The Data Daily
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5 days a week since May 1st, 2023.
I wasn't sure this day would come
One year ago today I launched something.
May 1st, 2023 was the first edition of this email - The Data Daily. A brave 35 people received the first email that day and I'm so grateful for that group (only a few of those people were my parents and family members)
There are just a few more than 35 people here now. Thank you so much for all of the replies over the last year. Without a doubt, your replies are the best part of this journey. I've made more than a few friends from this simple email.
I've written 250 daily emails. And I'm really looking forward to the next 250.
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Today, May 1st, 2024, I'm excited to launch something else. A podcast.
A podcast for conversations about data and leadership at mission-driven organizations with practical insights into the intersection of non-profit mission, strategy, and data.
Episode 0 is available now. My friend Troy has joined me as my cohost for this new adventure (and dad jokes). We have several guests interviewed lined up for the podcast and are excited to share the conversations with you. It won't be daily - expect episodes every other week.
I'm glad you are here,
Sawyer
from The Data Shop
p.s. If you missed the Data Roundtable about LLMs on LinkedIn live yesterday you can catch the replay.
They had bigger boxes than expected.
Yesterday, we talked about making decision in boxes. It’s our naturally developed pattern for our brains to manage an increasingly complex world.
This framework is also known as Bounded Rationality.
We make rational decisions within boundaries.
Moving into leadership from an individual contributor requires increasing the size of your boxes.
Similarly to your personal life, if you go from being single to married with kids. Your boxes have to get bigger because your decision-making now has to be optimized around more than just yourself - it has to include your spouse and children.
The brave part about being in leadership, and the quintessential characteristic of the best leaders, is to operate in the next level larger box.
Winston Churchill, Gandhi, Martin Luther King Jr., Nelson Mandela.
Were able to think and make optimal decisions in a larger box than expected. Beyond their country, people group, religious circles, or race.
A small step for you today in your role as a leader (or individual contributor) is to reflect on the boundaries you currently have on your rationality.
Do you fight for your team's budget without consideration of larger company needs?
Have you ignored challenging issues present in other areas of your organization because they didn’t impact your team’s success?
Have you pushed back on new initiatives that would limit your influence?
The question isn’t whether these actions were right or wrong. The encouragement is to reflect on what boxes you decided from.
Great leaders will step into the next larger box size.
You begin to define your team’s success based on the success of the whole.
We don’t win if you don’t win. We win or lose together.
That’s partnership.
And that's leadership.
Sawyer
from The Data Shop
Small boxes, backstabbing, and big scissors.
"Why did they backstab our team?"
"Why did they ignore this information?"
Why are we rowing in different directions?
"Why can’t we all agree on what the goal is?"
"Why does it feel like we are competing against ourselves?"
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You’ve felt this before at your company. The data objectives are ignored in favor of other goals. A clear decision is pushed aside for something that feels irrelevant to you.
There’s a good reason for this. Humans are great at thinking in boxes. It’s a necessary coping mechanism for survival in a complex world.
We’re wired to draw boxes and to optimize our decision-making for what’s inside our box. We make choices based on what’s best for what’s in our box. Both biologically and psychologically it’s nearly impossible for us to do otherwise.
In your personal life, your primary boxes might be yourself, your family, your neighborhood, city, state, country, and planet. You make choices based on what’s in the best interest of the smallest box first and work your way out. As you move out, it gets increasingly hard to make optimal choices that take into account both the smallest box (yourself and your family) and the larger boxes (your country and the planet).
When buying groceries we cannot simultaneously make optimal decisions about my family's health needs and financial constraints, while also thinking about the economics, environmental, and political factors of my state, country, and planet.
To handle this overload, our brains make simple optimizations. We allow ourselves to be rational in only the smallest boxes.
This shows up constantly in the workplace.
Our boxes are - ourselves, our team, our department, our company.
Just as in our personal lives, we struggle to make optimal decisions for all areas of our company, and so we focus on optimizing the smallest boxes.
Which leads to infighting, contradicting goals, frustrating leadership meetings, and a lack of progress.
What makes the role of CEO, President, Prime Minister, etc. so incredibly hard is to make decisions about very large boxes constantly!
So how do you manage these boxes in your workplace?
Let’s talk more about that tomorrow,
I’m here,
Sawyer
from The Data Shop
A cocktail of biases, blind spots, and bad incentives
More important than data literacy.
than tech stacks
tech budgets
or org headcount.
