"Everything starts out looking like a toy" (No. 18)
Observations where data and systems meet by Greg Meyer
This week’s toy: the LIDAR sensor in the new iPhone lets you measure someone’s height easily. Today, one click measuring of things, tomorrow (perhaps), information for other systems to take action based on relative difference in space. Edition No. 18 of this newsletter is here - it’s October 31, 2020.
The Big Idea
The purpose of this newsletter is to continue to investigate things that seem simple now and might be something more than simple in the future. Today, they look like a toy, a gear, or a single purpose tool. How do you find the models for aggregating those tools into a more cohesive whole, and make a bet on which ones will become household names?
Photo by Georg Eiermann on Unsplash
My rubric for identifying opportunity is to look at the “stack height” - that is, the level of the technology relative to the technology that is mandatory to achieve a result - the difficulty in initial ease of use, and the type of person likely to find value in the outcome. But maybe that’s not thinking big enough in identifying a generally available idea.
When people adopt new tools, they look for something similar to what they have. Software hits often look like the digital version of today’s process, until they hit a breakthrough impossible in the current process. Examples of this include Maps > Garmin Map Devices > Apple / Google Maps > Maps + just in time prompts and real time information.
Thinking in World 2.0 Terms
Daniel Gross’s essay on World 2.0 Startups helps put this into context. He posits a “World 2.0” model to show the transition between physical process, 1st generation software or networked process, and the following results that look very different than the original but fulfill a similar user goal.
With Daniel’s model in mind, what other “World 2.0” startups are out there waiting to be created from actions that are already in place? I think one of the most promising places to explore is asking people to do fractional tasks. This could mean scheduling a meeting, enriching a company by looking up a value, finding an email address for a contact, or similar tasks.
Today, these are typically atomic tasks and are not related, so orchestrating them is not easy. There are security concerns, availability of resource concerns, and data concerns. So what would break through this?
Programming the Humans
When trying to optimize a process, we often look at a person doing that process who does it well and break it down into chunks. How does the person move from task a to task b? What information do they always gather? Are there any shortcuts they can make that gain more time without losing accuracy?
A World 2.0 model to organizing people to do things might take the world 1.0 idea of a schedule (get x to y done by a date), combine it with networked capacity (can I find people to do work who match my requirements, like UpWork or similar) and create a layer on top that will estimate how long completion will take to do this at a high rate of success.
This idea might map well to many different type of structured processes. If you create a template for “Customer Onboarding”, wouldn’t it be great to know exactly what resources are required, the sequencing of tasks, and the alarms to sound when things don’t happen in sequence.
If you don’t know where to start, a first step might be to digitize the boring stuff your company does often, like things that are handled in EDI (a company called Stedi is doing this).
What’s the takeaway? To find a big opportunity, look not only at the inefficient things that people do but also at how often highly variable things happen in your environment. When you see a series of tasks that never seem to get done the same way by multiple people, that’s an opportunity to optimize (or organize into a product).
We’d like to know …
Brands are now creating “virtual influencers” that are garnering followers on social media. Should these creations need to be labeled, or should the internet remain the Wild West where influencers are concerned?
Click the tweet to tell us whether you think labeling is needed for virtual influencers.
Links for Reading and Sharing
These are links that caught my eye.
1/ Robots choose better… - When considering utilitarian qualities, people appreciate AI recommendations. This effect doesn’t continue to emotional experiences, suggesting that AI-based recommendations might work better for retail than food reviews.
2/ ZOOOOOOm - Want to go 500 KPH? There’s a car that does that now. If you’ve got $1.9m in the couch cushions, you might be able to buy one.
3/ How does that news skew? - It’s now possible to measure the sentiment in online headlines at scale. There’s a lot of promise to using technology like this to identify whether news is center, left-leaning, or right-leaning. However, it also is highly dependent on the model used to train the data.
On the Reading/Watching List
Pete Souza was a presidential photographer for decades. There’s a new documentary out sharing his unique viewpoint - The Way I See It. It’s fascinating to get a peek inside of this world.
Ryan Singer’s Shape Up: Stop Running in Circles and Ship Work that Matters is a master class in user experience, usability, and building a product. The lessons in this book are applicable for everyone doing project work, not just those building a product.
What to do next
Hit reply if you’ve got links to share, data stories, or want to say hello. If you’re in the US, and haven’t done so yet, please VOTE in this year’s election.
I’m grateful you read this far. Thank you. If you found this useful, consider sharing with a friend.
The next big thing always starts out being dismissed as a “toy.” - Chris Dixon