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Despite I’ve been touching the topic of digital ecosystem “layering” once in a while, I felt the need to come up with a quick framing model, something that could quickly help strategists, and designers understand better the context of modern ecosystems and platforms.

• What market are you addressing?
• What evolutionary forces operate in that market?
• What is the user value?
• What competition can/should you expect?

All these points are worth knowing before approaching the creation of a strategy, this post will help you address them.

To do this, I’ll correlate and explain mainly the three following aspects:

• value chains, and evolution of human activities (I’m going to borrow a lot from swardley here);
• the layering of digital markets, and the long tail (I’m going to use the seminal concepts introduced by John Hagel in the epochal “Hero’s Journey”, and later);
• aggregators and aggregation theory (here’s I’ll pick some from the amazing analysis from Stratechery’s Ben Thompson here).

Sometimes I’m a bit shocked to see how these concepts, that are more than 10 years old or at least clarified in the first half of 2010’s, are still so far from wide understanding. A recap is definitely worth. I hope the reader will enjoy and ideally save energy and money spent on addressing the wrong opportunity.

Understanding Value Chains and Evolution

I remember when I discovered the work of Simon Wardley, now probably something like ten years ago: that was an enlightening moment. Long story short (I definitely encourage you to dig deeper into his work), Simon’s maps and tools helped me to understand that all human activities evolve.

Evolution spans from a moment of invention (genesis)— when something is uncertain and novel — to a status where everything is well defined, where the activity is accessible everywhere, at a relatively affordable price (commodity). This evolution is driven by ever-increasing demand and — therefore competition.

From Genesis to Ubiquity

Essentially when something new comes up, it gets custom built — existing in one or few instances. If this “something” proves useful, demand increases and producer needs to make more of it. This results in producers demanding more standardized components to suppliers. In turn, more standard components make it possible for new producers to create competing instances of this “something” that, in the meantime, becomes a product (something that one can buy).

Within time, increased demand wants to access this product everywhere, and at any time, on the other hand, producers want to provide this product to larger cohorts of users: this ultimately drives the evolution of the product into a service and, ultimately, into a consumable utility.

It’s rather simple to relate this to the story of computing: from Eniac to standardized architectures (mainframes), to server farms with racks, to managed hosting, then cloud computing and now…serverless.

Ecosystems as a Future Sensing Engine

The definitive connection with our work on platforms came just a few years later when Simon so effectively explained how evolution connects with ecosystems in his “Understanding Ecosystems”, and “Platforms and Ecosystems “ (plus many more posts).

According to Wardley, ecosystems should be used by organizations as “future sensing engines”: the success of a modern company is related to creating tools for the ecosystem to allow the ecosystem innovate with a lower risk of failure.

In this continuous Innovate-Leverage-Componentize cycle the organization:

• makes tools and building blocks for the ecosystem to create new experiences, and innovations;
• watches how enabling blocks/services are used to create the new products, and services that sit on top of the enabling ones in the value chain;
• eventually standardizes these novel services, actually eating the ecosystem’s cake (pushing the ecosystem to create newer things, on top of the newly standardized products).

This process contributes within time, in cycles, to climb the value chain, eventually driving innovations. At the same time an “enabling” player like this (a platform/infrastructure) establishes a key position as an ecosystem organizer, enabler, and ruler.

I provided already an interpretation of the ILC cycle in the platform context in our “Design APIs for disobedience”, a talk and post presented last year at API days in Paris, also featuring a couple of key examples (Airbnb, Amazon…).
> Read below 👇.

The “triangle”: Long Tails, Aggregators, Infrastructures

In the meantime, another epochal piece of understanding of digital economies was coming up from Deloitte, and John Hagel’s team in 2014. The hero’s journey through the landscape of the future provided a nice complement to the basic understanding provided by Wardley.

The Hero’s journey, explained very clearly what are the three major areas of business available today and correlated them with two dominating dynamics of digital markets, fragmentation, and consolidation.

“Infrastructure management business: Infrastructure management businesses are driven by powerful scale economics, require skills to manage high-volume, routine processing activities, and have cultures that prioritize standardization, cost control, and predictability. The facility or asset trumps the human being.

