We’ve got snow on the forecast! It’s finally getting cold here in Texas (lows around 22F/-6C), so the forecast is calling for one inch of snow on Tuesday morning. Woot! ❄️
Texans are quite awful in the snow. There’s no salt/sand/plow infrastructure because it’s so rare. No one has snow tires. No one has much experience or recent practice at driving in the snow and ice.
I haven’t been to the grocery store yet, but in past years with a forecast like this, all the stores will be out of milk and toilet paper as everyone freaks out and stocks up on supplies.
Sometimes the schools even close in anticipation of snow, although right now school is still on for the week.
Cold weather also means an end to American football season. I’ve been enjoying the NFL playoff games with the family, but as of you reading this there are only three games left in the season.
There’s Formula 1 in March, and the kids still play a lot of organized sports, but there’s nothing for me quite like football season.
What’s January like in your neck of the woods? Are you in summer down under? Are you a Northerner already buried in snow? I’d love to hear from you; email me at heykev@kevinnoble.xyz and let me know.
Kevin 🥶
A Quote
“
We must all stop treating every little fucking thing that happens at work like it’s on a breaking-news ticker.
— Jason Fried and David Heinemeier Hansson in "It Doesn't Have to be Crazy at Work"
Three Things
1 - 🏖️ Noah Smith Being Bullish on the Middle East - Having just finished the book on Dubai, I was interested in hearing Noah Smith’s take on why he thinks that region could be poised for good things ahead. Advances in technology, particularly in solar power and desalination, could drive development and reduce reliance on oil. With a favorable demographic shift, the region may transform into a hub of green energy and industry.
2 - 🚀 Bezos’ New Origin Competition with Elon’s SpaceX - Blue Origin, the space company founded by Jeff Bezos, successfully launched their New Glenn rocket on their first flight. It’s really cool to see competition in commercial space flight. What newly developed technologies will make their way down market in the future?
3 - 🏦 Spending $30K to Buy a Company, Making $1.7M in Profit in a Few Years - Entrepreneurship Through Acquisition (ETA) remains a fascinating concept to me. I previously shared a story of a friend who lost almost everything on a bad deal, so today I’m sharing the opposite. Guest Pete Ciaverilla spent roughly $30K of his own money to buy an HVAC business, and now he owns 92% of it, and it generates $1.7M in cash every year. That’s a sweet deal!
(This is a 6️⃣ minute read)
Deep Dive on Input Metrics
You want to drive big outcomes.
Maybe at work you want to increase revenue. Or increase customer retention. Or decrease employee attrition. Something big and meaningful.
In your personal life you might want to lose weight or get stronger. I’ve got my own VO2 Max goals I shared previously.
But how do you get there?
Goals are out of your control.
A goal doesn’t care that you want it. You can’t wish it into existence.
Goals are achieved based on what you do.
But your energy and attention are limited. You can’t do everything. What are the specific areas you should invest in? What’s under your control?
What you’re looking for are the input metrics. Today I’ll introduce the concept, share a few examples, then show techniques to find them.
“Donald Wheeler, in his book Understanding Variation, explains: Before you can improve any system … you must understand how the inputs affect the outputs of the system. You must be able to change the inputs (and possibly the system) in order to achieve the desired results. This will require a sustained effort, constancy of purpose, and an environment where continual improvement is the operating philosophy. “ - From “Working Backwards”
The Relationship Between Inputs and Outputs
You experience inputs and outputs all the time, even if you’re not really thinking about it.
You want coffee (output). So you pick out how many beans, choose the grind size, and turn on the machine (inputs).
You want dinner (output). So you pick out a recipe, grab ingredients, choose equipment, temperatures, and the process (inputs).
…or you order online (also a valid input) 😁🍕
We’re operating in a system that is a series of causes and effects.
Watch this OK Go music video for “This Too Shall Pass” from 2010 to see a very elaborate Rube Goldberg machine - a red truck is the input, getting splattered with paint is the output.
Simple outcomes have simple inputs. Bigger outcomes - like those big goals we’re driving - have a complicated or complex set of inputs.
Running Example
When teaching people about inputs and output metrics, I like to use this running example.
If I want to improve my 5K time, that’s my output.
I don’t control my 5K time. So I need to find something I control that has a positive effect on that output.
