My morning news scan predicts a long winter. Fuel prices in Canada are expected to rocket past CA$2.25/litre (US$6.20/US gal) by January, just 60 days from now. Interest rates will continue to increase. At the same time, house prices may come down, reducing homeowners’ net worth and ability to borrow, while rents will continue to rise. Federal and provincial governments are giving mixed signals about how they plan to respond. Some actions focus on short-term relief at the cost of the longer term, while others do the opposite.

War in Ukraine will spark conflicts in other parts of the world due to food shortages or could spread in Eastern Europe if tactics get ugly. On the other side of the globe, a retired Japanese admiral warns Canada and Western countries to look closely at the situation in Taiwan, which can flair up at any time. Political instability in the US, Canada’s continental roommate, could encourage similar shenanigans here.

In 2020, the unthinkable happened as society retreated behind closed doors, bringing the economy to a halt. This disruption put the wrecking ball to many popular assumptions about the economy. It also gave us a taste of what awaits us as the effects of climate change are increasingly felt daily.

I do not doubt that we are just experiencing the storm’s beginning.

Startup founders tend to view the future through rose-coloured glasses. This is expected because challenging the future is risky, uncertain and dangerous to one’s health, whether financial, mental or physical. This is why very few people leap into entrepreneurship. 

However, startup founders cannot afford to maintain an overly optimistic view of the world. Macroeconomic and microeconomic forces do not spare startups. Sooner or later, founders need to face the future with their eyes fully open.

Netflix recently announced price increases of 20% for their individual tier. Which makes me wonder: why this increase, and why now?

It’s not like there are supply chain or resource issues that are raising their input costs. These services are not adding new features which add to the offer’s utility for me. There are no currency issues, new taxes or labour cost increases that merit a price hike at this moment.

I also find the price hike timing strange as most of their customers are experiencing the impact of high inflation eating into their discretionary income. As people have less money to spend, the perceived expense of these services as a proportion of the money left over after the essentials makes the price increase even more apparent.

How are digital goods priced? The difference between digital business models and more conventional brick+mortar+equipment (BME) models is that the biggest costs are upfront: building the infrastructure. Once this is done, the marginal costs of adding customers are minor. In conventional BME businesses, your physical plant can only handle so many customers or build X widgets, then you need to build more physical facilities.

I’m struggling writing my chapter about why the Hockeystick growth curve is a mirage in today’s post-pandemic unpredictable world. Then I read this. Basically, fast-growth business models “all turn out to face the same main pitfalls: a misplaced faith in network effects, low barriers to entry and a dependence on someone else’s platform.”

1. Network effects are real but have limits: building a network in one city does not necessarily mean better service in another. Incremental capacity does not translate into incremental value (what’s the added value of one more Indian restaurant on Doordash or one more driver on Uber?);
2. Low barriers to entry: On one hand, the tech stack is cheaper and cheaper, allowing copycats to quickly steal traffic. On the other, customer acquisition and retention costs climb because of competition;
3. Dependence on someone else’s platform: Reliance on the gig economy means loss of control over quality and customer satisfaction. Or you may be dependent on another platform, for example if your business relies on Facebook, Spotify, AirBnB, or the iOS/Android duopoly.

The bottom line is that your business model must evolve with the stage you are at. The strategies that get you in the game need to change as you scale, then change again as you achieve your first, second and third levels of consolidation.

What went wrong with Snap, Netflix and Uber?

Despite superficial differences, digital darlings’ business models rest on the same shaky pillars

The Economist

Link:: https://www.economist.com/business/2022/10/31/what-went-wrong-with-snap-netflix-and-uber

[Panel Question #2: How can you ensure that you have the correct data in sufficient quality and quantity to carry out an AI project]

Data is the lifeblood of an AI project. In a perfect world, an algorithm would train on all the data that ever existed. However, it still would not be a perfectly trained algorithm.

This question is a hot research topic. The answer depends on several factors, such as the type of classifier, the number of weights, and the data quality. If there is insufficient quantity and quality of data, the model will not achieve the desired accuracy. If there is too much data, the model will tend to overfit and not be accurate in edge situations. This is the most problematic because these are the cases where you most want accurate recommendations.

[Panel Question 1: How to make accessible the knowledge of AI researchers and experts to Quebec’s industries and SMEs?]

Transferring knowledge from academia to industry is a long-existing problem because each operates in separate bubbles. Academia wants to solve cool technical challenges, while businesses want to maximize profit. 

Once a business reaches the point where it is making a profit from a process, this becomes a core capability, which can only be changed by risking the business’s cashflow. Of course, this is the last thing they want. This resistance is the main obstacle to corporate innovation.

There are three issues that come up when considering how to make accessible the knowledge of AI researchers and experts to industry and SMEs:

– The company’s willingness to innovate;

– Maintaining the company’s core vs innovating at the edge; and

– The innovation value chain, or how new practices diffuse through the organization.