While your leadership might lack any skills, priority, or growth in any of those areas, that is not what’s lacking.
An organization that takes data seriously doesn’t need to spend time on data literacy courses.
Or waste money buying new tech tools.
Or splurge on hiring the best and brightest.
The gap, for both data leaders and executive leaders, is a coherent model for decision-making.
They are constantly making decisions. About what to buy, sell, grow, disband, adjust, scale, prioritize, and eliminate.
How does data play a role in your decision-making framework?
Most leaders trust firmly in their experience and the expertise of the leaders around them. But it leaves them exposed to a variety of biases, blind spots, and bad incentives.
An organization that prioritizes data will
→ Know their outcomes
→ Make decisions that close that gap in their outcomes
→ Use data to make the best decisions possible.
If you want data to be meaningful to your org. Connect it to the decisions that need to be made. And connect those decisions to the ultimate outcome your organization wants.
I’m here,
Sawyer
from The Data Shop
They said it. Not me.
We just wrapped up the first cohort for The Technical and Strategic Data Leader. It was a 6-week intensive cohort learning experience for data leaders, data architects, and those responsible for data at their organization.
Our first cohort was filled with Directors, Sr. Managers, VPs, or Solution Architects focused on growing and becoming great data leaders.
So, how did it go?
Don’t listen to me. I’m biased.
Here’s what the cohort participants said they got from TSDL:
They learned they aren’t alone:
“A lot of the issues we face are not isolated to us and that other data leaders have the same issues/concerns”
“I have made some connections that I will keep for a very long time.”
It was a benefit to be “able to hear insights from peers”
“Expanding network with professionals” was valuable.
They got direct access to mentors:
The small cohort experience offered “access to instructor expertise“and the panel was “highly qualified”
They engaged with great content:
“The content was very robust”
“All of the material was great”
“The comprehensive agenda from general data team setup to architecture overview to specifics on delivering dashboards was great.”
“Content was very relatable and applicable to my role.”
“Increased knowledge on the tech side as well and a better understanding of guiding an org through the decision process”
I received a “high-level understanding of the strategic place of data in an organization”
“I found the course very informative and quick paced. Good value for the money”
The Overall Experience:
“It was well-organized and well run.”
“The TSDL was a great experience where I received a professionally curated education on various topics data leaders need to know.”
“The discussion time during the calls were great and led to good conversation. “
100% said they would recommend the TSDL to others.
Do you feel like you missed out? Don’t worry. I got you covered. Planning for TSDL #2 is in the works now. We can only take a small cohort.
Want to be the first to know about the launch? Want access to registration before anyone else? Want early bird pricing?
Click here to get on the waitlist.
We will announce dates in the next couple of weeks.
I’m excited,
Sawyer
Before this moment I never cared about the geometry of a bike
At the beginning of this year, I wanted to buy a new mountain bike. My old one was…well very old… and falling apart.
So I started visiting bike shops. The first shop I went into was empty except for a lonely sales rep. The rep wandered over to me, asked a little about what I was looking for, and then showed me a couple of bikes on the wall. I asked a few questions. She answered. It felt like a totally normal experience.
Then I went to another small local bike shop. The owner, Ryan, met me when I walked in. He asked the same initial question as the last sales rep. But something was different. Within 30 seconds of talking with him, you could tell – Ryan loves bikes. He didn’t just point out a couple of bikes for me to look at. He pulled them off the rack, squatted down, and talked me through the geometry of the bike, a bit of the history of how mountain bikes have developed over the last decade and his favorite features of this bike.
Oh, and it turned out we both road the same trails and he described to me what a feature of the bike would feel like while riding on a specific section of that trail.
Then he shoved me out the door and told me to take it on a test ride around the block.
I didn’t look at any other bikes. Or other bike shops. Ryan had transferred his love of bikes, the sport of mountain biking, and his passion for the intricacies of this particular bike.
When I got back from my test ride I bought the bike.
Selling is about transferring emotions. Which Ryan did masterfully. He cared deeply about how I would experience the bike. And it worked.
Here’s why this matters for data.
We spend most of our days in data trying to get business teams to care about data.
“Look at this report.”
“Here I built a new view.”
“Did you see the results of this ML model?”
