How to Escape Data Flatland
This is the Three Data Point Thursday, making your business smarter with data & AI.
Actionable Insights
If you only have a few minutes, here’s what’s going to make your business smarter:
We’ve lost the ability to use data in every aspect of our lives. In times of information scarcity, the rule was simple: Acquire the right data at whatever cost is necessary. Use it to broaden your horizons, explore more options, and decide quickly.
There are only four clear rules for truly using data in decision-making: Spend serious resources on acquiring data. Focus everything on acquiring the right data. Use data only for broadening your options list. Move fast.
These four rules apply all across your life. Whether you’re traveling, founding a company, or checking the weather.
“What I’ve learned from watching real people in action is that […] they’re often unaware circumstances are thinking for them. ” - Shane Parrish in Clear Thinking
Pete is the Head of Data at a medium-sized company. But if you ask him whether the company would function without data, if he’s really truthful, he’d tell you: Sure, no manager would stop working just because he doesn’t have dashboards.
Anna is a startup founder, and she just came out of 50 discovery calls with customers. Does her startup also run without data? Yes, she admits, it kind of does. Most of her discovery calls only tell her what not to do, and she’s mostly focused on solving a problem she herself has anyhow!
If you ask me whether data makes my life better, I’ll watch my weather app and probably tell you it sure doesn’t feel that way. Mostly, data makes me anxious and annoyed.
If you had asked the military genius Sun Tzu the same question, though, he would’ve told you: Yes! My life and the lives of all my soldiers depend on data, the right data.
We’ve Lost the Way of Data
We have lost the way of data long ago. The age of information combined with modern technology screwed us over; the abundance of information made us incapable of working with it. We’re like rich children with so many toys that we cannot truly enjoy playing with any single one.
But that wasn’t always the case. When we return to the age of scarce information, we can learn how to use data and AI properly. So let’s time travel!
“Spies are a most important element in war, because on them largely depends an army’s ability to [make decisions on where to] move.” - Sun Tzu in The Art of War.
Sun Tzu lived 2,500 years ago in the Chou dynasty, which ruled China for almost 1,000 years (quite the feat itself). One of the things that stood out to me lately as I reread “The Art Of War” is the deliberate use of data by the Chinese generals & emperors, including Sun Tzu himself.
Knowledge gained by gathering data allows wise sovereigns to achieve things beyond the reach of ordinary men, as he puts it. To achieve this, Sun Tzu employed an extensive system of different spies. He made a point of rewarding them as much as possible; in fact, no member of the army should be more liberally rewarded than the spies.
This class of Chinese generals thus sourced their dominance for over 1,000 years with one simple imperative:
Acquire the right data at whatever cost is necessary. Use it to broaden your horizons, explore more options, and make a decision quickly.
Unfortunately, we’ve lost this attitude, and it’s not as straightforward to implement in our modern society as it should be, given all the advanced data and AI we have access to today.
So, let’s see how we can regain that attitude and apply it to our personal lives and businesses.
“The gift of the information age, after all, is knowing your options - not your destiny” - Rolf Potts in Vagabonding
What Really Matters in Decision-Making
How often have you checked your weather app, decided not to take the raincoat, and returned soaked? Exactly. Businesses keep looking at the same charts daily and still miss the big market opportunity. Entrepreneurs interview 200 potential customers and still build a sucky app.
Data is abundant, but what’s overrated is how we currently use it in decision-making. Decision-making, as it is taught in university, is bullshit. In university, decision-making means collecting tons of data to maximize a function over a set list of options. The thing is, neither human life nor data works like that.
I’ve learned three lessons about data and decision-making that help me make sense of this.
Lesson 1: Data is there to provide options, broaden your horizon, and never “help you make a decision.”
In a conversation, Stripe CEO and founder Patrick Collisson explains how decision-making as a discipline seems overrated. Instead, Patrick points out that real-world decisions, such as business decisions, rarely involve optimizing a choice of options on a list.
“It’s less on how do you make a decision and more about how do you jolt yourself out of the particular furrows that you’re in and realize the possibility space and the world is just so much bigger than perhaps people are thinking about. ” - Patrick Collison on the Tim Ferriss Show
Lesson 2: Speed of decision-making does matter.
“The senior team at Amazon is determined to keep our decision making velocity high”
Jeff Bezos realized long ago that decisions usually aren’t made with too little information but rather with too much. Too much information means lost time, so Amazon aims to make most decisions with 70% of the data you wish you had.
The problem of data and AI today: We’ve been told the tools and apps we have help with decision-making. Yet, in my experience, they don’t because they don’t obey the two lessons.
They feed us data in tabular formats, in probabilities, and in charts, and that’s it.
For us humans, there isn’t such a thing as a 30% ruined birthday party because you decided to
have the party outside and trust your weather app.
And that’s the key: today's tools are great for helping machines decide, but not humans.
So what? But we can and should use those tools as Sun Tzu used them 2,500 years ago: to broaden our horizons and follow these two lessons of decision-making then.
Four Rules For Data-based Decision-Making
If we combine lessons from Patrick Collison, from Amazon, and from Sun Tzu, we end up with a set of simple rules for using data for decision-making.
Rule 1: Spend some serious money on acquiring data. Sun Tzu rewarded his spies better than any other commander; Patrick Collison keeps talking about spending time not on optimizing but gathering more options and investing in the right kind of data.
Rule 2: Focus all your efforts on acquiring the right data. Remember, Sun Tzu didn’t spend his money on maps, geographers, or scouts; he spent it on spies. He knew the only essential information was the movements and the opponents' motivation. That’s where he put all his money. Amazon pushes everyone to understand what the right data is quickly. Collect 70% of the data and move fast!
Rule 3: Never mistake the information you gain as “your destiny.” Sun Tzu spent his time in deep thought, analyzing data to reach heights others never had. He never moved just because the opponent was moving. He took the data, studied it, and then made his decision, never mistaking information for destiny.
Rule 4: Move fast, both in acquiring data and making a decision based on it. While Sun Tzu did take the time to get the spies in place, he always knew that with every second, his army's resources were depleting. So he never wasted time. Once he got 70% of the data he needed, he made a decision. That’s what you must do, too.
So now, let’s look at a few examples of how we should use data & AI every day.
How To Use Data When Travelling
Rolf Potts is the author of Vagabonding, a generalist travel guide, but he’s also an expert in the perils of the information age. His advice is clear: Do serious research before going on your trips, buy special travel guides, and go through forums. Spend some serious money and time on gathering data (Rule 1).
But make sure you avoid the wrong kinds of travel information; try to find a mix of both, expert advice from guide books, locals, and experience reports written by other travelers (Rule 2). Don’t fall into a TikTok trap and watch “The 10 Things To Do In Iceland Noone Knows About” (I did…). Don’t rely on guidebooks for restaurant tips; in fact, he recommends avoiding the restaurants listed in guidebooks altogether and taking your time to ask locals for their recommendations.
“The gift of the information age, after all, is knowing your options - not your destiny” - Rolf Potts in Vagabonding (Rule 3)
Finally, Rolf clearly emphasizes getting going, not making too many decisions before you leave, and not overplanning. Simply get to the country you want to visit and go from there. Premature decisions on further transportation and sights to visit will only lock you in and reduce your actual experience—the joy of the new (Rule 4).
There is a reason why Vagabonding has over 3,000 stars on Amazon: it’s an amazingly unique book with clear advice on how to work with data in travel. An approach few people advertise for travel - yet everyone needs.
How To Really Use ChatGPT
Before writing a single word in this paragraph, I opened ChatGPT. In fact, I use ChatGPT frequently in writing. Yet, not a single word I publish is written by ChatGPT. How does it work?
I use ChatGPT as an idea-generation machine. And yes, I pay for the best version of it (Rule 1!). I don’t spend money on much else, no fancy writing tools, but this (Rule 2).
I asked ChatGPT to provide me with some outlines for this paragraph. What did ChatGPT suggest? A ton of crap (Rule 3). But between all these ideas, there was one option I hadn’t thought of: To weave the historical story of Sun Tzu deeper into this paragraph.
So, just like Sun Tzu, who paid enemy soldiers to acquire first-hand information, I can pay ChatGPT to get into the heads of other great writers. I don’t have to trust the information; I consider it an option among many, but if it fits well, I can use it immediately (Rules 3 & 4).
If I write an eBay text, I use ChatGPT because I’m not a professional seller. And you know what? I have zero ideas, but I get one that works using ChatGPT. It’s that simple to use AI these days; you just have to obey the rules.
How To Really Use Data As An Entrepreneur
Entrepreneurs, in my experience, have the luxury of drowning in high-quality data. They also have the trouble of not seeing any of it.
“Talk to your customers” is a rule hammered into start-ups worldwide (Rules 1). That’s all good, but it’s not enough.
