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5-Bit Friday’s (#8): Weekly snacks from the startup/tech universe
On The Innovators Dilemma (all you need to know), how to lose a monopoly, the future of TikTok, betting vs backlogs, and the hardest thing in product management.
Hi, I’m Jaryd. 👋 Every other week, I pick one startup/company you probably know, and do a deep dive on how they kickstarted their growth, and drive growth today.
Plus, every Friday — I bring you 5 short-form insights and takeaways from the startup/tech universe. (this!)
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Happy Friday, friends! 🍻
And happy 2023 — wishing you all the health, happiness, success, and productivity for the year ahead. 🙏
It’s been a minute. As most of you know, I was taking some PTO back in Cape Town to see family and attempt a sun tan. But, with recovering sunburn, I’m back — and I’m super excited to get back into our regular scheduled programming. Today will be our first 5-Bit Friday of the year, and next week Wednesday (the 11th) is when we’ll kickoff the main cheese of this newsletter — our deep dives.
P.S: If you’re ever traveling to South Africa (which I highly suggest) — hit me up. I’ve got loads of recommendations for you. 🌞
Alrighty, let’s do it.
Here’s what we’ve got this week.
The Innovators Dilemma - the 10 main points summarized
How to lose a monopoly — when moats become irrelevant
Why TikTok’s future has never been so cloudy
Bets, not backlogs
The hardest thing in product management
Bonus: Other interesting things if you have time 🎓
The Innovators Dilemma - the 10 main points summarized
If you work in tech, you’ve probably been told you need to read The Innovators Dilemma: When New Technologies Cause Great Firms to Fail, by Clayton Christensen.
I certainly have, and I’ve seen it on countless book recommendation lists. It’s no doubt an enormously influential business book, “a kind of bible for some of the most influential managers of recent years”. Steve Jobs famously listed it as one of the few business books he trusted, and the startup world also practices a lot of the concepts.
So, while on vacation, I picked it up and gave it a read.
Except, I found it enormously tedious and boring to read. 🙃
I wish I didn’t, but I find academic writing particularly tough to get through. So, still wanting to learn about this influential theory, I did lots of watching and reading of interviews and short-form pieces around it — making it much more palatable to understand.
So, here’s my high-level summary of the books main arguments for us. If you haven’t read it, perhaps this is enough. If you have, it’s a nice refresher!
But first, a quick definition. Christensen famously coined the word disruption. Given its overuse these days — here is an excerpt from the book that aligns on how Christensen sees true disruption.
Most new technologies foster improved product performance. I call these sustaining technologies. Some sustaining technologies can be discontinuous or radical in character, while others are of an incremental nature.
What all sustaining technologies have in common is that they improve the performance of established products, along the dimensions of performance that mainstream customers in major markets have historically valued.
Most technological advances in a given industry are sustaining in character. An important finding revealed in this book is that rarely have even the most radically difficult sustaining technologies precipitated the failure of leading firms.
Occasionally, however, disruptive technologies emerge: technologies that result in worse product performance, at least in the near-term. Ironically, in each of the instances studied in this book, it was disruptive technology that precipitated the leading firms’ failure.
Products based on disruptive technologies are typically cheaper, simpler, smaller, and, frequently, more convenient to use.
In other words…
Sustained innovation: improving on things customers already care about for existing products
Disruptive innovation: transforms a product that was once expensive and hard to use, and makes it accessible to the masses (i.e democratizing something)
With that definition in mind, here are the 10 main points from The Innovators Dilemma, with a short quote from the book below it.
Big idea #1:
The way that companies that are already operating in established, mature, markets are organized (resources, processes, and values) isn’t effective for addressing disruptive technologies.
Successful companies want their resources to be focused on activities that address customers’ needs, that promise higher profits, that are technologically feasible, and that help them play in substantial markets. Yet, to expect the processes that accomplish these things also to do something like nurturing disruptive technologies — to focus resources on proposals that customers reject, that offer lower profit, that underperform existing technologies and can only be sold in insignificant markets — is akin to flapping one’s arms with wings strapped to them in an attempt to fly.
Big idea #2:
Creating a new market is less risky and more rewarding than entering established markets.
The evidence from the disk drive industry shows that creating new markets is significantly less risky and more rewarding than entering established markets against entrenched competition.
*This is similar to the theory of Blue Ocean Strategy
Big idea #3:
Being a first mover is an advantage when developing disruptive innovation, but it doesn’t have an effect when playing in an established market.
