If a client needs to schedule internal development work to use your data, adoption will stall.
On paper, distribution looks easy. You expose an API. You publish documentation. You ship an Excel add-in. Job done.
Most financial firms already have APIs. They have cloud infrastructure. They have engineering teams capable of building connectors. Yet adoption of data and analytics products still lags ambition.
In practice, usage depends on what the client has to do next. Do they need a developer? Do they need a security review? Do they need to reconcile entitlement logic with their own systems? If the answer is yes, your “available” product is competing with everything else on their roadmap. And it will usually lose.
Excel is deeply embedded in institutional workflows. Traders run pricing sheets that have existed for years. Risk teams maintain layered workbooks tied to daily processes. Portfolio managers trust what sits on their desktop.
Replace them, and you are not modernising; you are disrupting.
At the same time, Excel is not enough. Clients expect APIs for system integration. They increasingly expect chat-based interaction for operational workflows. In some environments, chat is closer to a command line than an email replacement.
The real challenge is not choosing between channels. It is supporting several without duplicating entitlement logic, rewriting connectors and fragmenting governance every time a new endpoint appears. This is where many firms stumble.
They have market data. They have analytics. They have margin and trade services. But accessing those services often requires the client to assign a developer, schedule integration work and test connectivity.
That’s where friction creeps in. Not because the data lacks value, but because the path to it is inconsistent.
Internal distribution builds usually start clean.
A small team exposes an API. An Excel add-in is written. A chat integration is bolted on later. Entitlements are handled in one place, then partially duplicated somewhere else to satisfy a new client requirement. It works. For a while.
Then versions drift. One client is on v1.2 of an add-in. Another was never upgraded. A security review forces token changes. A re-platforming exercise breaks an integration that nobody fully documented. A new sales opportunity requires delivery into a different channel, and suddenly, there is no reusable pattern. The problem is not incompetence. It is entropy.
Over time, onboarding takes longer. Exceptions increase. A handful of engineers become gatekeepers because they’re the only ones who understand how the pieces fit together.
A more durable model treats distribution as a dedicated control layer between internal systems and client endpoints.
That layer handles:
Connectivity to Excel, chat platforms and APIs.
Entitlements across all channels.
Auditability and governance in one place.
Channel expansion without rewriting core logic.
When a new endpoint is required, chat, a new API consumer, or another desktop integration, the question shouldn’t be “how do we build this from scratch?” It should be “how does this plug into the existing control layer?”
Without that separation, every new delivery format reintroduces design decisions you thought you’d already solved.
Data as a service doesn’t break because APIs don’t exist. It breaks because each channel behaves differently and nobody owns the consistency across them.
Abaxx did not need more data. It needed participants to use the data it already had. Delivering real-time access to exchange data directly into Excel accelerating trader engagement and onboarding.
Ultumus faced a different pressure. Providing automated delivery of ETF and index prices into client desktop Excel, eliminating manual workflows and minimising complex client-side integration.
A Global Clearing House. Expanded usage of margin calculation services by embedding into Symphony and Excel, eliminating integration friction and accelerating client adoption.
In each case, the improvement was not cosmetic. It shortened the distance between “we offer this” and “clients actually use this.”
Supporting Excel, chat platforms and APIs simultaneously is no longer ambitious. It is the baseline.
An omnichannel strategy only works if entitlement, governance and connectivity are consistent across endpoints. Otherwise, each new delivery format introduces another set of rules, credentials and failure modes.
Channel proliferation is accelerating. Workflow tools will continue to evolve. If distribution is fragmented, complexity grows linearly with each addition. If it is unified, complexity grows far more slowly.
This is not cosmetic architecture. It affects sales cycles, onboarding timelines and ultimately revenue predictability.
Most financial institutions do not lack valuable data. They do not lack analytics. What they lack, repeatedly, is frictionless adoption at scale.
If clients must invest engineering time to use your service, usage will be limited by their roadmap, not your ambition.
When services appear directly inside the environments clients already use, Excel, chat platforms, APIs integrated into internal systems, adoption becomes a function of relevance rather than integration effort.
Data distribution is therefore not a technical footnote. It is the layer that converts capability into usage. And usage is what drives revenue. Learn more about ipushpull's data distribution services.