But they don’t care about data. They care about the feeling of what data will give them.
Confidence in their next decision.
Relief in knowing their campaign results.
Clarity about their team's performance.
Excitement about the direction of their program.
Those are feelings people will buy.
It was good to see you today,
Sawyer
from The Data Shop
Taking your next step with data – New offer
You see the value of data.
You understand the important data in decision-making
You know how data can help make progress toward your desired outcome.
But you are trapped.
Stuck.
Unsure how to execute with data. Spreadsheets are everywhere. Manual processes rule your data kingdom. People don’t know what information to trust. So, they don’t trust any of it and instead make decisions with their gut.
Oof.
I’ve seen this in organizations of all sizes and industries. It’s an epidemic. You are not alone.
What I’ve also seen is the transformation when people are challenged, trained, and equipped differently with data.
My focus is non-profits, not-for-profits, and mission-driven organizations. Organizations that are driven by social impact and changing communities for the better.
These organizations shouldn’t be left stranded with data. If any group should take data seriously it’s the people who have the opportunity to transform our communities.
So I made something for you (I hope you like it).
Making Data Matter 101 – A Power BI Launchpad for Nonprofits
A four-day workshop to take your team from zero to data-capable. It focuses on understanding the role of data in an organization and decision-making. But then it gets hands-on with a data tool Power BI that can transform the way you think and act with data.
The use cases, terminology, and conversations are designed specifically for mission-driven organizations. The days are filled with interactive discussions, hands-on practical skills, and personalized coaching and mentoring.
Module 1 – Strategy and Purpose of Data
Module 2 – How data moves through an organization
Module 3 – Getting and Transforming Data
Module 4 – Data Models and Making Data Meaningful
Module 5 – Calculations and Metrics
Module 6 – Data Visualization 101
Module 7 – Reporting and Data Storytelling
Module 8 – Scalable and Sharing Data Across Your Organization.
Before this workshop, students are:
-> Managing numerous Excel spreadsheets.
-> Facing constant manual processes to analyze and deliver data to their team.
-> Hoping for more scalable processes that allow them to do more of the work they love.
-> Wondering what else is possible for their data but feel trapped in their current tools.
After this workshop you will be able to:
-> Connect to, import, and transform data from a variety of sources.
-> Define business rules and KPIs.
-> Explore data with powerful visualization tools.
-> Build stunning reports with Power BI.
-> Share dashboards with your team and across your organization and publish them to the web.
I only have availability for 1 per month. More details are available here.
Hit reply to get started.
Sawyer
from The Data Shop
I'm not playing games. It's simple but not easy.
Why do we model data?
Because it helps us make good decisions.
Why do we use source control?
Because it helps us make good decisions.
Why do we visualize data?
Because it helps us make good decisions.
Why do clean data?
Because it helps us make good decisions.
Why do we create prediction models?
Because it helps us make good decisions.
Why do we want to make good decisions?
Because it’s how we get the outcomes we want.
I'm here,
Sawyer
from The Data Shop
p.s. Open Office Hour today from 2-3 pm ET. Stop by to say "Hi" or chat about data. Open only to people on this list. Here's the link to join.
This is 100% NOT about complacency.
Is it good enough?
How clean does the data need to be?
How fast does the pipeline need to run?
How easy should the visualization be to read?
How many data sources do we need to integrate with?
----------------
Clean enough, fast enough, easy enough… so that the organization can make their decisions.
Ease. Quality. Speed. Quantity. Are all relative and will never be at 100%.
How far you go is based 100% on what decisions and outcomes are required.
Starting at nothing? A little bit can be huge.
Perfection won’t help your organization if all it needed was “enough”.
This isn’t complacency.
It’s being outcome-driven.
I’m here,
Sawyer
from The Data Shop
p.s. Open Office Hour on Monday the 22nd from 2-3 pm ET. Open only to people on this list. Drop in and say "Hi". Chat about data or whatever else is on your mind. I'll send a link to join on Monday morning.
Before you curl up in the fetal position
You are growing.
Fast.
Congrats!
Savored the moment a little bit. In time, you will come to terms with how growth is straining, stressing, or cracking your data team.
Here are 4 ways growth knocks your data team off balance:
1. As business units grow the demand for analytics, reporting, and data will grow. Developing a mature business intelligence plan will help your team scale the insights and data products you can deliver.