A crucial strategic decision in the management of innovation is whether it is important to be a leader or acceptable to be a follower. Volumes have been written on first-mover advantages, and an offsetting amount on the wisdom of waiting until the innovation’s major risks have been resolved by the pioneering firms. “You can always tell who the pioneers were,” an old management adage goes. “They’re the ones with the arrows in their backs.” As with most disagreements in management theory, neither position is always right.
There is no evidence that any of the leaders in developing and adopting sustaining technologies developed a discernible competitive advantage over the followers.
In contrast to the evidence that leadership in sustaining technologies has historically conferred little advantage on the pioneering disk drive firms, there is strong evidence that leadership in disruptive technology has been very important. The companies that entered the new value networks enabled by disruptive generations of disk drives within the first two years after those drives appeared were six times more likely to succeed than those that entered later.
[Only three of the fifty-one firms (6 percent)] that entered established markets ever reached the $100 million revenue benchmark. In contrast, 37 percent of the firms that led in disruptive technological innovation — those entering markets that were less than two years old — surpassed the $100 million level. Whether a firm was a start-up or a diversified firm had little impact on its success rate. What mattered appears not to have been its organizational form, but whether it was a leader in introducing disruptive products and creating the markets in which they were sold.
It is, indeed, an innovator’s dilemma. Firms that sought growth by entering small, emerging markets logged twenty times the revenues of the firms pursuing growth in larger markets
[It’s about exchanging] a market risk, the risk that an emerging market for the disruptive technology might not develop after all, for a competitive risk, the risk of entering markets against entrenched competition.
Big idea #4:
Emerging markets are not attractive to established firms because they don’t provide significant short term gains. But, it’s here that firms should enter them in order to become market leaders in the future. Eg — for Kodak, film was much bigger business than this new tech of digital cameras…
The last element of the failure framework, the conclusion by established companies that investing aggressively in disruptive technologies is not a rational financial decision for them to make, has three bases. First, disruptive products are simpler and cheaper; they generally promise lower margins, not greater profits. Second, disruptive technologies typically are first commercialized in emerging or insignificant markets. And third, leading firms’ most profitable customers generally don’t want, and indeed initially can’t use, products based on disruptive technologies. By and large, a disruptive technology is initially embraced by the least profitable customers in a market.
Hence, most companies with a practiced discipline of listening to their best customers and identifying new products that promise greater profitability and growth are rarely able to build a case for investing in disruptive technologies until it is too late.
This problem is particularly vexing for big companies confronting disruptive technologies. Disruptive technologies facilitate the emergence of new markets, and there are no $800 million emerging markets. But it is precisely when emerging markets are small — when they are least attractive to large companies in search of big chunks of new revenue — that entry into them is so critical.
The executives’ actions were a symptom of a deeper problem: Small markets cannot satisfy the near-term growth requirements of big organizations.
Big idea #5:
For established companies to survive long-term, they should create subsidiaries or acquire other companies that have the right organizational structure (process, values), equip them with resources (money and people) — and then let them run independently. They should not to be pressured into making a short term profit, rather be given a unique identity and allowed to create their market.
Though its total revenues amount to more than $20 billion, J&J comprises 160 autonomously operating companies, which range from its huge MacNeil and Janssen pharmaceuticals companies to small companies with annual revenues of less than $20 million. Johnson & Johnson’s strategy is to launch products of disruptive technologies through very small companies acquired for that purpose.
This recommendation is not new, of course; a host of other management scholars have also argued that smallness and independence confer certain advantages in innovation.
Establishing independent organizations to pursue disruptive technology seems to be a necessary condition for success.
Big idea #6:
These independent companies shouldn't be pressured into being right the first time. Rather, they should be encouraged to be taking big bets, and the most important factor for the bigger company should be reducing sunk costs, so if bets fail (which they should), pivoting is cheap. "Business plans" should instead be "learning plans".
Guessing the right strategy at the outset isn’t nearly as important to success as conserving enough resources (or having the relationships with trusting backers or investors) so that new business initiatives get a second or third stab at getting it right. Those that run out of resources or credibility before they can iterate toward a viable strategy are the ones that fail.
Careful planning, followed by aggressive execution, is the right formula for success in sustaining technology. But in disruptive situations, action must be taken before careful plans are made. Because much less can be known about what markets need or how large they can become, plans must serve a very different purpose: They must be plans for learning rather than plans for implementation.
