You could be selling metals or farm produce, not technology. But technology plays an ever-increasing role in your ability to build and sustain competitive advantage.
Popular narrative emphasizes tech hype cycles – NFTs in 2021, Metaverse in 2022, and well, generative content creation in 2023.
But what’s far more important is how shifts in tech shape shifts in competitive advantage.
You may not need an NFT strategy in 2022. Or a metaverse strategy in 2023.
But you will always need to understand how to develop competitive advantage for your business and how tech shifts provide new tools in your strategic toolkit.
This post is about such tools that have become increasingly important over the past few years.
Drawing on work I’ve published particularly this past year, but also in 2021 and 2022, this post lays out nine different forms of tech-driven advantage.
The interface advantage
The cross-subsidization advantage
Thebrand integration advantage
The vertical integration advantage
The unbundling advantage
The composability advantage
The interoperability advantage
The community advantageAnd most important…
The rebundling advantage
1. The interface advantage
In an attention economy, control of the user interface is one of the strongest sources of competitive advantage!
It is also one of the most deeply contested value bottlenecks in any ecosystem, allowing you greater negotiation advantage over all other players.
Business models are built around scarce and tradable resources.
Tradability affords value transfer and scarcity affords negotiation leverage in such transfer.
Attention is both scarce and tradable.
Attention is scarce – yes, because the sum total of human attention is a finite number.
But more important, with an abundance of content and interactions, our decision-making ability gets depleted, allowing our attention to be more manipulable as a resource.
Attention is also tradable. Sophisticated auction mechanisms trade our attention (and the attendant decision – which is already manipulable) to the highest bidder.
Your goal as the interface of choice is to manage both the scarcity and tradability of attention.
b. Interface advantage = Primacy of relationship + control point
You gain the right to manage attention scarcity by gaining primacy of the user relationship through a core use case on which you have primacy of user relationship.
You gain the right to manage attention tradability by ensuring you own a key control point through which user attention may be traded with third parties.
How do you gain primacy of the user relationship?
Here, we need to make a distinction between primary demand and secondary demand.
A homebuyer has primary demand for a house. This primary demand generates secondary demand for mortgage.
In healthcare, the primary demand for cure and wellness creates secondary demand for pills and procedures.
The secondary demand is a means to an end, the primary demand is the end.
In an industrial economy, serving secondary demand was hugely profitable as long as you owned proprietary channels (e.g. bank branches, clinics etc.) and some form of regulatory moat (e.g. license to operate).
In an attention economy, where consumers are constantly connected and attention is both scarce and tradable, owning the primary demand is key.
The firms that own primary demand will eventually commoditize the ones that own secondary demand.
This is why banks want to move ‘beyond banking’ because they see profit pools shifting into the primary demand that ‘wraps around’ their product lines.
To build an interface advantage, you need primacy of user relationship and that is best owned by owning a core use case in the primary demand.
Here’s the full deep-dive, with a particular focus on the one business model that rules them all at the interface – the super-app model:
How do the BigTechs crowd startups out of entire layers in the value chain?
They leverage a fourth tool in the toolkit: cross-subsidization.
Cross-subsidization allows you to build one deep profit pool and commoditize multiple complementary value chain layers by deeply subsidizing capabilities at those layers and starving the layer-specific players for profits.
If you’re an incumbent, this is by far the strongest tool in your toolkit.
a. Commoditize the complement
How to lose at Gen AI (the most read post of the year) explains how cross-subsidization helped incumbents beat startups for the IoT prize.
Most incumbents – companies like Schneider, Johnson, and Honeywell – subsidized IoT services and bundled in the connected services with their existing profit pools where they charged for devices.
Clueless startups looking to capture value on connected services tried to subsidize their hardware and were left footing a huge manufacturing bill for subsidizing low quality hardware that took them nowhere.
Incumbents, instead, ‘commoditized the complement’ and increased the value of their devices by bundling in subsidized connected services – a huge business model advantage.
Effectively, startups footed the experimentation and customer discovery bill while incumbents captured all the value.
b. Cross-subsidization in Gen AI
Something similar is now playing out in Gen AI as well.
Incumbents can subsidize AI by bundling it with an existing already-working profit pool. Startups, instead, need to charge for AI. Workflow-only startups that gain traction but don’t own a proprietary model may get stuck with a huge LLM API bill, making AI subsidization untenable even with heavy VC funding.
Startups focusing on innovation (largely prompt engineering and UX) at the workflow layer are merely footing the bill for finding product-market fit, while a well-positioned incumbent on the prowl can swoop in once early signs of product-market fit are visible.
c. The BigTech get Bigger
And the BigTechs – who redrafted the cross-subsidization playbook for digital value chains – are poised to win in an especially big way:
At the compute layer, Microsoft, Amazon, and Google benefit from undeniable scale advantages with their cloud computing capabilities.
At the workflow layer, Google’s search dominance and Microsoft’s Office suite are examples of large installed bases that become more sticky when AI-aid is bundled into the workflow.
Finally, all these players are leading investors at the model layer. Google with its in-house efforts and Microsoft with its investment in OpenAI.
By vertically integrating across all three, these players get significant advantages both in terms of economics (lowering the costs of inference) and negotiating power (by squeezing out profits from players sandwiched in between their dominant layers).
