Every time you say Data-Platform, God Kills a Kitten
A reflection on why one needs to focus on understanding and enabling the business context, before thinking about data
> Co-edited by Eugenio Battaglia and Simone Cicero
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The Post in Brief
- data is not a magic wand to solve a team’s little understanding of the context that the team is targeting with a platform strategy;
- especially in industrial contexts finding ways to de-fragment and break silos, competition patterns is key to make strategies that can generate network effects;
- designing share governance and shared investing programs are two very much needed practices to master platforms in industrial contexts.
It happens often lately — working with teams involved in transformation programs for large organizations — to hear their excitement to build what they call a “data platform”. The discussion often begins by imagining a great promise of value coming from the capability to aggregate data (at a certain moment in the future): data will make everyone smarter, everybody will want to consume data flows, data is everything.
I think it’s normal: we’ve been bombarded with the narrative of Big Data for years now. The problem with this way of thinking though is that, despite this focus on data, often no one in the team has a clear understanding of the ecosystem that data is supposed to serve.
When working with teams aiming at serving and shaping ecosystems, we often, therefore, help them sit back and create a map of the diverse pre-existing sub-contexts that the strategy is supposed to serve. In other words: it’s not enough to say that you want to create a “data-platform” (sorry 🐱) for this or that. Data is not a magic wand to solve a team’s little understanding.
If no one in the team has a systemic view of what’s going on in the ecosystem — and what the ecosystem is trying to achieve — focusing on the value of data will only be a false promise.
Data is not a magic wand to solve a team’s little understanding.
Think about aggregating Context instead of aggregating Data
Organizations are often divided in silos, with a separated scope and function: this is clearly a paradox if we think about the nature of the ecosystems they’re trying to serve which, instead, is a fuzzy continuum where the need to interact beyond walled gardens and boundaries is now pressing (read our post on the real future of platforms).
What we’re clearly understanding is that a fragmented vision of the world inevitably reflects on the way most businesses work (with units looking into industries, markets as separated contexts), and vice versa. The fragmented nature of business silos and lack of proper methods to integrate a shared contextual understanding of the world creates underperforming strategies.
Furthermore, contemporary strategies cannot be decided at a high level by allocating units the responsibility to shape this or that industry. Contemporary strategies can only be crafted contextually, in a direct relationship (an overlap) with the ecosystem they’re designed for. In the context, there’s meaning and purpose.
Instead of obsessing about aggregating data (often without a clear map), we should ask our organizations to create a transversal conversation that breaks across silos and, first and foremost, aggregate contexts. When crafting a platform strategy you’re in the business of connecting, making the work of simplifying complexity so that the ecosystem won’t have to. Crafting platform strategies essentially means to simplify so that interactions can happen at scale.
Before letting 10 teams launch their own “data platform” (whatever that means) hold on. Get them to craft a shared picture of the context(s) they’re serving, interact with each other, understand overlaps and opportunities.
We’ve created our Platform Opportunity Exploration process to share with our adopters a way to do that. The first step normally consists in picturing the interactions happening in the ecosystem with the Ecosystem Scan: catching the “weak signals” coming from existing behaviors is key to really understand what the ecosystem you’re designing for is trying to achieve. Other techniques might be used to complement and integrate: we’ve been experimenting overlapping our Ecosystem Scanning approach with Alberto Brandolini’s Eventstorming, adding an even deeper understanding of the domain, mapping behaviors not only by layers (infrastructure, aggregators, long tails) but also by the dimension of time.
The second step we always push our adopters to do, aims at analyzing the value-chain in the ecosystems you’re serving: identify what assets you can leverage on and what opportunities of platformization gameplay are available for you to adopt across context.
This steps will have a twofold effect: integrating the work to be done “inside” the organization (breaking silos, transforming processes) with the interactions happening in the ecosystem one is trying to mobilize. This will unveil how, in reality, no boundary exists anymore between inside and outside, or between different industries.
What is, in reality, the job you need to do as an ecosystem shaper?
Platform shapers today must play a decisive role: the talent agent.
Incumbents can leverage the reputation and industry understanding to support increasingly smaller players in delivering complex value flows, addressing larger market opportunities, improve.
To catch this opportunity your obsession should be about killing waste and bureaucracy, thus declaring a relentless war to any internal or external friction that generates unnecessary steps in transaction flows between entities in the ecosystem you’re facilitating.
When the reflection on inter-industry overlaps due to the idea of market expansion comes up, participants to our workshops often report that their companies are “not that simple”: existing business units may have conflicting interests on similar, or overlapped, markets, making it difficult to really think “beyond” boundaries and having unbounded strategies.
Constraining communication and interaction (inter-silos, inter-competition) is a hard job in a world where interaction wants to be free.
Artificial complexity due to political, bureaucratic reasons, is hardly tolerated today in a world where there’s a mounting performance pressure. A world where — as Hagel puts it — you need to be able to collaborate with anyone, anywhere. Complex business models have a particular way to solve these frictions: they tend to collapse.
Wherever there’s a fragmentation there’s an opportunity
Industrial, traditional markets are definitely some key innovation context of our future. Large cross-industry groups that target these markets, normally suffer from a strong fragmentation issue: sometimes it’s domain-driven, other times geographic, other times is just, well, political.
Aggregating contexts means defragmenting the industry you’re trying to serve. Fragmentation is a protector of technical, cultural and organizational debt in every industry. By defragmenting (aggregating) industries it will be possible to let the best solution providers emerge and give them the possibility to express their quality in a way bigger market than the one they originally used to serve. As Rita McGrath pointed out we (all) now compete in arenas — not industries.
Fragmentation is a protector of technical, cultural and organizational debt
Thinking boundaryless is key to really design platform strategies in formerly industrial contexts: if similar processes and tools apply to more than one industry contexts this calls for de-fragmentation. As an example: if a mechanical design agency’s services can apply to naval industries and urban transportation, why shouldn’t we — as aggregators — help this player explore this broader opportunity context? If a data scientist’s insights can help in financial services and healthcare investment planning: why shouldn’t we make a case for a continuous context across the two industries?
Context aggregation will generate bigger network-effects: this, in turn, will make growth possible and scalable learning opportunities for everyone to face uncertainty and performance pressure.
Context aggregation will generate bigger network-effects
Boundaryless Infrastructures and Platforms
As a consequential effect, we’ll increasingly have shared infrastructures and — to some extent — shared aggregators.
Advantages are obvious: having a common field, being it a technological or information infrastructure (such as software), or a more specific infrastructure (such as a network of physical assets) will make sense as it will “unbundle” the most basic layers from everything else, make them ubiquitous, thus making room for more aggregation strategies to be created on top, to aggregate producers and consumers on new niche markets.
Consolidate these fundamental infrastructure layers and standardize them, and creating a shared aggregation strategy for basic services on top of it, will have to be a multi-stakeholder initiative: we’ll increasingly need to learn how to deal with shared governance in industrial innovation.
Embracing a shared governance tactic from the beginning might be an essential move to success: platform shapers need to favor shared infrastructure strategies (à la Open Handset Alliance, Hyperledger, etc…) so that they can focus on service aggregation at higher value chain layers. Focusing on small, newcoming players may be a smart approach for an industry aggregator: in the case of OHA, Google wanted to create a shared Open Source Operating System (Android) and succeeded to do so by engaging with Chinese and Korean rampant handset makers, and by letting Nokia — at the time the dominator of the industry — to stay aside.
In this way Google encountered weaker resistance as opportunity/cost ratio for them was higher. Now that the infrastructural layer (in this case an information infrastructure) is common, Google could develop aggregators (Google Play) and vertically integrated services (Google Play Services). Read Ben Thompson’s on this topic, always illuminating.
In platform thinking, a bigger market is made of smaller markets (niches) and it’s therefore essential for platform-ecosystem shapers to focus on democratizing access (“Reduce Barriers to the Market”, Pattern E1 in our collection of Platformization Patterns). Serving the small is key: a great platform strategy needs to be designed to allow new entrants to onboard the market and quickly climb the ladder of growth and opportunity so that they can identify their niche and serve it greatly. In many cross-industry markets, this means focusing on upstart providers, providing niche applications, allowing them to connect internationally to several corporate customers.
A New Set of Perspectives
In large companies, the just described challenges often add up to generalized concerns on the short term sustainability of platform projects. People conscious that the inherent complexity of launching platform business models proves to be significantly more challenging than traditional product/service innovation efforts. For this same reason, conventional KPIs and metrics no longer fit the diverse and complex value flows inherent to platform business models.
Inevitably, this lack of metrics leaves a vacuum in the company culture around how to prove or disprove the viability of a given project, when competing on internal resources. Likewise, the inability to clarify the multiple value propositions of a platform business model precludes the possibility to quantify the potential benefits for each party involved, undermining the ability of a team to negotiate a critical partnership and collaboration agreements in the very early stage of a risky platform project.
In order to address this bi-directional issue, we believe that a number of initiatives can be undertaken, organization-wide:
- defining a newly shared glossary of value that stretches beyond immediate monetary benefit and assets optimization, but that rather starts from a deep understanding of ecosystem-centric value;
- allow the creation of new ecosystem-centric metrics — that measure the success of the partner’s ecosystem before that of the organizing brand — more fit to capture and assess the value of a platform strategy (see what Shopify is doing for inspiration);
- overturn traditional budget allocation practices towards direct investments practice as a way to improve teams’ skin-in-the-game: as an example the Chinese platform organization pioneer Haier is now overcoming the employer-employee relationship towards an investor-investee relationship, also letting Micro Enterprises to collect external investment and employee investment.
As already stated, players that are interested in launching Ecosystem-mobilizing strategies cannot ignore the topic of ecosystem-governance. It’s important to clarify joint gains and accountabilities as each party (internal or external) will chip in the strategy.
Those who are daring to think as an industry, and not just as a player, need to think as a standard-setting harmonizer that conveys opportunities not just of a single player but of an entire industry in the process of rethinking itself.
Necessarily, this has to be a wide, deep and urgent conversation that drives all innovation efforts in large groups. These reflections mark the shift from industrial customer-centric marketing to building ecosystem-mobilizing stories. A shift in the tone is needed in the age of platforms.
As we often say, a great platform strategy is not about telling how cool you are (as a shaper), but it’s about telling how great the ecosystem’s entities can be — if they join the context of play you’re building for them.
If you liked this post, it’s probably important for you to read our previous oped on data and platforms:
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