Scale Economies, Network Effects, Branding, and More: The 7 Powers of Product Strategy [Part II]

In the last post we looked at what strategy is and the false contradiction between planning for strategy and letting your product emerge through rapid experimentation and fast feedback loops, which often combine and compound in unforeseen ways. We talked at how writing it down can help you clarify your future thinking and crystallize your product definition and the strategy that underlies it.

In this post, we’ll look at strategic power. What types of moats and differentiating factors your strategy will help you create so that you can design your plans in light of what you really want your business to achieve.

We’ll look at it through the recent but highly recommended classic 7 Powers, which synthesizes the key types of strategic power one can aim to achieve and what benefits and barriers each of the powers carries with it. Some of them are quite well-known and well-studied, like network effects — typical of N-sided marketplaces, or social networks - while others might take a more in-depth analysis to get used to.

The 7 Powers

Scale Economies

Ben Thompson writes about some of the transformational effects of the internet in terms of creating new moats and the impacts this has had on scale economies. In his post “Defining Aggregators”, Ben describes this internet-powered scenario:

“Companies traditionally have had to incur (up to) three types of marginal costs when it comes to serving users/customers directly.

1. The cost of goods sold (COGS), that is, the cost of producing an item or providing a service

2. Distribution costs, that is the cost of getting an item to the customer (usually via retail) or facilitating the provision of a service (usually via real estate)

3. Transaction costs, that is the cost of executing a transaction for a good or service, providing customer service, etc.

Aggregators incur none of these costs:

1. The goods “sold” by an aggregator are digital and thus have zero marginal costs (they may, of course, have significant fixed costs)
2. These digital goods are delivered via the Internet, which results in zero distribution costs
3. Transactions are handled automatically through automatic account management, credit cards payments, etc..”

The key insight here in terms of marginal costs is that digital goods have none (or trend towards zero). Effectively, once you create a piece of software, you can onboard new users indefinitely or replicate its instances with virtually zero marginal cost. This means your initial Capital Expenditure (CAPEX), can be paid off multiple times at no additional cost, provided you have efficient distribution and operation. Facebook can now add any new user or advertiser at near-zero additional cost. The same goes for AWS, which has already rented or built out server space and management capabilities, and can now onboard any new paying user at virtually zero cost.

This exacerbates something that already happened in the physical world. Often when producing a new physical good, brands and producers incurred in significant costs to produce a limited amount of units ahead of proving their model could scale, before ramping up production and capturing efficiencies in operations, cost of goods, human resources and others, that would allow them to drive down unit costs and capture a larger share of revenue.

This insight from Moiz Ali, founder of Natural Deodorant brand Native speaks to the application of scale economies to physical products and how the initial price point he chose (designed to break-even), eventually led to profitability as production increased:

“Yes. The cost fell dramatically. We found a new manufacturer when we started scaling. We went from 500 units a week to 500 units a day. And the cost fell in half. Then we went from 500 units a day to 1,000 units a day, and then we went from a 1,000 units a day to like 10,000 units a day. And then sooner or later we were at tens of thousands of units a day. And at each stage our cost fell.”

The same types of scale economies allow Netflix and Spotify to invest in premium content, produce their own shows (podcasts in Spotify’s case, so as not to come into conflict with record labels, who still hold power over distribution in the music industry) and distribute the costs of their purchases over a much larger user base than their competitors (say the cost of a $2B series Netflix invests in would be paid by ~200M subscribers, meaning they’d pay it back within a month, give or take — now imagine that for a competitor or an upstart), earning return on their investments much sooner, allowing them to reinvest and creating a virtuous feedback loop for their shareholders. Which is exactly the type of dynamics that allow Netflix to gain and retain market power.

Network Effects

Another one of the most well-known strategic powers is the creation of network economies. You’ll recognize them from marketplace-type businesses or social networks, where there are deep connections between players in the network, and where each additional node (user/customer/supplier), increases the value of the network positively non-linearly.