2. New business divisions and software platforms mean new data sources. ETL processes that can scale to integrate with new systems rapidly will quickly determine whether your data team is drowning to thriving.
3. When a production pipeline fails more people notice. Downtime becomes more costly as more people become more dependent on your data. Having change control and DevOps processes established can minimize downtime.
4. The team that got you here may not get you there. The number of seats and arrangement of the chairs changes when rapid growth hits. Determining how talent and team will adapt to growth is crucial.
You might be moving so fast you don’t see these things.
It's the growth inflection points that push us somewhere new.
Before you curl up in the fetal position here are 3 steps to take.
1. Clear your schedule for a day to assess.
It might feel impossible to clear your loaded calendar. But it's equally impossible to see the forest when you are face-planted into a tree.
2. Get outside eyes.
Someone who cares more about your success than your feelings. A manager from a neighboring department. A peer at another company. An outside consultant.
3. Roadmap
Yes, roadmaps tell you where you are going. But they also show you barriers and detours. Layout the landmarks and the obstacles. Have your outside set of eyes review it.
You got this. I'm cheering for you.
I'm here,
Sawyer
from The Data Shop
The BYOD was the best part
Last week I sat around a conference table with an accounting and finance team for four days.
Here’s what I heard (and saw):
“No way”
“Oh, this is awesome”
“Can we do this again in a few months?”
*draw drop*
“Why didn’t we know about this before?”
And…my favorite (from day 3)
“I had a dream about this last night”.
Through a four-day training class, I took a group of users from downloading Power BI for the first time on Monday to building scalable reports on their own data by the end of the week.
Of course, there were some slides and hands-on training labs, but the best part was the last day - What I call Bring Your Own Data day. On Monday, everything started theoretical. On Thursday, they were automating and dramatically enhancing manual reporting they had always handled in Excel.
It will:
Delight end users.
Save them hours a week.
Unlock numerous new possibilities.
Begin a new data culture at their organization.
Taking customers on this journey is one of my favorite things to do because the light bulb moments and the impact to their work is so instant.
Hit reply with BYOD and I’d love to tell you how your team can have the same transformation.
Sawyer
from The Data Shop
p.s. Open Office Hour next Monday the 22nd from 2-3pm ET. Drop in and say "Hi". Chat about data or whatever else is on your mind. I'll send a link on the day of.
You are wasting so much creativity
Here’s the thing.
If you are striving to allow your team the freedom to innovate and be creative, you also have to balance efficiency.
The act of creating is wasteful. It’s the opposite of efficiency.
But from a cost, performance, and business standpoint, efficiency is also important.
So how do you balance those two?
Try this on.
Create with waste. Deliver with efficiency.
Don’t constrain the act of creating or innovating. Rather, constrain, optimize, and improve the act of delivering that creation.
Don’t track the time your developers spend building a new feature. Rather optimize the time it takes to merge, test, and deploy that feature to prod.
Don’t track the process for developing data visualizations. Rather improve the effectiveness of receiving feedback from stakeholders and the time it takes to complete iterations.
The more you improve the delivery process, the more capacity you have for creation.
Think about the different areas your team creates in and the core areas where your team delivers.
Enable space for the first. And pursue efficiency in the other.
It was good to see you today,
Sawyer
from The Data Shop
p.s. Open Office Hour next Monday from 2-3pm ET. Drop in and say "Hi". Chat about data or whatever else is on your mind. I'll send a link on the day of.
It’s a red herring
Things that slow us down:
Fear of making a wrong choice
Uncertainty about next step (analyzing is easier than making progress)
Belief that you won't get the support you need if you make the decision
Lack of clarity about the desired outcome (so how could you make a decision)
No one knows who should do what or when because communication has stalled.
People are stubborn about making changes (because it threatens their security in their knowledge)
Doing things a different way each time
A slow moving data team is not a technology problem.
It’s a leadership opportunity.
A people challenge.
And a process issue.
Spending your time focusing on technology is a red herring that’s distracting you from the hard conversations and the real work required in your people and processes.
I’m glad you are here,
Sawyer
from The Data Shop
Most people shouldn’t lead
The role of leadership is to move from 10,000-foot to on the ground and back.
Your team may not ever care about the 10,000-foot view.
But you have to.
As a data leader, this means you have to care about department-wide strategy.
