👓 Freelancing, networks and IT - the new core strategic focus
I absolutely enjoyed Laetitia Vitaud's writings on how the rise in freelancing is pushing companies to re-think corporate strategy
and HR. Externalising or internalising activities has long been a key strategic concern for companies, with the consensus being that companies should focus on their core business and outsource everything else to other specialised companies. However, with the development of large digital networks and marketplaces, and with the advent of services like DocuSign
, a firm's transaction costs (related to information, to negotiation, to contract enforcement) have been fallen massively, hence this dogma must be revisited. As companies must now provide the best possible customer experience by controlling critical areas in the value chain, they can now benefit from the skills of the freelancers to in-source some of the activities that were previously outsourced (and hence out of direct control). The freelancer model gives rise to a question:
"What is a company’s strategic core
? Is it one line of business in particular or is it the company’s ability to coordinate teams of different actors around a given project
Laetitia also writes separately that the blurring lines between what's inside and what's outside organisations is redefining HR as well
, as companies will have to learn to nourish long-lasting relationships in larger communities and freelancer-ecosystems, by embracing the project-based nature of professional relationships, and work in the digital age not being positioned as a lifetime engagement anymore.
Growing TAMs, disruptive innovation and its antidote
🚕 Successful digital marketplace strategies actually expand the Total Addressable Market (TAM) of the industries they operate in, in parallel with disrupting existing incumbents. This fascinating data-set from Kevin Kwok
shows how, for example, Uber and Lyft expanded the total number of monthly rides in NYC by being able to operate in underserved markets in the city's outer boroughs. As they grow, it is only normal to cannibalize existing taxi-rides within the center of the city. And it appears to be the same in music. The internet has unbundled music and saw the industry's revenues plunge. However, the business model of music streaming, which is a new way to create a bigger and better bundle, is actually expanding the TAM, as it improves both the value proposition for listeners and the revenue potential for the music industry.
🎵 📷 ARK Invest models that music streaming platforms could actually boost the music market by more than 10x by 2023
. In photography, Canon started with expanding the market by focusing on amateur consumers. How Nikon, as a result, lost the leadership position to Canon in the market for professional photography is a very interesting story, illustrated by Steven Sinofsky
, involving technology transitions over a period of 30 or more years. Canon was going after Nikon from the underserved market, as they could not win over professionals, so they were forced to focus on mass-consumers and ease of use (with features like autofocus which were laughed at the moment of launch).
💉 There is, however, an antidote to this type of disruption. Ben Thompson argues that what makes today's tech platforms (such as Apple and Amazon)
so successful and immune to Clayton Christensen' disruptive innovation is their end goal, which is the perfect
These companies have educated their market to continuously prefer a superior user experience, which never plateaus but gets more and more demanding, hence the risk of overshooting
(meaning that in their chase for higher margins, their technology and products will progress faster than market demand) is non-existent. In Jeff Bezos' words, the customers' divine discontent
is the true moat against overshooting and hence being disrupted: because achieving the perfect user experience is a neverending goal.
But it is critically important for tech companies to strategically manage the context
as well, as otherwise they risk striking the responsive chord
of customers and easily turn their virtuous circles of trust in vicious ones. Network effects can be dangerous as well, writes Nicolas Colin
On Tesla, Uber, visionary CEOs vs. pragmatic markets and vestigial metrics
Facing a production-hell recently, Elon Musk declared (=tweeted) that excessive automation at Tesla was a mistake and that humans are underrated. This feels like an acknowledgement of the fact that large-scale car manufacturing is really hard, writes Timothy Lee,
reason why traditional carmakers like General Motors didn't achieve it (despite its relentless focus on full-automation in the 80s and 90s). In fact, it seems that Tesla is struggling just to match the efficiency of its more established rivals.
🚗 Steve Blank also argues that, if you want to understand the future of Tesla and Elon Musk’s role, we should look at the story of how Alfred Sloan replaced Billy Durant
from the head of General Motors in 1920. Billy Durant was a visionary and he founded the company that grew into General Motors at the turn of the 20th century, and was fired twice from its helm, both times because the company was over-indebted and risked running out of cash, mainly due to tight-integration, centralisation, inventory pilling up, too much speculation from its CEO and in general, a one-man-show attitude
that damaged the company. He was replaced by Alfred Sloan, who not only ran the company successfully for the next three decades, but also invented the "Modern Corporation" in the meantime, as he was the first to work out how to systematically organize a big company, putting in place strategy, measurements and principles of decentralisation.
🔥 So it is compelling to see how Elon Musk, after creating a whole new market and captured the imagination and fascination of consumers worldwide, might become the danger to Tesla (as the company is burning money so fast that there is now a genuine risk that it could run out of cash in 2018
), which maybe is in need of its own Alfred Sloan (Uber provides a more recent cautionary tale of not acting quickly to oust a value-destructive CEO: the company risked seeing its value plunge to zero before its board took the decision to remove CEO and co-founder Travis Kalanick, and replace it with Dara Khosrowshahi, who is charged with turning the scandal-plagued startup into a traditional company
—without sacrificing what made it successful.
🍭 Elon Musk argues that what matters most is the pace of innovation, while "moats are lame" and equity research is vestigial. Network effects can be one of the deepest and most enduring types of moat for many great technology companies, but not all businesses are candidates for a network effect approach, and Tesla, at first glance, seems such a company, hence why Elon might be downplaying the moat narrative. As per Matt Heiman, other types of moats exists in the digital era
: 1/ Scale - which has been a feature of business since the Fordist era, but in the Digital Era, the internet magnifies the importance of scale by removing the geographical constraints and reducing the capital intensity of growth (which is not really a feat of Tesla yet); 2/ Brand and 3/ Switching costs. ... Maybe his Twitter candy-rant
at Warren Buffet is some sort of brand-building.
📊 It could also be that, in arguing that Tesla is a digital company, Elon Musk is basically saying that the investors' financial accounting model cannot capture the principle value creator for his company
. Being a digital company, investments in its future are treated as expenses in calculation of profits. So the more a digital company invests in building its future, the higher its reported losses. Investors thus have no choice but to disregard earnings in their investment decisions. Or maybe he just doesn't like metrics, and he shares Professor Jerry Muller's theory that today's institutions over-rely on metrics, and this in turn creates nothing but short-termism
and economic stagnation.
🔮 Or maybe, Elon Musk understands the paradigm shift that is implied by building a company with Artificial Intelligence at its core. Strategy professor Ajay Agrawal has a very original view on the economic purpose of AI
: it lowers the cost of prediction
. Understanding this can help business leaders determing RoI for building on top of the technology. Drawing a parallel to semiconductors, which had the profound impact of reducing the costs of arithmetic, which had three main impacts:
1/ an increase in arithmetic being used within applications that were already using it;
2/ using arithmetic to analyse problems which weren't previously framed as arithmetic-problems;
3/ the value of arithmetic-complements went up and the value of its substitutes went down.
With the cost of prediction going down
, we can expect the same impacts:
1/ businesses will use more of it for traditional prediction problems (such as inventory management);
2/ re-look at problems from a prediction-angle (driverless);
3/ the value of prediction-substitutes will go down (human-prediction) and the value of complements will go up: data, human judgement (because what A.I is doing is unbundling decision making which is human prediction + human judgement), and action.
How Netflix Became a $100 Billion Company in 20 Years
Netflix is a beautiful example of a company that nailed all aspects
we discussed in this section: it understood that the relationship between employer and employee must be based on radical honesty, is project-based and therefore transient by nature; it made its mission to deliver superior customer experience (even if it meant disrupting its own DVD business via what was initially a poorer-quality product = streaming online); it used the internet to un-bundle and decentralise TV entertainment and build a more valuable bundle which increased the total addressable market for video consumption; it focused only on a single North Star metric (rather than optimising individual shows to maximise the number of viewers, it instead optimised its business for movies watched per individual user); this in turn led to key product initiatives in the areas of prediction, such as its recommendation AI algorithm; it used all this infrastructure to vertically integrate in order to continuously chase the divinely discontent customer.