The power of a network economy dynamic is often compared to that of a flywheel, which stores rotational energy very effectively past a certain amount of energy being invested into the system. This means that once you hit a critical mass point, where the right amount of users are onboarded into the system, it takes you a lot less energy to add additional ones, whereas it would take your competitors (benefitting from smaller effects, a lot more energy to attain and preserve the same energy).

This, again, releases capital that you can reinvest in aggregating demand, in capturing supply revenue, in improving your distribution channels, in improving your search and matchmaking capabilities, or invest in tangent capabilities that strenghten your moat (see Amazon’s foray into logistics and fulfillment as a platform, past their success as a traditional marketplace with low amounts of inventory). For more on network effects, I recommend these 2 posts by A16Z as starters: All about network effects and The Dynamics of Network Effects.

It follows, then, that the key issue in obtaining network effects, is that products seeking them need to be able to power the network with sufficient energy so as to get the flywheel spinning fast enough that it becomes sustainable and creates a moat. Aggregating demand appears to be the way to do it both for social networks (which more often than not begin with no plans as to how they’ll monetize, and instead focus on building the network itself), as well as for modern marketplace businesses, which often focus on distribution-first, a niche market (so as to constrain the amount of differentiated supply they need), or a commoditized-supply regional business (such as scooter-rental), which they can then use to power network effects across other segments.

Even in crypto-currencies, ICOs and other token-offering mechanisms which benefit early-adopters, were ways their network designers looked to solve the chicken-egg problem through a financial reward. In participation the network as a node early on, you’d own a larger share of it, thus incentivizing the creation of critical mass. Unfortunately for them, most forgot that in order to maintain the flywheel spinning, it still needs a level of energy / utility for participants to want to come back. That, takes real power.

Switching Costs

Switching costs often pop up in B2B due to how tighly integrated with business practices certain acquisitions are (whether of products or of services). Imagine your company moves into Workday for HR Management and Planning. Not only will all your employees move into the tool, you’ll have had it integrated with your Single-Sign-On server, your ERP, your benefits solution, your expenses management solution, your HR people will have been trained to use it, your employees will have had their data migrated to it, etc.

Even if you haven’t paid a penny of your actual subscription to Workday yet, you’re already incurring in switching costs. Both the financial, the time and the workflow-driven investments you make in the tool (you might adjust certain processes or customize the tool to fit yours), will constitute switching costs when a competitor solution comes along and tries to replace it within your enterprise.

Typically the stiffer your processes are, the more difficult for you to change things up later. Also the larger the amount (of time and money) you invest organizationally into a solution, the larger the sunk cost and the opportunity cost to switch to a new one. This happens all the time in the public sector, or in sectors where operational complexity is high. Imagine you’re a public hospital who wants to buy a new software that improves your patient health records, allows you to make better clinical decisions and saves your doctors and frontline staff’s time, you still need to consider the implications of procuring that software, moving all your data across to the new system, training your staff to use it, onboarding patients and stakeholders into the system, securing it within your IT infrastructure’s operating constraints, amongst other switching costs. This moat by the incumbent is often referred to as Vendor Lock-in.

The same type of workflow integration happens with consumer products, but on an individual basis. If one invests years of their life getting all of their photos on Google Photos or Apple’s iCloud Storage, benefits from its integration with other Google/Apple services and devices, this will introduce switching costs when considering alternative solutions (if even they try to lower the burden of change). Similarly, once one builds a tight-knit pattern of friends and relationships within a social network, it is really really hard for a challenger to untie those in a format that encourages users to switch. The costs are just too damn high!

This often happens by coming up with a completely new format (think Instagram’s filters), or disrupting the incumbent in one key dimension that’s critical for a niche segment before expanding to mass market. More on this in counter-positioning.

Cornered Resource

Cornered Resources typically happen by fiat, i.e. by decree, by natural emergence or prescriptive influence, by virtue of one of the competitors having accessed a resource that isn’t accessible by others in the market for some reason that then constitutes an unfair advantage vs their competitors.

This is arguably the case with state-sponsored oil companies in the Gulf region, which have been given regulatory rights to explore a scarce commodity with worldwide demand, rights which may not be shared or democratized.