Even if the individuals on your team don’t.
You have to care about how your team is incentivized or disincentivized.
Even if your team isn’t aware of why that matters.
You have to care about closing the gap on organizational objectives.
Even if your team is only worried about punching the clock for 40 hours.
You have to care about long-term technology choices.
Even if your team would rather pick the simple and easier option today.
You have to care about removing bloat from the code base and dashboard portal.
Even if your team doesn’t want to delete stuff they made 5 years ago.
You have to care about the passion and energy for excellence on the team.
Even if the team is comfortable with average.
Most people shouldn’t lead.
But if you are there, we need you to help us flourish.
Or we will all fail.
I’m glad you are here,
Sawyer
from The Data Shop
“Oh, I need more data”
I recently sat across a conference table with the president and owner of a small manufacturing company.
For years, he has run his company on spreadsheets. Sales, forecasts, inventory, customers, etc. We were spending the day introducing him to Power BI and allowing him to explore what it might do for him and his business.
Within an hour of picking up the tool and clicking through some demo workflows, the lightbulb came on.
He said: “Oh, I need more data”
I asked him to explain what he meant.
As he’s been collecting and managing data in spreadsheets, its overwhelming to manage too much data. The spreadsheet crashes. Even more so, it’s challenging to communicate to his team anything about the data if there are too many data points.
So for years, he’s been limited in what he can collect and communicate.
“Oh, I need more data” was filled with excitement about the possibilities. Now he saw data with a whole new viewpoint. And he wanted more of it.
That's what good data does.
It doesn’t overwhelm, frustrate, or confuse. It empowers and expands.
A good tool. A few good processes. Can unlock decisions and business opportunities they had only dreamed of.
You want more of it.
It was good to see you today,
Sawyer
from The Data Shop
Your data team is slow.
Your data team is slow.
And it’s damaging your organization in many ways.
Here are some of the things that happen:
The users are left waiting…and waiting.
Your team members are bored and frustrated
The leadership is rolling the dice on decisions without good information.
The best people on the data team are scrolling job boards looking for a role with more life.
Someone from the business who “knows some Python” pulls together their own info to get what they need without waiting.
A solution held together with duct tape and chewing games makes it into the hands of the execs.
No one can reproduce the “duct tape” solution.
Bugs in the data product show up….and take out a 30-year mortgage while you try to deploy a fix.
That business team keeps skipping the requirements gathering meetings you schedule.
They stop asking the data teams for new stuff because it will be “2-4 weeks”
The last three things the data team delivered haven’t been used.
Trust between (and within) teams evaporates.
Any of that sound familiar?
Your data team isn’t a lost cause. They are just lost in their own culture, processes, and disappointment.
It’s not a technology problem. It’s people and process.
As a leader, it’s your job to
Establish strategic direction about what is a valuable outcome.
Identify bottlenecks in the process.
Own where mistakes have been made in the past.
Take an incremental step towards something new.
That’s hard from inside the tornado. Outside eyes can help.
Call a friend, mentor, or coach.
Tomorrow’s a new day.
I’m glad you are here,
Sawyer
from The Data Shop
Constrain the "why"
You have choices when you measure or define success for your team.
1. You can place constraints around the inputs.
And define expectations about what items people can put into the process. Time, money, keystrokes, or attention.
2. You can place constraints around the outputs.
And define expectations about what should come out of the process. Code, reports, models, or documentation.
3. Or you can place constraints around the outcomes.
And define expectations about what end results should come from the process. Revenue, customer satisfaction, market capture, or student retention.
-————
The first two will give your team very restricted marching orders for their activities. But it will also produce a wide array of outcomes.
The third will give your team a wide berth of freedom and creativity in their activities. And it has the best chance of producing the outcome you want.
The first two will lead to burnout, budget cuts, and disappointed stakeholders.
The third infuses energy and innovation into the team. Consequentially, it also produces the most satisfied stakeholders.
Constrain the “why”.
Leave the “what” and “how” wide open.
Sawyer
from The Data Shop
Your measurements aren’t the problem
What you measure on your team or at your company isn’t the problem.
Measurements are benign by themselves.
You don't “get more of anything you measure”.
People don't “game every measurement”.
The crucial point is what you attach to the measurement.
What is the incentive around the measurement?
Are people being promoted, hired, fired, or receiving bonuses based on a metric?