Big idea #7:
Customers follow the "Buying Hierarchy" depending on the maturity of the market. The phases are: functionality ⇒ reliability ⇒ convenience ⇒ price.
Consider, for example, the product evolution model, called the buying hierarchy, which describes as typical the following four phases: functionality, reliability, convenience, and price. Initially, when no available product satisfies the functionality requirements the market, the basis of competition, or the criteria by which product choice is made, tends to be product functionality. Once two or more products credibly satisfy the market’s demand for functionality, however, customers can no longer base their choice of products on functionality, but tend to choose a product and vendor based on reliability. As long as market demand for reliability exceeds what vendors “are able to provide, customers choose products on this basis — and the most reliable vendors of the most reliable products earn a premium for it.
But when two or more vendors improve to the point that they more than satisfy the reliability demanded by the market, the basis of competition shifts to convenience. Customers will prefer those products that are the most convenient to use and those vendors that are most convenient to deal with. Again, as long as the market demand for convenience exceeds what vendors are able to provide, customers choose products on this basis and reward vendors with premium prices for the convenience they offer.
Finally, when multiple vendors offer a package of convenient products and services that fully satisfies market demand, the basis of competition shifts to price.
Big idea #8:
The characteristics that make disruptive products valuable in emerging markets are the same ones that make them worthless in mainstream markets.
The attributes that make disruptive products worthless in mainstream markets typically become their strongest selling points in emerging markets; and second, disruptive products tend to be simpler, cheaper, and more reliable and convenient than established products.
In contrast, the firms that were most successful in commercializing a disruptive technology were those framing their primary development challenge as a marketing one: to build or find a market where product competition occurred along dimensions that favored the disruptive attributes of the product.
Big idea #9:
The best way to identify disruptive technologies is by creating a graph with performance improvement demanded in the market vs. performance improvement supplied by the technology.
Does it constitute an opportunity for profitable growth? To answer these questions, I would graph the trajectories of performance improvement demanded in the market versus the performance improvement supplied by the technology; … Such charts are the best method I know for identifying disruptive technologies.
If these trajectories are parallel, then (electric vehicles) are unlikely to become factors in the mainstream market; but if the technology will progress faster than the pace of improvement demanded in the market, then the threat of disruption is real.
Big idea #10:
Disruptive technologies involve existing technology in a new architecture.
Historically, disruptive technologies involve no new technologies; rather, they consist of components built around proven technologies and put together in a novel product architecture that offers the customer a set of attributes never before available.
In short, the dilemma is this: "Should we make better products to make better profits or make worse profits for people that are not our customers that eat into our own margins?”
It’s the disincentive managers face to go into new, unproven, markets — when doing so is how you maintain longevity.
How to lose a monopoly — when moats become irrelevant
Sticking to the same theme here — there’s a great essay by Benedict Evans, How to lose a monopoly. He talks about how Microsoft and IBM each dominated their generation of tech, and they each lost that dominance, not because of anything they did, nor because of anti-trust, but because the business they controlled stopped being the centre of tech.
In his essay, he talks a lot about power as the characteristic of monopoly.
When we talk about ‘power’ and ‘dominance’ and perhaps ‘monopoly’ in tech, we actually mean two rather different things, and we generally conflate them:
There is having power or dominance or a monopoly around your own product in that product’s own market…
but then there is whether that position also means you control the broader industry.
In the 1970s dominating mainframes meant dominating tech, and in the 1990s dominating PC operating systems (and productivity software) meant dominating tech. Not any more. IBM still dominates mainframes, and Microsoft still dominates PCs, but that isn’t where broader dominance of the tech industry comes from. Once upon a time, IBM, and then Microsoft, could make people do things they didn’t want to do.
Not today. Being rich is not the same as being powerful.
Microsoft is a much bigger company now than it was in 1995, but then, so is IBM. No-one would look at the IBM [stock] chart and say ‘look - IBM dominates tech’, but the same applies to Microsoft.
We often think that Google, Facebook, etc will easily and naturally transfer their dominance to any new cycle that comes along. But, this wasn’t the case for IBM or Microsoft, the two previous generations of tech dominance — and it’s not necessarily true for the new big incumbents.
The tech industry loves to talk about ‘moats’ around a business - some mechanic of the product or market that forms a fundamental structural barrier to competition, so that just having a better product isn‘t enough to break in. But there are several ways that a moat can stop working. Sometimes the King orders you to fill in the moat and knock down the walls. This is the deus ex machina of state intervention - of anti-trust investigations and trials.
But sometimes the river changes course, or the harbour silts up, or someone opens a new pass over the mountains, or the trade routes move, and the castle is still there and still impregnable but slowly stops being important. This is what happened to IBM and Microsoft. The competition isn’t another mainframe company or another PC operating system - it’s something that solves the same underlying user needs in very different ways, or creates new ones that matter more. The web didn’t bridge Microsoft’s moat - it went around, and made it irrelevant. Of course, this isn’t limited to tech - railway and ocean liner companies didn’t make the jump into airlines either. But those companies had a run of a century - IBM and Microsoft each only got 20 years.
Perhaps Clayton Christensen’s Argument 5 above is the answer.
Why TikTok’s future has never been so cloudy
If you look at the most downloaded free apps on iOS and Google, you’ll find TikTok where it usually is — at the top.
It’s the most dominant social app with a massive cultural impact across the world. “It’s the place where new trends are born, pop stars are minted, and young people spend a staggering share of their time.”
But, while we scroll indefinitely sharing cat videos, a ton of skepticism and concern over the app and its Chinese parent company, ByteDance, is brewing in the US. Basically, people are very worried about what China can do with all the data (influence?) on people they could get via TikTok.
Due to recent congress action — as a first move, TikTok has been forbidden from being installed on devices owned by the federal government. Sorry Uncle Sam, no Wednesday Adam’s dance videos for you!
In a recent post by Casey Newton from the Platformer, he gets into this issue. He sets the stage by saying:
Amid an ongoing trade war with China, distrust of ByteDance is the rare tech issue on which Republicans and Democrats found bipartisan agreement. The $1.7 trillion spending bill that President Biden signed into law on Thursday contained a provision banning TikTok from devices under federal management; it is also banned in the House of Representatives and the Senate.
All of which raises a question that had seemed mostly resolved since Trump left office: could TikTok be banned in the United States, period?
Trump tried and failed to forcibly divest ByteDance of TikTok and hand it to one of his top fundraisers, Oracle CEO Larry Ellison. Biden has taken a less thuggish approach to his China dealings, but in the end is proving to be quite hawkish on Chinese tech: he has worked to prevent China from developing advanced chips, plans to limit US investments in Chinese tech, and will restrict the ability of Chinese apps to collect data about Americans. (Guess who that last one is aimed at.)
TikTok has been working with the US government to allow ByteDance continue to own the company while putting TikTok’s user data, recommendation algorithms, and corporate governance “into a kind of quarantine” — protecting US users.
At first glance, Casey goes on to say, “it might look like TikTok’s future is a familiar one to anybody who has followed the past half-decade of US tech regulation. Lawmakers hold hearings and draft rules, but succumb in the end to infighting and paralysis. The only changes we ultimately see come either from regulation in Europe or competitive pressures from rivals.”
But, he adds:
While that has been the story to date for Facebook, YouTube, Twitter, and others, TikTok’s position appears to be much more serious. For all the criticism that Facebook in particular took during that period, it was never banned from federal government devices. And while banning TikTok for consumers would surely cause a furor, Biden’s China posture to date suggests that he may be willing to do it anyway.
At such a fraught time, ByteDance can ill afford a high-profile mistake. And yet in the days after more states began to ban TikTok, an internal investigation found that ByteDance employees had used TikTok to record journalists’ physical locations using their IP addresses. It was apparently part of a leak investigation in which ByteDance attempted to discover reporters’ sources.
Not kosher + bad for goodwill = lots of alarmed lawmakers.
Since the beginning of this fiasco, ByteDance execs have openly scoffed at the idea that their app could be used to surveil Americans. But, here we are — TikTok being used for exactly that purpose. And on top of that, it was used against the US journalists trying to figure out the relationship between ByteDance and TikTok.
Where there’s smoke!…. 🔥
Get more on this story below + other tech news centered around democracy from the Platformer.
Bets, not backlogs
I’ve written on chapters from Basecamp’s Shape Up e-book before. I think it’s a great read for product managers with loads of useful frameworks.
One that I want to talk about today is “Bets, not backlogs”.
If you’re in product development, you’re more than likely familiar with the long lists of tasks that can pile up on the backlog — many of which never actually get picked up and done.
Backlogs are big time wasters too. The time spent constantly reviewing, grooming and organizing old ideas prevents everyone from moving forward on the timely projects that really matter right now.
And with a backlog, you have to be reviewing, grooming, and organizing what’s on it — otherwise it really is just an abyss that becomes more and more daunting over time.
So in Shape Up, Basecamp bring the idea of a few potential bets to the table.
This is how they explain it:
So what do we do instead? Before each six-week cycle, we hold a betting table where stakeholders decide what to do in the next cycle. At the betting table, they look at pitches from the last six weeks — or any pitches that somebody purposefully revived and lobbied for again.
Nothing else is on the table. There’s no giant list of ideas to review. There’s no time spent grooming a backlog of old ideas. There are just a few well-shaped, risk-reduced options to review. The pitches are potential bets.
With just a few options and a six-week long cycle, these meetings are infrequent, short, and intensely productive.
If we decide to bet on a pitch, it goes into the next cycle to build. If we don’t, we let it go. There’s nothing we need to track or hold on to.
What if the pitch was great, but the time just wasn’t right? Anyone who wants to advocate for it again simply tracks it independently—their own way—and then lobbies for it six weeks later.
This way the conversation is always fresh. Anything brought back is brought back with a context, by a person, with a purpose. Everything is relevant, timely, and of the moment.
Here are a few other important takeaways from the chapter:
Decentralized lists: Everyone can still track pitches, bugs, requests, or things they want to do independently without a central backlog. There’s no one backlog or central list and none of these lists are direct inputs to the betting process.
Cross-department brainstorming: Outside of the betting table meeting, 1:1s and async communication help bring up ideas and get alignment.
Working and betting in cycles: It’s important to find a cycle that makes sense for your business. For Basecamp, they tested until they landed on 6-weeks. “We wanted a cycle that would be long enough to finish a whole project, start to end. At the same time, cycles need to be short enough to see the end from the beginning. People need to feel the deadline looming in order to make trade-offs.”
The betting table: “The meeting is short, the options well-shaped, and the headcount low. When these criteria are met, the betting table becomes a place to exercise control over the direction of the product instead of a battle for resources or a plea for prioritization. With cycles long enough to make meaningful progress and shaped work that will realistically ship, the betting table gives the C-suite a hands on the wheel feeling they haven’t had since the early days.”
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The hardest thing in product management
It’s not your product, its distribution.
According to Abhishek Chakravarty:
When Product Managers are asked what some of their most risky assumptions are, they often cite market risk assumptions or technology risk assumptions. This is what the vast majority of PMs spend time thinking about and validating.
Market Risk — the assumption that there is meaningful demand for the product you are building
Technology Risk — that the core value proposition (that eliminates the market risk) can indeed be built in reality.
The thing that Product Managers and builders often don’t take into account is Distribution risk assumptions, which is, — can a product successfully be distributed/delivered to customers at scale?
I’ve spoken before about how essential distribution is to growth. You can have an amazing product, but be careful underestimating the challenges around distributing a groundbreaking product that people had never heard of before.
Peter Thiel in Zero to One frames the challenge this way:
Superior sales and distribution by itself can create a monopoly, even with no product differentiation. The converse is not true. No matter how strong your product — even if it easily fits into already established habits and anybody who tries it likes it immediately — you must still support it with a strong distribution plan.
Most businesses actually get zero distribution channels to work. Poor distribution — not product — is the number one cause of failure.
The takeaway here is simple: think about your distribution strategy as you plan and build the product. Work with marketing and sales, and get going on this early. Start by looking at your product’s KPIs and ask your self — how do we get there?
With distribution, there is no magic bullet — here’s Abhisheck’s recommendation:
Take a scientific approach to figuring out the right channel for your product. Start with first principles. Identify a broad set of channels that you think may work, and Experiment , Measure & Learn to identify your core channels that are demonstrably and repeatedly bringing you profitable customers. Then double down on these channels.
Talking about first principles — taking a hard re-look at your product & customer segments is the best way to get started.
In his essay, he gets more into what it means to (1) look at your product, and (2) look at your customer segments. He also goes into the issue around being in the distribution Dead Zone (i.e selling to small businesses at a $1k price point)— and some concrete distribution tips if you do find yourself here .
And that’s a wrap for our first weekly roundup of 2023! Keep an eye on your inbox next Wed, 8am EST, for our first deep dive of the year. It’s going to be epic. 😉
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See you next time! ✌️