How do you turbo-charge brand advantages in digital value chains?
By building integrated brand experiences, powered by an ecosystem of connected services.
As we note in the interface advantage above, owning the primary demand is a key tool in your digital competition arsenal. Integrated brand experiences uniquely position you for winning in the primary demand.
Consider the problems solved by brands like Nike and Sephora.
For Sephora, the primary demand for grooming and beauty drives the secondary demand for cosmetics.
For Nike, shoes constitute secondary demand, health and fitness are the primary demand.
By serving the primary demand of the customer, integrated brands command right of customer relationship and can intermediate the customer’s relationship with third parties which serve this secondary demand.
a. Sephora – the integrated brand advantage
Consider Sephora, for example, whose integrated brand experience integrates its in-store experience with its digital services and social networks, linked together through the user’s digitized profile.
Sephora has invested heavily in facial feature recognition AI to track facial features and build augmented reality experiences using this capability. Its integrated brand experience includes virtual try-ons to enhance its digital commerce experience. Sephora has developed services to help consumers sample different scents and fragrances.
It also engages its user community through social networks like Beauty TIP (teach, inspire, play), an integrated experience workshop, where customers learn via group beauty classes, using Sephora’s Virtual Artist technology, Beauty Board, and its gallery of products.
b. Nike – the integrated brand advantage
Nike orchestrates a similar integrated brand experience, combining a powerful brand with deep community engagement:
c. Walgreens – the integrated brand advantage
And Walgreens similarly orchestrates an integrated experience strung together around its loyalty program:
For a deep-dive on all three case studies, have a look at the analysis below:
Digital business models are notorious for running counter to vertical integration. Digital technologies reduce transactions costs and unbundle vertically integrated models.
Yet, while physical value chains get unbundled, a new form of advantage emerges in vertical integration:
Vertical integration across the data value chain!
This is best explained by looking at the role that demand-side data integration plays in supply network design and optimization.
Why is demand-side data integration so important to a successful supply chain play?
To understand this, let’s look at another online commerce player that defeated an offline incumbent through the sheer brilliance of its supply chain: Netflix.
If 2012 feels like ancient history, it’s worth calling out at this point that long before Netflix became the online streaming giant that it is today, it was a DVD rental startup delivering DVDs to doorsteps across the US. Blockbuster – the appropriately named incumbent – was the 800 pound gorilla that no one could unseat.
You could argue that there were many things that drove Netflix’s success in the DVD rental business. But the one thing that Blockbuster could never compete with was the integration of demand-side queuing data (users would add movies that they wanted to watch next into a queue) with a national-scale logistics system. All this queueing data aggregated at a national scale informed Netflix on upcoming demand for DVDs across the country.
Blockbuster could only serve users based on DVD inventory available at a local store. This resulted in:
1) low availability of some titles ( local demand > local supply), and
2) low utilization of other titles (local supply > local demand).
Netflix, on the other hand, could move DVDs to different parts of the US based on where users were queueing those titles. This resulted in higher availability while also having fewer titles idle at any point.
Queueing data improved stocking and resulted in higher utilization and higher availability. It allowed Netflix to serve local demand using national-scale inventory.
Notice the red arrows that I’ve thrown in there? Those are the two arrows that make all the difference.
One arrow ensures high availability of DVDs locally, the other arrow ensures high utilization of DVDs at national scale.
There was no way for Blockbuster to compete with Netflix within the framework of local inventory – local fulfilment. Netflix fundamentally changed that framework.
Traditional supply chains need to manage the trade-off between utilization and availability.
But the ability to predict demand solves this trade-off and informs stocking and logistics.
For more on this advantage, have a look at the deep-dive below:
Why offline retailers fail at online marketplaces
5. The unbundling advantage
How do you unseat an established incumbent, even more so a platform with well-established network effects?
Marketplaces bundled demand-side onboarding, decision support systems, and tools with supply-side onboarding, decision support systems, and tools. Protocols unbundle the two.
For instance, a marketplace like Ebay bundles seller onboarding, seller analytics, buyer onboarding, buyer decision support, search functionalities, and exchange infrastructure. All these components will be unbundled.
As a result, we move away from central market-maker architectures to decentralised agent-based architectures, all coordinated by a shared, common protocol.
Protocols are an effective way to attack established platforms. Yet, protocols win only under certain conditions.
b. The three laws of protocol-based unbundling
In The ONDC Conundrum, I lay these conditions out in the form of the three laws of protocol-based unbundling.
First:
A protocol creates value through unbundling to the extent that it can absorb and resolve the coordination costs originating from unbundling.
Unbundling can create a nightmare if the coordination costs aren’t sufficiently resolved.
Second:
The more the number of steps in the value chain you unbundle, the higher the coordination costs.
Third:
A protocol’s ability to absorb coordination costs is inversely proportional to the degree of variability in use cases it needs to directly coordinate.
Bringing all this together, we realize that protocol effectiveness may lie across a spectrum – from weak to strong.
The lower the variability in use cases and the lower the coordination costs, the stronger the protocol’s effectiveness at mediation.
The higher the variability in use cases and the higher the coordination costs, the weaker the protocol’s effectiveness at mediation.
If you’d like to read through a detailed analysis applying the above considerations, have a look at: