To be sure, as a long-standing Silicon Valley darling and a key member of the Facebook, Amazon, Apple, Netflix and Google (FAANG) cohort representing US big tech, much of Netflix’s story thus far has been inextricably linked to technology. The company’s tango with machine learning and algorithms dates back to the early 2000s, when its proprietary Cinematch algorithm formed the basis of personal movie recommendations on the then NetFlix. com. In fact: Since 2010, the company has taken to publicly documenting various aspects of its multi-pronged tech strategy via deep dives and technical reports on its official Netflix Tech Blog (https://netflixtechblog.com/).
But to focus solely on Netflix’s visible tech updates would be missing the bigger picture. Rewind the days when Netflix played David to Blockbuster’s Goliath in the movie rental wars: one of its most consequential innovations was surprisingly rudimentary by modern tech standards — the iconic red Netflix mailing envelope. This patented design was essentially an ordinary envelope ingeniously modified with an extended flap that concealed a pre-printed return address underneath. Tear off the perforated strip and the same envelope could then be mailed back to the company’s distribution centre at no extra cost. The added space also doubled as additional advertising real estate. It was low tech by any standard — simple and unglamorous, yet undeniably effective.
Since its inception on April 14, 1997, Netflix’s trajectory can broadly be divided into several key phases (see Table), each marked by a consistent pattern of marrying innovation with visionary leadership; and operational excellence to drive sustained, transformational growth (see Chart 1).
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The first major turning point came when the company shifted from a pay-per-rent model to a subscription service around the turn of the century. The appeal of its new “unlimited rental” and no-late-fees business model was augmented by heavy investments in data analytics. The company began collecting and analysing user reviews, ratings and “queues” (essentially, desired rental titles) to fuel the aforementioned Cinematch recommendation engine — to predict what other users might like. Within the span of a year, Netflix’s subscriber count jumped from 10,000 at the end of the beta period to 300,000. After another year, when the company went public in 2002, it had accumulated around 600,000 subscribers.
In the words of business writer Thomas Redman, “where there is data smoke, there is business fire”. Throughout the 2000s, Netflix continued investing heavily to improve its algorithmic systems, most prominently through the launch of the Netflix Prize — an open competition offering US$1 million for the most effective collaborative filtering system. The contest drew widespread attention and successfully crowdsourced improvements to its Cinematch algorithm, though it turned out to be a short-lived initiative with no sequel after the competition came under Federal Trade Commission (FTC) scrutiny over customer data privacy concerns.
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By 2010, Netflix’s viewing catalogue had expanded to more than 6,000 movies and 500 TV shows, making the process of browsing through the database increasingly arduous. This was when the company’s data-driven approach proved critical in enabling strategic pivots. First, towards personalisation features such as tailored recommendations and curated movie lists designed to circumvent user choice paralysis. Netflix’s later transition to original content production in 2011 was similarly data-informed — with internal analytics guiding decisions not only about genre and themes, but also the choice of lead actors and directors. The company hit the ground running with its first true original series, House of Cards, a pitch-perfect political drama whose success is often accompanied by the anecdote that Netflix executives knew it would be a hit before filming even began.
Behind the scenes, the transformation across Netflix’s back-end infrastructure has been equally extensive — reflecting the same deliberate interplay between technology and operations. A defining moment came in 2008, when a major database corruption incident halted order shipments for three days. The failure prompted Netflix’s shift to cloud-native architecture, a move that proved prescient to the company’s eventual ambitions for a global footprint.
Seven years later, in January 2016, Netflix completed its full migration to Amazon Web Services (AWS) and launched streaming services in 130 countries simultaneously. This global rollout was only possible by leveraging Amazon’s distributed network of data centres to store, process and deliver large volumes of content at minimal latency. Supporting pivots such as the company’s decision to drop Microsoft Silverlight in favour of HTML in 2013 — the latter being a more standard-compliant, broader supported streaming technology — further accelerated Netflix’s global expansion, especially in markets where mobile devices dominate as the primary mode of internet access and content consumption.
Viewed collectively, these moves highlight one central truth: Netflix’s technological bets consistently reinforced — and were reinforced by — strategic business vision. Early investments in cutting-edge technology laid the foundation and enabled later shifts in business priorities — the operative word here being “enable”. In this sense, technology at Netflix was often a directional choice that was deeply tied to business priorities: the very act of selecting which technologies to adopt or abandon was itself a strategic decision that was guided by longer-term operational vision. The importance of this point is one that becomes apparent when comparing the set of case studies in the next section.
As for Netflix: true to form, its recent platform expansion initiatives do not rely on technological advantage alone. Notably, the company has moved into bricks-and-mortar ventures that focus on the experiential economy — opening its themed restaurant, Netflix Bites, at the MGM Grand in February — and plans to launch larger permanent entertainment venues branded as Netflix House later this year. Meanwhile, in its core streaming business, Netflix continues to lead the premium subscription video-on-demand (SVOD) sector — maintaining the largest market share (26%) and lowest churn rates, holding steady around 2%.
Retail’s big bet on AI: Walmart
The traditional bricks-and-mortar retail industry offers both a textbook case of success as well as a cautionary tale. As it stands, the task of integrating new technologies into the traditional retail industry, with its deeply entrenched legacy systems, is no easy feat. Yet, in recent years, big retail’s ambitions for an AI makeover have been an open secret. Case in point: This year’s National Retail Federation Big Show — the largest retail trade show globally — was themed “game changer” and opened with a joint keynote presentation from Walmart CEO John Furner and Nvidia’s Azita Martin, spotlighting AI as central to the future of shopping experiences.
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Retail giants to fast-food chains alike have begun leveraging AI for cost and efficiency gains. In this realm, Walmart stands head and shoulders above its peers for executing one of the most successful digital transformations in recent memory (see Chart 2). Indeed, its e-commerce arm has grown into a formidable competitor against Amazon while its subscription-based warehouse store Sam’s Club has emerged as an industry leader — not just among warehouse clubs, but also general merchandise retailers overall, according to the 2024 American Customer Satisfaction Index (ACSI). Its upgraded Scan and Go self-checkout technology, which allows customers to bypass checkouts altogether, was cited as a key factor behind Sam’s Club’s top ranking in customer satisfaction.
Though it might be tempting to view Walmart’s tech evolution as a recent pivot, in truth its digital transformation has been a decade in the making. Early efforts — like curbside delivery (originally branded “Online Grocery Pickup”, or OGP), which was later augmented by its Spark last-mile delivery platform — may have lacked the seamless shine of today’s Sam’s Club experience. Still, they laid crucial groundwork for Walmart’s long-term positioning against market leaders Amazon and Costco.
Walmart has since broadened its innovation push. The company launched a drone delivery programme in 2021 and now partners with Wing and Zipline to emerge as the US retailer with the largest drone delivery footprint. Other AI-driven initiatives like InHome Replenishment — an algorithmic service that anticipates customer needs and places automated orders based on their historical grocery-shopping habits — further illustrate Walmart’s push to reshape retail logistics by leveraging cutting-edge technology. Yet, perspective matters: Walmart’s online shopping operations, launched all the way back in 2000, only turned in its first profit in 1Q2025. Indeed, transformative breakthroughs rarely arrive overnight — they are more often the product of years of slow, deliberate iterations. In Walmart’s case, its tech efforts have long been anchored by a clear, consistent strategic vision focused on customer convenience and upholding its promise of everyday low prices. As the well-worn adage goes, “change takes time”.
On the other end of the spectrum, Walgreens’ foray into digital waters stands as a cautionary tale (see Chart 3). The company partnered with tech-start-up CoolerX (formerly Cooler Screens) in 2020 to replace traditional refrigerator doors with digital screens in a high-profile bid to modernise its store and generate additional advertising revenue. The screens were designed to replace the generic rows of dimly lit shelving typical of conventional fridge displays with dynamic product images and advertisements. In practice, however, they frequently malfunctioned — displaying incorrect products, going dark and even catching fire. These issues were compounded by frequent power surges stemming from the company’s outdated store infrastructure.
Unsurprisingly, the digital doors generated minimal revenue — reportedly just US$215 per screen annually. The failed experiment spiralled into a US$200 million lawsuit, when CoolerX sued Walgreens in 2023 and severed data feeds to over 100 stores, leaving Walgreens customers to blindly rummage through multiple fridges to identify their intended purchases. Separately, AI solutions company Alpha Modus has since also filed a patent infringement suit against Walgreens for the use of digital screens in stores, alleging violations of its real-time retail technology and smart display patents. The core issue of Walgreens’ tech pivot — summed up succinctly by consumer intelligence firm NeilsenIQ — was the “[complication of] a simple, straightforward sale”. Or, as one TikTok user laid out even more plainly: “We didn’t need this”. In the year leading up to Walgreens’ legal woes (in 2022), the company cycled through three different chief information officers (CIOs), underscoring a deeper pattern of unstable tech leadership.
