Uber’s market entry methods reveal parallel peer learning

Let’s start with how Uber handled January’s sharp drop in Nigeria’s Naira following the drop in crude oil prices:

One of them, is the price people are willing to pay for the Nigerian Naira (black market rates), which reflects its true value, and the other price is the one the CBN is pretending represents the Naira’s value (official rates).
What on earth does this have to do with a transportation network company?
Recently, users of the service started noticing discrepancies between their service charge, as reported by the Uber app, and the debit-card deductions reported by their respective banks.

So Uber deployed a cash payment option which they’d tested in Hyderabad, then Nairobi. When the dust settled in Nigeria, they introduced credit card payments.

“Oh wow! Credit card!” I hear you mocking. Except this is Nigeria, the country that Paypal excluded completely until 2014.

Image from Tech Suplex, who gathered some of Uber’s more candid customer responses.

Uber reacted quickly to the Naira drop, and came out ahead - in one of the toughest markets in the world when it comes to collecting money digitally.

Meanwhile, in China which is proving to the be the world’s early-adopter market for consumer Fintech, Uber’s actively engaged in the online payments war, rolling out Alipay and Baidu Wallet options.

Uber’s growth has clearly been execution focused, learning as it goes, and adapting to local markets.

I’m reminded of Nick Imrie’s comment to me over a few beers, years ago:

We used to have Lean Startup, we just called it “execution.”

Uber executes on different options for different markets. Execution flushes up challenges, which directs learning. Launch fast, and iterate, right? Not quite. That implies linear execution. As Uber shows us, the solutions to those challenges transcend markets. Their execution is parallel.

There’s an important distinction between this and the typical nail-it-then-scale-it approach that we’ve seen from US startups growing beyond their national borders. In most of those cases, by the time they’re going international, they’re executing on a US playbook that doesn’t work well in other places. Hence, they tend to grow by acquiring their international competitors.

Uber is executing in different markets, starting with playbooks from closer markets, then adapting them and sharing what works across markets. Their execution includes learning, and sharing that learning horizontally.


Interesting to see such examples of distributed learning, right? We've centralised a bunch of them in our upcoming book called Peer Learning is.... Follow the link for the Table of Contents, and more reads.