Are budgets being cut, projects being approved, or headcount expanding because of a metric?
The measurement isn't the concern.
It's the incentives you attach to it.
When a measurement becomes a “KPI” then it’s measuring performance.
Once a team’s performance is attached to a number, then it will influence your team’s dynamics.
We should measure lots of things.
But very few measurements should have incentives tied to it.
I’m here,
Sawyer
from The Data Shop
If the purpose of data is making better decisions then…
What is a good decision?
How do we move beyond a platitude about “data driven decisions”?
We want data to be an influential factor in our decisions, but what does that look like?
How do we make ‘good decisions’?
A good decision includes at least this:
An intentional choice made with an appropriate level of consideration and time reviewing the relevant information - that will give you the best chance of moving you closer to your desired outcome over time.
Not passive, ignored, or unaware.
An appropriate amount of mental energy and time spent based on how reversible and severe the results are. More time is spent on buying a house than picking a paint color for the bedroom.
Take into consideration future expectations, historical inputs, and current reality
We know what we want and we are making a decision toward that end.
You do not judge a single decision based on a single outcome. Too many unknowns and luck involved. Not every time, but with enough time. There is always some level of uncertainty.
Consider your benign choices from today so far (what to wear, what to eat for breakfast, whether to read this email) and evaluate them through this pattern.
Most of the decisions we make are below the conscious level. But the more important the decision, the more crucial it is to have a decision-making framework.
Nothing will lead to perfect outcomes.
But over time, they will get you closer.
I’m here,
Sawyer
from The Data Shop
How to build your writing muscle
Since I started The Data Daily I've written 210 days (nearly every Mon-Fri since May). People have asked me how I keep going or if I will stop sometime.
I have no plans to stop.
Here’s how I keep going.
And four core steps so you can develop your own writing muscle.
1. Idea Capture
The biggest fear people have when thinking about writing is not knowing what to write about. It’s a false fear. You have so many ideas – you just don’t capture them. Any idea you had earlier in the week, earlier in the day, or even a few minutes ago will evaporate when you stare at a blank page.
You have to have a low friction and extremely easy method for capturing ideas. For me, that looks like two key things: A Notion doc called “The Data Daily – Ideas” and a paper journal. When I’m at my computer, ideas go into the Notion doc. But ideas hit me all the time away from my desk (in the shower, mowing the lawn, playing Lego, etc). So my journal (much to my wife’s annoyance) floats around the house so it’s available quickly to jot something down.
Ideas are simple – One or two sentences.
2. Set a timer
Writing is hard. Like exercise, it requires work and it’s exhausting. Just like you wouldn’t set out for a two-hour run on your first day of marathon training, don’t sit down to write for a couple hours.
Set a timer. Start with 10 minutes. Pick up a topic from your idea list. Write until the time goes off. Then stop.
It doesn’t matter if you are done with the idea. The timer says you are done so stop.
After a couple of weeks, you can up the time to 15 minutes.
3. Regular Practice
Consistency is more important than length of time. Starting with a short amount of time will make it easier for you to fit it into your schedule at an ideal time for you. For me, writing has to be the first thing in my work day. Starting at 8 am, I sit down and start writing. If I skip that time window, it’s 50/50 whether I will get any writing down that day at all.
I’ll make it easy for you. Block out 8:00-8:10 am (or whenever you start your work day) every Mon, Wed and Fri. Don’t look at email. Don’t check social media. Don’t look at your phone. Set your time and begin.
4. Publish
Writing is fundamentally about helping me clarify my thinking. But, the only way to get better at writing and thinking is to publish. This is the scary part. Put my words in front of other people, let them respond, ask questions, express confusion, or feel excitement.
Find a place to publish. You may not want to publish right away. That’s fine. Take a week or two of writing with publishing. But then you get your words away from your computer and in front of a reader.
There are so many ways to publish. Social media, blogs, newsletters, or emails, and several platforms are available for each of those. The style, length, and cadence of your publishing can vary a lot based on your platform.
Don’t overthink it. Don’t procrastinate coming up with a catchy name for your blog or exactly which platform to publish your newsletter on. Pick one. And publish. Publishing is the hard part. Picking a name, platform, or format is just noise right now.
And when you start publishing, hit reply and tell me about it. I'd love to follow along.
I’m here,
Sawyer
from The Data Shop