This might also be the case with intellectual property, when knowledge or access to information is shared within a small group and constitutes a market advantage, and that group uses that information to productize it or turn it into services that are hard if not impossible (economically) for competitors to replicate. Pixar’s positional scarcity, aggregating knowledge, capabilities and resources that no other studios had. Disney’s early advantage on character building and their usage of those characters in theme parks is one such cornered resource which has now seeped into the streaming business with Disney Plus. Record labels’ possession of the rights to license the most well-known brands in the industry (allowing them to exercise power over distributors — what Tren Griffin calls “Wholesale Transfer Pricing".

Once you get a hold of a valuable resource (by virtue, by chance or even by malfeasance) and you corner the market for it, it becomes a competitive advantage that can be insurmountable for vast periods of time and allow you to accumulate capital advantages elsewhere. That, is power.

Process Power

One source of power that’s less visited but Helmer discusses in the book is Process Power. The obvious example is Toyota’s, and how the conditions to their success look unimitable from the outside, their processes have been emulated many many times since their popularization, they even worked with competitors directly to implement their key operating principles in their manufacturing plants (such as GM — see here), and yet their competitors never managed to achieve the levels of quality, efficiency and effectiveness of their Japanese counterparts. Numerous books have been written since on the Toyota Production System, their Lean manufacturing approach, the Toyota Kata, the Kaizen system for continuous improvement, and everywhere in the world, and across every industry, people have tried to replicate it and its principles with varying degrees of success. As a source of Power, though, its process as a key moat for Toyota, that allowed it to scale worldwide even in the face other regulatory and competitive obstacles that competitors and nation-states tried to impose on the company.

The reality many discovered — it’s what you do. Behaviors promoted and incentivized, codes of conduct, relationships, hiring processes and traits you optimize for. These are all a part of process power.

Process power can’t be replicated by simply following a recipe, there’s art and craft that’s been perfected over time to result in the right culture, making it hard to replicate, and thus constituting a moat.

It’s the corollary of all things spoken and unspoken in corporate culture, that result in thousands of purposeful micro-decisions within the process framework that sustains the innovative approach and the results that it contains.

Recently, with Agile, Lean, and a culture focused on speed of iteration and experimentation (enabled by software, which drastically lowers the cost of change and whose micro improvements can be continuously absorbed by the market), the process power gap has closed in new industries, and many have tried to copy each others’ processes resulting in more or less a consensus as to how to build an amazing software company at scale. Even then, cultural differences come to the fore, and as a result of that optimization, different capabilities emerge. As Michael Porter described, in talking about what is NOT process power:

“Operational effectiveness is about things that you really shouldn’t have to make choices on; it’s about what’s good for everybody and about what every business should be doing.”

There’s a clear difference between what Amazon, with its 2-pizza team-size rules, its API Mandate as a template for organizational change, making them their primary means of communication, decentralizing communication and allowing them to move forward independently, enabled Amazon to become competitive in multiple different areas, diversifying their offers and their revenue streams and strengthening their moat as an ecommerce leader and a commerce logistics & fulfilment platform.

Many have tried copying these processes blindly, in hopes that it would give them a competitive advantage, and failed. They failed in the same manner others failed in trying to implement a founder-centric decision-making process, in the hopes of emulating Steve Jobs and his design-centric critique process at Apple during the invention of its most successful products. Hard-to-copy, emergent, true to their nature and context, deeply connected to the roots of its company’s nature, that the source of process power.

Branding

It’s easy to talk about the power of brand for established household names. Coca-Cola, Nike, Heinz, Apple, IKEA, Hermès. They’ve created emotional connections to their names through years of repetition and carefully written marketing narratives that changed perception of their products from their functional utility to their emotional resonance.

The three key effects of brand power are 1) that they can be used to reduce price elasticity of demand, with brands acquiring pricing power over consumers and selling a product with similar features for a higher price (as a result of consumers being able to signal their affiliation through product use, which translates to how they are themselves perceived). 2) that they make lower the cost of retention / loyalty, with customers coming back to purchase again based on that sentimental affiliation, less than an objective preference function. 3) that they lower acquisition costs, with power users becoming some of their most passionate advocates, and the mass market customers following revealed preferences of this more passionate group by mere pattern recognition. For these customers, the decision-making process is vastly simplified, since they can follow the curated preferences of the advocate group and take that as signal of a certain product’s superiority.

These human biases and cognition pitfalls have hardly been changed by internet economy dynamics, although it is important to acknowledge that in many product categories, with low product differentiation, aggregators have more than ever built brands that commoditize supply. Customers will buy any brand of electronics on Amazon, will follow any top result on Google, will visit whatever service business has 5-star reviews on Yelp, will buy any jacket they like on ASOS. This is an effect of the age of abundance. Commoditization of supply and the large power of aggregators on the internet has created defaults for distribution that customers resort to without much acknowledgement of the underlying brands.

However, this has also meant that many highly specific, scarce niche winners have emerged. High quality goods, or brands highly indexed on a particular trait (e.g. sustainability, style) have emerged, and dominated narrowly defined categories, that still capture a large share of consumers’ wallets. In retail clothing, new luxury brands like off-white, supreme and Yeezy have emerged. Tesla in cars. The rise of D2C brands like Warby Parker, Glossier, Away, Patagonia and others solving highly specific problems for a particular segment or demographic talk to the power of brands, even in the age of commoditization. We’ll see how well these brands can continue to craft their narrative and guaranteeting dominance over prospective challengers in each of their categories (which are quick to spin up and try to gain market share, with the cost of starting new brands coming down via automation and the democratization of supply chains, as well as the accessibility of good design).

Counter-positioning

The last power we’ll talk about is the closest to Clay Christensen’s disruption theory, in my view, and the one that more closely relates in definition to differentiation. Ryan Singer describes positioning as:

A product’s position is a “location” in a more abstract space — the space of trade-offs. The decisions you make about which features to build and how to integrate them places you “closer” or “further” from other products.

Of course positioning isn’t a new marketing concept, but Ryan is spot on when he identifies it as a place occupied in an abstract space that is also inhabited by your competitors. From any of your customers’ perspectives, your positioning is the space you occupy or end up occupying in relation to other brands and products that serve a similar or adjacent need/desire. To start quoting Christensen:

Questions are places in your mind where answers fit. If you haven’t asked the question, the answer has nowhere to go.

Customers will be looking to make progress on a given Job-To-Be-Done, and your product’s position will ensure it fits better (or worse) with that JTBD in the customer’s mind, informing your decision-making in the process and also moving you closer to others who position themselves similarly.

This ability to distance yourself from the existing mapping of the solution space, is one of the key principles of innovation. In particular, disruptive innovation, offers you a lens into product positioning where disruptive companies often counter position themselves to incumbents by drastically improving the product in one key dimension, while maintaing relative inferiority in others, which incumbents are still optimizing for, since their existing customer base continues to value them.

This, then, takes us to one of Disruption Theory’s key insights: incumbents get disrupted by doing the right thing for their customers, not by being negligent of their needs.

It is simply that they are unable to optimize for an emergent segment, which values the disruptive dimension, while trading-off others that are over-served by the existing competitive landscape. This allows disruptors to underprice, grow rapidly and more nimbly with a given segment and attack new emergent market facets faster than their competitors can respond to them, and grow through hyper-specialization in relation to the type of value chain that is being designed by the market agents.

Counter-positioning also is a way to develop one of my favorite concepts, that of building your own proprietary distribution channel, fueled by your hyper-fit with a target segment’s needs. This, in Sam Altman’s view (at YCombinator), is how to grow huge. Tap into a fast-moving, high-reach distribution channel, and use the love of your key advocates to optimize your distribution. This, again, speaks to how these trade-offs can make your product occupy the space in customers’ minds where you are seen as THE solution to one of their needs, instead of one of the solutions to some of their wants. That, is power.