For running that would be: - How often I run. - How far I run. - My running speed.
So if I had an objective to reduce my 5K time by three minutes before the end of the year, I would focus on my inputs. I’d increase how often I run, I’d increase my training miles, and I’d improve my pace.
The output would follow from the inputs.
Notably, hours of YouTube videos watched on running is not a valid input.
Amazon Example
Amazon is famous for focusing on inputs instead of outputs; Jeff Bezos is a huge proponent.
For Amazon, the business cares about things like revenue, profit, and customer growth. But since those aren’t under their control - and customers don’t care about them - they focus instead on the inputs to revenue, profit, and customer growth.
For Amazon, inputs are things like product prices, breadth of selection, and time to delivery. Amazon can work to improve those measures and the outputs will take care of themselves.
Amazon might want to increase the number of customers by 10%, but they’ll focus on reducing prices, stocking more items, and increasing the number of markets they’re in.
They Work in Layers
If you work on a big team with really big outcomes, it can be helpful to think of inputs and outputs as working in layers.
In the above example, Amazon would treat something like time to delivery as an input. Relative to revenue, it was something they could control.
But once you decide to focus on time to delivery as an input, you’ve got to figure out how to drive it.
You can keep going layers deeper. Time to delivery might be influenced by the location of distribution centers, contracts with package carriers, warehouse staffing levels, and so on.
Even THOSE measures have layers of inputs.
This becomes important for how you coordinate efforts. As a leader accountable for a big goal, you’ll want to coordinate efforts across your team across those inputs.
You’ll want to ensure you’ve got dashboards showing how you’re scoring across all of them. You’ll want to assign autonomous teams to focus their efforts on moving those input metrics.
It’s the beginning of how you coordinate action across a large team to achieve big things.
So you’re convinced on how important input metrics are, but how do you find them? I’ll share three techniques that can be used in combination with each other.
Finding Inputs: Systems Thinking
The first technique is a way of thinking. it’s being aware that you’re trying to influence a system and conceptualizing it as such.
It’s helpful to think of your environment as a machine. What’s the fuel? What’s the exhaust? Are there repeatable loops? What are the boundaries of the system? What are the forces at play?
Drawing is a useful tool. You can use mind maps, fishbone diagrams, value stream mapping, or literally drawing all the pieces involved and their relationships to each other.
You’re doing this to build an increased awareness and intuition of the system. From there you’ll be able to develop hypotheses on the inputs.
“Success is not a goal to reach or a finish line to cross. It is a system to improve, an endless process to refine.”
When you already know your system, or when you have an abundance of data and metrics, it may be helpful just to jump to correlations.
Correlation testing is a science in itself, but what you’re doing is checking whether your potential input measure seems to have a predictable relationship with your output measure.
Always remember, correlation is not causation! Just because you see two variables tracking along with each other does NOT mean that they’re actually related to each other.
I mean, I guess eating less margarine could cause couples to stay together. Click on the image to view more Spurious Correlations.
One of the confounding factors with correlation testing is that the effect of an input may not be close in time and space to the output.
For example, you may be spending hours each day studying a language, but your score on the proficiency test won’t improve until much later. This might be missed in a simple correlation test (it would seem like all that studying has no effect).
Just like with systems thinking, correlations are good at generating hypotheses for further testing.
Finding Inputs: Experimentation
One final technique for finding inputs is to actually do some experimentation. Here you’re trying to find causation by doing a little bit of a controlled experiment.
You pull the input lever and see if the output moves. There are many ways to approach experimentation, but the main goal is to increase your confidence in - and maybe even your mathematical sophistication with - the relationship between input and output.
The size of "eruption" in this science project is directly proportional to the amount of, and distribution between, baking soda and vinegar.
Call to Action
What’s your number one goal in front of you?
How well do you understand your inputs? Are you poking around in the dark, or do you have a precise mathematical understanding of how inputs affect the output?
If your confidence and precision are on the low end, do some work on the techniques above. Do some system mapping. Pull data and look for correlations. Run an experiment to test causation.
Place your input metrics on a shared dashboard for the team if you don’t have one already.
I love this type of work, so I’d be happy to chat with you about it. Is there anything you want to explore further? Anything I can clarify for you? Email me at heykev@kevinnoble.xyz.