Product/service business: Product/service innovation and commercialization businesses are driven by economies of time — speed to market — and, as a result, require skills focused on rapid iteration in design and development so that market opportunities can be quickly identified and addressed. The culture prioritizes creative talent — everything is oriented toward supporting the creative “stars.”

Customer relationship business: Customer relationship business types are driven by economies of scope — building broader relationships with a growing number of customers. This business type requires skills related to gathering and analyzing large amounts of data to develop a much deeper understanding of the evolving context of each customer. The culture of this business type is completely focused on the customer — the customer is king no matter how much internal turmoil and heartburn meeting customer requirements might create.”

Fragmentation

It’s easy to understand why the Product/Service context is subject to what Hagel calls fragmentation: you’ll be probably familiar with the concept of the Long Tail — introduced by Chris Anderson in the seminal book of 2006 (in case you’re not familiar with this, frankly, you should be worried).

Substantially: increasing demand of personalized services (from a customer point of view), the increasing penetration of powerful producer enabling technologies (think to 3D printing, mobile computing), and available ubiquitous infrastructures (think APIs, cloud services) make smaller producers more competitive and capable, while at the same time, reduce the investment needed to play the producer role.

This essentially means: the future is about smaller and smaller producers, able to thrive by connecting with their niche customer base.

I’ve always found Kevin Kelly’s 1000 true fans so powerful in explaining this:

“Every thing made, or thought of, can interest at least one person in a million — it’s a low bar. Yet if even only one out of million people were interested, that’s potentially 7,000 people on the planet. That means that any 1-in-a-million appeal can find 1,000 true fans.

The trick is to practically find those fans, or more accurately, to have them find you.”

Concentration

The last part of Kelly’s sentence “The trick is to practically find those fans, or more accurately, to have them find you.” teases the role that Customer/Relationship businesses have in modern ecosystem economics.

According to Hagel, Customer/Relationship businesses need to become “trusted advisors” and “talent agents”: able to connect consumers to the right product/producers, and producers (talents) to the right consumers and/or support services.

Despite it may sound confusing to see aggregation platforms in the same box as infrastructure providers, Hagel itself points out — and an attentive reader will do the same — how aggregation platforms, by leveraging network effects, attract all sort of demand and supply and therefore have the potential to play this “connection” role.

This is related to what we call “access and reach gains” in our Entity Portrait: the necessity that players have to connect with their “other half of the apple” (a consumer with the right producer and vice versa).

Furthermore by using massive data pools, aggregation platforms become able to be first predictive, and then prescriptive towards the user (as in John Hagel’s “The Big Shift in Platform Business Models”):

“data services […] have the potential to rapidly evolve into predictive data services and, most attractive of all, prescriptive data services that advise participants on actions they can take to increase value for themselves.”

It’s easier to see how both aggregation platforms (increasingly playing also the role of the C/R business) and infrastructure businesses have a clear tendency to concentrate:

• Infrastructures that make essential components cheap and ubiquitous, powering more and more aggregation platforms, and C/R business, are subject to concentration (growth-monopoly) because they need economies of scale and operate at the essential cost of business. Think AWS.
• Aggregation platforms (playing also the C/R business role often) are subject to network effects, needed to ensure the economies of scope (generate infinite different experiences): as it’s impossible to provide mass customization industrially (the cost of bureaucracy would make the process so costly that would be impossible to serve small customers), aggregation platforms need to connect the right producer to the right consumer for self serving each other, tend to become “the place to be” and often monopolize an industry. Think Airbnb.

We came out with a slightly different and more simplified view of the market with our triangle:

Where do you want to play?

So where do you want to play as an organization in these modern markets?

Do you want to make products and services? Be prepared to deal with an ever-fragmenting market (a market made of smaller and smaller niches), where your competition is going to abound.

Do you want to become an infrastructure provider? That’s more or less where most of the incumbents are now, due to their inertia and inability to innovate: think about banks, telco operators, retailers. That’s also the role that some of the digital giants (GAFAs) are playing, but in new fields: think Amazon Web Services or Google Cloud, but also think about Amazon Logistics, Facebook Graph APIs, Twilio and many others. There are several key issues with becoming an infrastructure provider though: for example having to compete with giants, and having to be so efficient to function at the lowest cost of business possible, with an ever-shrinking marginality. Not many survive.

