Henry Ford + TikTok = Business Analytics?


Hope everyone had a good weekend! For all the non-basketball fans out there, don’t worry it’s almost over, but for now the madness ensues.

With my original champion already eliminated, I’m placing my next bets on UConn.

Kingsford Charcoal

Some of you may be familiar with the story of how Kingsford Charcoal was started, but if not, here ya go.
Edward Kingsford worked for Henry Ford back in 1919, only 15 years after the company was started. He was part of the procurement team, and in charge of finding lumber that would be used for the Ford Factory in Detroit.

Lumber was a crucial piece of the puzzle; it was burned to forge iron, form metal used on the Model T, and wherever else it was needed across the plant.
But along with burning so much wood, came an insane amount of waste (the embers, coals, etc.) that was just thrown away. Ford and Kingsford sat down one day and brainstormed how this waste could be repurposed, and just like that Kingsford Charcoal was made.
Condensing all the embers and coals resulted in what we call charcoal today, perfect for firing up the grill.
Just like that, Ford had found (more like created) another income stream through circular economies and upcycling.
This business was initially kept under the Ford brand but was eventually spun off and named Kingsford in Edward’s honor.
You know what they say, one man’s trash is another man’s treasure.

So many circles

While Ford my have been the first large scale example of success for these circular economies, we see them everywhere. Without even noticing a lot of the times. Stuff like using old tires for the rubber in artificial turf, shredding warped and knotty word for mulch, turning byproducts of the petroleum industry to form plastics, and even taking pulp from restaurants and juice bars and making chips.
All of these examples take the waste from another process and make it the primary selling point of their own brands.
Circular economy, upcycling, call it whatever you want. The point is that it’s a win-win, with the vendor being able to sell something that was once wasted (bonus revenue) and the buyer getting a discount for important supplies (saved cost).
And it’s often more sustainable than the current processes too.



But there’s a new commodity in town

The examples that I provided outlined this process through things that are tangible, but there are two new commodities that everyone has been fighting over recently: data and attention.
Data and attention have proven the be the most powerful and sought-after commodities in the world, for obvious reasons.
Media companies that have your attention can better sell products through advertisements, shape public opinion, take time away from competitors, and gain loyalty.
And it’s a similar story for data. Companies that are allowed to collect data understand consumer behavior and can create more personalized ads, understand trends in attention, can use that data for new products of their own, or just sell the data to companies who do use it.
As with anything there are good and bad examples. A good example? A Fitbit, Apple watch, or some other bio wearable. They don’t fight for your attention, but they collect more data than you may think regarding your health. However, most of that data is used to improve health tracking like alerting 911 when you’re in an accident, or telling you when your heart rate is too low, etc.
A bad example? It seems as though the US has identified TikTok as a villain given the congress hearings, so we’ll roll with it (for the record, still haven’t been on since Jan 1 and don’t miss a thing). TikTok is being accused of putting user data at risk and being detrimental to attention span, self-esteem, and other cognitive abilities.


Putting these things together

I don’t really have a point in bringing all of that up other than giving y’all some background and setting the stage for an idea.
Circular economies rock, and so does publicly available data. Wouldn’t it be cool if somehow, we could combine these ideas?
Obama thought so.
Under the Obama administration data.gov began, which is now one of the biggest public data banks available. Released by the White House regularly, this data base was created to help start businesses by providing previously unavailable insights on anything from macroeconomics to macro agricultural trends.
This was especially pertinent when during the Great Recession, when it was started.
And lots of businesses have come from this. Major, venture backed companies like Yield Monitor and Cowealthy were built by using this data.
Apple, John Deere, Fitbit, and Bloomberg have all admitted to using it as well for market insights.
Only one thing. You must have a fresh perspective/new way to look at the data. You must see something nobody else does within the numbers.
What do I mean by fresh perspective? Well do you see a young or older woman here?

If you see a young woman (don’t worry, I’m still looking for it too), then you may have it. And if you’re good with numbers, then it may be worth trying.

The Joe Holka Show


With March Madness in full swing, the World Baseball Classic, the NFL draft, and baseball starting up now’s as good a time as ever to start listening to The Joe Holka Show! It’s a great blend of information and conversation, almost like you’re sitting across from him, and it’s 5 star rating on Apple Podcast speaks for itself. Go check it out! #ad


Final thoughts

TLDR? This part is for you.
Basically, that was all a long-winded way of saying a “business analytics” company is just one that found a new way of looking at data in an age where data is hot. And the data under the microscope almost always comes as the byproduct of another process, AKA circular economies.

For example, CB Insights, a company worth over 50 million dollars, is just really good at rebranding, repackaging, and dressing up data that is largely already public. The founder calls it “sawdust data”. Creating a picture and taking information from the sawdust made by bigger processes, hence the picture at the top.

If you’re looking for more examples of how to look at data differently or go one layer deeper, I’d recommend the books Freakanomics and Superfreakanomics.

That’s all.

‘Til Friday.

from, matt

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