.
Once a user follows more than Dunbar’s number, algorithms have to kick in for platforms to be usable and not overwhelm. Generating engagement and stickiness requires displaying content platforms think you will like. So algorithms look at what the users first, second, etc level connections like, what similar profiles like.
Objective, rational content is boring and gets little engagement. Publishers push content that is emotionally driven. Content that requires us to pick a side.
Combine both and you have a filter bubble that amplifies tribal tendencies. A filter bubble based on identity politics.
This isn’t to say social media creates identity politics. We all want to be part of our own tribes. The point is that the natural output of social media will always be based on identity politics.
It is not unlike other social interactions. We hang out with family, neighbors, coworkers, church members, alums, etc. The problem is our expectations. For some reason we thought global social platforms would connect us all, expose us to new and different ideas, and then we would all become enlightened.
That’s not how our biology works.
What happens to society or businesses if young men never have any reason to leave home?
Historically, young men of a certain age, let’s say 18, want to leave home. The reasons are well known and revolve around the idea that independence will allow for making money (or going to college to gain a skill), entertainment, socializing and dating. Everyone wants to ascend in Maslow’s Hierarchy.
But rules of the game have changed.
Young men may not be enthusiastic to join a work environment where they realize they are not as unique as mommy/daddy/school said they were and now have to put in the time and effort and play the office politics to climb through corporate ranks. And even if they do, there is the constant threat of layoffs/outsourcing/automation and stagnating wages. On the flipside, if the only available jobs are in a low-paying service industry, it is challenging to support oneself, let alone raising a family or saving for retirement. To make it all worse, possibly crippling student debt.
Add in that marriage and settling down is not an exciting milestone. Hanging overhead is the experience of complex relationships and pain resulting from divorced parents. Add in the high bars set by heavily-curated lifestyles seen on social media creating unrealistic expectations for the perfect mate.
So, if you can live at home, why leave?
Nowadays platforms allow for more, quickly, now. But it’s not the technology that is exciting in itself; it’s the change in human behavior. So, what if men could fulfill all their needs, on demand, while living at home?
Entertainment: 5000 cable channels, Netflix, Hulu, Xbox, YouTube
Food: Grubhub, Ubereats, Postmates
Socializing: Facebook, Instagram, Snapchat, texting, Reddit, Discourse
Adult: infinite tube streaming sites
The shift in leaving home may not be permanent, but what is the impact of postponing the transition to adulthood for five years or even ten years?
The potential economic impact is significant. Take the home construction industry as an example. If historically the average person buys three homes over a lifetime, and Netflixication reduces this is to 2.5, the ripple effects are massive. Construction labor, building materials, landscaping, appliance manufacturing, furniture, retail, architecture, engineering, insurance, mortgages, transportation, wholesale, and warehousing.
We have built religious, legal, and economic rules around the expected social norms and life trajectory. Are we capable of dealing with them becoming frayed or delayed?
All the talk of Amazon buying Whole Foods revolves around Amazon getting its tentacles even more into the grocery business.
Talk about underestimating Amazon. Two articles I suggest reading to understand how Amazon thinks: Why Amazon is Eating the World and Amazon’s New Customer.
Amazon is a different breed of company. Why? Its service-oriented architecture (SOA) structure. The Wikipedia definition of SOA: “services are provided to the other components by application components, through a communication protocol over a network.” In short, autonomous components that know how to talk to each other. At first glance, this would not seem revolutionary. Plenty of big businesses already have silos that never talk to each other and compete against each other for budget and credit. Sure I am sarcastic, but how does Amazon do SOA?
Amazon’s silos service customers internally and externally. They start out with an existing large internal customer, but they are designed to be used externally as well. Their warehouses are not only for Amazon merchants but any third party who needs order fulfillment. Selling through amazon.com is not a requirement. AWS is similar. It was created to power parts of the website but became a product to rent out.
Most companies build a product or provide a service. Imagine what happens when all the core activities are profit centers by using them internally and externally. How you create a product, service, or function changes. It is building a business that can thrive in a world of constant change. Instead, we have companies creating innovation labs whose outputs will have to be bolted onto existing processes and systems…unsuccessfully.
As Ben Thompson points out, Whole Foods is not about getting into the grocery business. It is taking the Whole Foods logistics, re-architecting it so it can be used internally for Whole Foods, but any other industry/vertical that buys food whether its hotels, restaurants, assisted-living homes, schools, and so forth. They will be competing against Sysco and U.S. Foods.
We thought Uber’s was in the logistics business because of UberEats and flower deliveries. However, that is small potatoes compared to Amazon when it wants to do everything from payment (money logistics) to drone deliveries and everything in between.
Whenever brands talk about change transformation, usually there are three pillars: process, technology, and communication.
The people component is assumed to be elements of all three.
Unfortunately, the hard part is people.
Externally you have investors, analysts, regulators to satisfy.
Internally you have competing power structures and budgets, misaligned incentives, matrix reporting structures.
In reality, the roadblocks are much more significant:
Add in the fact humans don’t like change. Plus everyone’s favorite topic, corporate risk management.
We can try offshoring, nearshoring. We can try to add another piece of technology. We can try newsletters and coffee mugs.
None of it addresses the real problem.
How do people change or become comfortable with change in a faster-moving world?
Are alternative org structures like Wirearchy and Holacracy really a path forward?