We’ve been talking about the trends in infrastructurization and the shrinking opportunities for incumbents in our comment of Internet Trends 2018.
Read below 👇.

Be the Aggregator

At this moment it should be clear that the most promising role in the digitally powered (… everything?) economies of the XXIst century is that of the aggregator (platform): therefore is useful to highlight what are the key aggregator types, and what are their key characteristics. To do so I’ll refer (and adapt slightly) the essential Defining Aggregators — from Stratechery Ben Thompson — part of the Aggregation Theory series.

An aggregator is characterized by three essential characteristics.

First of all the aggregator controls the user relationship directly: this is, of course, true for the supply side, but increasingly and more importantly with demand side; as Thompson clearly puts it:

“there have always been far more users/consumers than suppliers, which means that in a world where transactions are costly owning the supplier relationship provides significantly more leverage. The fundamental disruption of the Internet has been to turn this dynamic on its head.”

In a world of plummeting transactions cost, the advantage is moving towards aggregating demand, and that’s what most of the successful aggregators do.

Furthermore, aggregators have zero marginal cost of connecting users to producers/products — sometimes because they provide entirely digital goods, other times because they use internet technologies to provide channels for self-managed coordination between peers.

Finally, by connecting multi-sided networks, aggregators have decreasing acquisition costs, due to the attraction of network effects: that’s the essential difference with traditional, pre-internet business, where normally the declining customer-product fit makes acquisition cost increase once the brand moves away from the initial cohort of “perfect” customers. Imagine the delicatessen shop around the corner: once the neighborhood’s customers are finished, it’s going to be rather costly to bring people in from the other side of the city.

When it comes to aggregator types, Thompson differentiates them according to the relationship they have with the supply side (as all of them normally aggregate demand in the same way):

• aggregators that acquire supply — e.g.: Netflix (that essentially buys or creates shows);
• sustain the cost of transaction to onboard a supply source that comes organically — e.g.: UBER (that needs to make background checks for new drivers);
• have zero marginal supply cost — e.g.: Google search or Facebook (if your page is not on Google you don’t exist, therefore you’ll optimize to be crawled).

Platform Evolution and Ecosystem Innovation

Once we understood these key mechanics of these digital economies and markets, we can correlate these with the key concepts of evolution and innovation. What does it mean to innovate in this context?

As I’ve been able to explain in my comment to Internet Trends 2018, innovating in the hyper-connected, and complex world we live in, is often about aggregating dis-aggregated experiences on top of what existing infrastructures provide.

This process aims at making novel experiences (genesis) available to larger cohorts of users (through aggregation), and, within time, transform these experiences into components (eg: APIs), making it possible for the ecosystem to combine these elements into more novel experiences.

Platform Evolution is therefore all about institutionalizing, and reducing barriers, to great experiences. The ecosystem is the one that is supposed to innovate (Ecosystem Innovation), by using available components to create something new. To quote again Simon Wardley, remember that the “ecosystem is a future sensing engine”. Do you want to sense the future? (This is, again, widely explained in Design for Disobedience).

Conclusions and a handy tool: the Platform Strategy Navigator

Here the reader can find a handy tool, that we’re experimenting these days in the flow of our masterclasses and workshops, in combination with other tools for exploration — such as our pattern library and horizon scanning tools.

The Platform Navigator is designed to be a quick recap that features a number of important questions you want to ask as soon as possible before you invest energy, and time into shaping a market with a platforms strategy.

Once you understand where you’re going to play, you’ll be able to play “what if” scenarios by looking at the current reality, through patterns of platformization, and understand how to use your identity advantages in developing powerful narratives, that drive network effects: the new moats of the digital age.

If you are interested in exploring platformization strategies for your organization let’s start a conversation, we can help 😎.

Do you want to learn how to use this methodology from the ones that created and evolve it? Join our upcoming Masterclasses.

A participant once said the masterclass: “changed the perception of what is possible”.

Check all available masterclasses here on our website or reach out directly for special deals and large groups.

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Icon Credit: young man by Gan Khoon Lay from the Noun Project