It’s amazing how much entrepreneurs can talk to customers without doing what they should do: acquire knowledge from their conversations! (Rule 2)
Only a few entrepreneurs train well in how to talk to customers (The Mom Test is a great book on this subject), and even fewer understand what they are trying to find out (Lean B2B has great guidance on this).
What they should really do is:
Invest into proper data gathering, pay for fireflies.ai, it will supercharge your ability to analyze the conversations later on.
Invest in Hubspot or any other good CRM tool to log everything you do.
Spend the time to seriously dig into those conversations you had and find the true urgency in your customer's voices. If they are “interested,” you’re screwed.
It is amazing how many entrepreneurs think, just because potential customers say they are “really interested” and “would buy this solution,” that anyone truly will. They miss rule 3, they think whatever the customer says, or whatever they have in mind is their destiny.
Instead, they should spend 50% of their time analyzing their calls, going back and forth again and again until they find the one that signals true urgency. Once they get their sign of urgency, they should have 2-3 follow-up calls to confirm it’s more than one customer. Then start building like a crazy person! (Rule 4)
How To Really Use BI As A Company
Edward Tufte has made it his life’s quest to fight how companies use charts and reports every day. He’s, in essence, helping companies escape flatland. He’s focused on going beyond the basic charts and reports every company is drowning in, and I’m very much on his side. As Tufte explains, there is nothing in this world that fits into two dimensions (almost every chart and report is based on 2-dimensional data). Things are multivariate, so you must work to use data in real business decisions.
Almost every company starts out its BI journey with the same process: Hire a data person, buy an expensive BI tool, and overwhelm the company with relatively cheap data so that they fail to make decisions fast. In essence, they do the opposite of every single rule.
What they instead should be doing is a simple process:
Educate people about using data in decisions (because we all have some kind of data)
Then, find the bottlenecks inside the decision cycles to identify the right data (Rule 2)
Spend some serious money on acquiring this right data, and focus all your efforts on 1-2 kinds of decisions (Rule 1)
Keep on educating people about how to use data (help them learn Rules 3 & 4)
And slowly move on to the next set of decisions.
Indeed, there rarely is a need to build up your own data warehouse at the beginning of your journey. If you focus on specific decisions, you will usually be better served by using managed services, CRM systems, and Excel combined with a few simple shell scripts than any expensive data warehousing efforts that lead to data overload and decision fatigue.
How To Really Use Data In Every Day
Those rules apply to our everyday lives as much as to entrepreneurship. I like to run, so I spent the money to invest in a good tracking app. There’s no reason to wrestle a free version of a crappy app if you don’t get the data at the end of the day.
Similarly, I bought a good rain radar that showed me the movements of the rain clouds. Because when I use my weather app, what I’m mostly interested in is the temperature chart (that the native apps do quite well) and the rain (which most apps suck at). So I invested the money.
Spend the money on data trackers that matter as long as they track the right data.
But at the same time, whenever I go hiking, I check both a local hiking app and a guidebook. The local hiking app should be aware of recent changes and see a few pictures and the guidebook for a detailed explanation of the hike, nice spots to rest, and a parking space for my car. I don’t rely on either as my destiny; I get options, get more data, take a look at potential shortcuts or additional nice sights, and then decide where and how to go.
Data isn’t for Humans
Let’s face it: data isn’t made for humans. We work with it, but to guide it, we personally need to convert it into information, options, and ideas. Whatever digital things produce for us, it’s not going to guide us in the foreseeable future until we get that brain-computer interface thing working.
Don’t make the same mistake and fall for this fallacy: You’re not a machine; you don’t want to be data-driven; you just want more ideas.
Questions To Answer Right Now
No matter who you are, you can and should ask yourself these questions right now, don’t worry. It won’t take more than 5 minutes.
Pick any context: your personal life, travel, your business, your startup. Now answer these:
Am I spending serious money on getting data? If not, why? The answer is probably “no” because you don’t care about the data you have. Things would work without it.
Once I get 70% of the data, am I happy to make a decision? If the answer is no, don’t worry. It’s not because you’re indecisive. It’s because you got the wrong data.
How did I come up with the list of options for the past two decisions I made? You likely spent a couple of minutes selecting options and then an hour making a difficult decision. That’s not how it is supposed to be. Data is just there to provide you with a few suggestions. Spend more time gathering options and less time making decisions.
Next up: Fix this! Or message me your answers. I’m happy to discuss your situation with you and guide you toward a better life/business with data.