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Simple, Not Easy
Takeaways from Chris Curran after a 32-year tech career
A Note from Andrew
It’s a big week for the Kazlow family - I’m excited to share that I’m currently out of the office on paternity leave! I had time to prepare 3 lessons learned and a few interesting links before baby came, but I’ve also asked Professor Chris Curran to share some of his experience with us. I think you’ll enjoy learning from him - I certainly have.
I’ll be back in the saddle next week.
Gratefully,Andrew
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Gratefully,Andrew
Two Lessons
I just finished my third year teaching in the entrepreneurship program at Texas A&M’s College of Engineering. After a 32-year career helping companies sort out how to get value from technology, I decided to pass on some of what I learned to students and maybe help them short-circuit some of the things I learned the hard way.
It’s a very clarifying exercise to answer a question like “What are the most important things you want to pass on to college students?”
My answer to that is simple:
IterateBreak up the time you have available into small chunks and use each chunk to work and create the best answer given available data. Then get some feedback from your customer, boss, or teammate and repeat until all the chunked time is gone. Don’t wait until your time is almost done to prepare your answer or get feedback.
FocusMake sure you know what the problem is you are solving. This applies to a small engineering task as much as it does to your first product launch. My approach to work dramatically changed when I shifted my focus from what to why.
Iteration and focus are not easy for technical founders (and university engineering students!) who are makers at heart and want to build stuff. It takes discipline and maybe more importantly, the belief that to build a business you must make something people want to buy.
Let me give you an example of someone who’s managed to succeed at this.
Scratch Your Own Itch
A few years ago, I met Logan Havern at an Aggie Angel Network meeting. Logan is an Aggie and technical founder/CEO of Datalogz. As an early investor and advisor to Datalogz, I’ve had the opportunity to closely follow his journey and have been impressed with the clarity of the problem they are solving. Datalogz is solving the problem of “BI Sprawl,” shorthand for the proliferation of data storage, reports, and other business intelligence assets that get created by the gigabyte but hardly ever reviewed and removed if not used resulting in wasted cloud spending. Following the “scratch your own itch” approach to problem discovery, Logan experienced the problem firsthand as a data engineer for an airline.
Logan maintains Datalogz’s focus on deeply understanding their customers’ problems through an iterative process of building, testing, and learning.
But all the focus and iteration won’t fix a bad problem.
Problems Worth Solving
Kevin Hale a Y Combinator partner, described five attributes of good problems as Popular, Growing, Urgent, Expensive, Mandatory, and Frequent. When we talk about this video at the beginning of our Lean Startup classes, we begin filtering student ideas by simply asking “Is this an urgent problem?” and “Do a lot of people have it?” I’ve also used these simple questions as my first diligence checkpoint.
Datalogz is addressing cloud computing costs growing 20%+ YOY - a real issue to manage. However, when generative AI hits mainstream enterprise use, look out. Everyone will want to ask questions and analyze their data using plain English. Managing the corresponding costs will create an urgent problem for most enterprises.
It’s simple to ask these questions. But, answering them requires engagement with customers and a willingness to rethink and change the problem you are solving, who you are solving it for, and how you are solving it.
Not easy.
Andrew’s Weekly Observations: 3 Lessons Learned
Don’t let perfect be the enemy of good - just make a decision.✂️This week I spent way too much time agonizing over the minute details of a simple flyer we’re handing out at an upcoming event (come see us at the Angel Capital Association Summit on May 13-15!). I finally cut myself off from any more tweaks and let good enough be good enough.
Angel investors each have a unique approach.👼I met with two different angels over the last 2 weeks to gather feedback on our work and how they approach angel investing. Both were very different. This quarter I’m aiming to interview 10-20 angels about their approach - interested in discovering what patterns emerge. Want to be included? Shoot me a note.
Ask for help.🙋♂️We’ve been trying to hire an admin/VA for a few months now. After failing to find a good fit multiple times, I asked for help from a friend. They were kind enough to share 6 pages of notes and a walkthrough of exactly what they did. Thanks to that coaching, I’ve made several adjustments to our approach and am much more optimistic going into the next attempt. Fingers crossed!
Andrew’s Weekly Links: 3 Things I Found Interesting
Thanks for reading, have a great week.
-Andrew & Chris
If you enjoyed this post, please share it with a friend, colleague, or anyone else who may benefit.
P.S. - I (Andrew) recently finished creating The Angel Network Toolkit: 90 Resources for Cultivating a Thriving Community of Pre-Series B Investors, and I’m sharing it with anyone who refers a friend.
How did we do this week?
About Andrew
I cultivate flourishing.
I'm also the CEO of PitchFact, where our mission is to cultivate flourishing specifically through efficient and collaborative early-stage diligence. I'm a proud husband, grateful father, and honest friend. My love languages include brisket, bourbon, and espresso.
About Chris
Chris Curran is a Professor of Practice in the College of Engineering at Texas A&M University. He works with engineering students as they learn how engineering fits into established and start-up businesses. He also directs the Engineering, Inc. student incubator where members apply Lean Startup concepts to explore their ideas in the context of a commercial business.He was co-founder and CTO for PwC’s New Ventures SaaS incubator focused on identifying and growing new digital products. He established a Lean Startup environment from scratch that incubated and launched 8 commercial software products, leveraging practical applications of cloud-based open source tech, several using advanced machine learning and NLP.