For sure, Walmart too had its share of digital missteps — such as its partnership with Bossa Nova Robotics, discontinued in 2020, when the company concluded that human employees could manage shelf inventory just as effectively at lower cost. The key difference lies in execution: Walmart maintained stable leadership and a coherent long-term strategy, whereas Walgreens’ revolving door-CIO problem revealed a disconnect between its tech ambitions and business realities. The CoolerX debacle exemplifies this misalignment — a flashy concept untethered from in-store practicalities. Rather than strengthening core processes, it came across as a gimmick.
This episode further underscores a broader risk in digital transformation, in which many companies rush into AI and tech adoption without fully accounting for infrastructure, customer experience or long-term viability. These are precisely the issues that strategy is meant to address. With failure often a necessary cost of innovation, it is all the more critical for a company’s digital experimentation to be anchored by clear, stable business strategy to ensure new initiatives advance rather than derail long-term objectives. Over the past decade, Walgreens’ shares have plunged more than 85% (see Chart 4). In March 2025, the company entered into a definitive agreement to be taken private by Sycamore Partners.
The bottom line
Netflix and Walmart are obviously very successful companies. One might ask, what is the point of this article? It is inevitable that businesses, no matter how large and successful, will get disrupted at some point. While many of the disruptors in the last two decades have been tech companies, what we have shown here is that “old economy” incumbents too can prevail. After all, one could hardly find a more “bricks-and-mortar” business than Walmart, founded by Sam Walton back in 1962. And while you might be inclined to think of Netflix as tech, the company started as a DVD rental by mail service in 1997. It is not about the technology itself, but how enterprises leverage technology to enhance productivity, innovate and gain comparative advantages against competitors.
As we have said more than once in the past, technology is, and always will be, just the ENABLER. Even the biggest of Big Tech understands this. NYU Stern School of Business professor Scott Galloway once controversially claimed that these companies serve human needs better than traditional institutions like religion: Google, a modern-day deity answering our digital prayers; Facebook, fulfilling our craving for love and belonging; Amazon, the need for security by offering instant access to abundance; and Apple, appealing to our desire for status and attraction with sleek, costly devices. A provocative claim, to be sure, but the underlying point rings true.
Whether you’re a legacy incumbent or Silicon Valley unicorn, success has always been less about tech wizardry and more about using technology to deliver real, meaningful value to customers. Finally, the title of a 2013 Wall Street Journal article on Netflix’s wild success with original content production sums it up best: the point, always, has been to “give [customers] what they want”.
Next week, we will discuss the opposite — case studies on companies that use tech but ultimately end up as failures. Because tech was the endgame and not a means to an end, due to poor knowledge and understanding of the intricacies of the industries they are attempting to disrupt, poor execution, lack of talent or simply the lack of a clear and sustainable strategy and bad business models. Despite some very high-profile failures, we fear there will be many more of these, and yes, big money will still be drawn by illusions.
The Malaysian Portfolio was up marginally, by 0.1% for the week ended June 18. United Plantations (+0.7%) finished higher while Kim Loong Resources and Insas Bhd – Warrants C ended the week unchanged. Total portfolio returns now stand at 184.2% since inception. This portfolio is outperforming the benchmark FBM KLCI, which is down 17.4% over the same period, by a long, long way.
The Absolute Returns Portfolio, on the other hand, fell 0.2% for the week, paring total returns since inception to 25.3%. The top three gaining stocks were JPMorgan (+2.2%), Goldman Sachs (+1.8%) and CrowdStrike (+1.7%), while the notable losers were Alibaba Group Holding (-5.2%), Trip.com (-4.9%) and Tencent Holdings (-1.9%). We disposed of our stake in US Steel Corp, netting smart returns of 32.6% in less than three months. Japan’s Nippon Steel has completed its acquisition of the company, and US Steel will be delisted from the NYSE effective June 30.
Tong’s AI Portfolio fell 3%, sending total portfolio returns since inception to -2.7%. Datadog was the sole gainer (+9.6%) last week. The biggest losers were Horizon Robotics (-11.8%), RoboSense Technology (-7.3%) and Workday (-5.8%).
Disclaimer: This is a personal portfolio for information purposes only and does not constitute a recommendation or solicitation or expression of views to influence readers to buy/sell stocks, including the particular stocks mentioned herein. It does not take into account an individual investor's particular financial situation, investment objectives, investment horizon, risk profile and/ or risk preference. Our shareholders, directors and employees may have positions in or may be materially interested in any of the stocks. We may also have or have had dealings with or may provide or have provided content services to the companies mentioned in the reports.
