For many organisations, investing in a BI tool feels like it should solve the reporting challenge. This is a conversation I find myself having regularly. “We’ve already got a BI platform. If we need more reports, we can bring in a consultant.”
And increasingly, I also hear: “We’ve got a data analyst internally who can build what we need.”
Both of those statements are entirely reasonable. In fact, most organisations I work with have already invested in reporting in exactly this way. They’ve built dashboards, they’ve engaged external expertise, or they’ve hired resource, and on paper they have everything they need to succeed.
But when you spend a little more time with those same teams, a different picture starts to emerge, and it’s remarkably consistent regardless of industry or scale.
They don’t have a reporting problem. They have an operating model problem.
Reporting Is No Longer the Constraint It Once Was
We’ve reached a point where building dashboards is no longer the barrier it used to be. The tools are mature, the skills are readily available in the market, and whether through a consultancy or an internal analyst, most organisations are capable of producing well-structured, visually compelling reports.
However, that capability only solves the first part of the challenge.
Because once those reports exist, the conversation shifts, and this is where the friction begins to surface in a more meaningful way.
You start to see situations where the same metric appears in multiple places but never quite reconciles in the same way, where leadership conversations are slowed down because time is spent validating numbers rather than acting on them, and where despite having access to more data than ever before, teams still find themselves exporting information into spreadsheets simply to feel confident in what they are looking at.
Alongside that, there is a more subtle but equally important issue, which is that reporting tends to evolve more slowly than the business itself. Even in organisations with strong capability, it is not unusual for it to take months, and in some cases years, to fully develop the reporting landscape that the business is actually asking for.
At that point, the challenge is no longer about whether you can build reports.
It is about whether your approach allows you to keep up with the pace of change.
Why More Reporting Resource Alone Doesn’t Solve the Problem
It is often assumed that this is simply a resourcing issue, and that bringing in a consultancy or hiring a data analyst will resolve it.
In reality, what tends to happen is something quite different.
Consultants can absolutely accelerate delivery, particularly in the early stages, but over time the organisation becomes dependent on their availability, their prioritisation, and their cost model. What begins as a way to move faster can gradually become a constraint, especially when every change needs to be scoped, requested, and scheduled.
Equally, hiring a data analyst introduces capability, but it does not necessarily remove the bottleneck. In many cases, it simply internalises it.
The analyst becomes the central point through which all reporting requests flow, balancing competing priorities across teams, managing a growing backlog, and ultimately acting as a gatekeeper for access to insight. Not because they want to, but because the structure around them requires it.
I have seen teams with highly capable analysts still struggling to meet demand, not due to lack of skill, but because the model they are operating within does not scale.
The Shift from Proactive to Reactive Reporting
What sits underneath both of these scenarios is dependency, and that dependency has a very real impact on how data is used within the business.
When reporting relies on a third party, or even a small number of internal specialists, it fundamentally changes the nature of how insight is delivered.
Instead of anticipating what the business needs to know, reporting becomes reactive.
A question is raised, a request is submitted, a report is built, and by the time it is delivered the context has often moved on. The business is no longer using data to stay ahead, but to catch up with what has already happened. That delay is not always obvious, but it compounds over time, and it limits the organisation’s ability to respond at pace.
Where Self-Service Is Often Misinterpreted
This is usually the point where organisations look towards self-service as the solution.
However, self-service is frequently interpreted as enabling more people to build reports, which on the surface feels like the right direction, but in practice can introduce a new set of challenges.
Without a consistent structure, you begin to see multiple versions of the same metric emerge, each technically valid but contextually different, alongside an increase in workarounds and a growing reliance on informal “power users” who become the new gatekeepers.
In effect, you move from a centralised bottleneck to a distributed one.
True self-service is not about turning everyone into a report builder.
It is about removing dependency without sacrificing control, and enabling users to explore and interact with data confidently, knowing that what they are seeing is consistent, governed, and reliable.
Where the Model Begins to Break Down
As organisations continue to grow, these pressures become more pronounced.
Analysts become increasingly stretched, backlogs continue to expand, and teams begin to find alternative ways of working around the reporting function altogether. Decision-making slows down, not because the data is unavailable, but because it is not accessible in the right way, at the right time.
At this stage, the organisation is no longer constrained by tooling or talent. It is constrained by structure.
What Changes When You Shift the BI Reporting Approach
The shift that I see in more mature organisations is not about introducing more reporting, but about fundamentally changing how reporting is delivered and used.
It is a move away from a model where insight is requested and produced, towards one where it is anticipated, distributed, and embedded into the day to day operation of the business.
In practical terms, that means moving from an environment where reports are created by a small number of specialists and accessed intermittently, to one where insight is delivered proactively, exceptions are surfaced clearly, and users are able to explore and answer their own questions within a defined and trusted framework.
It is a subtle change in design, but it has a significant impact on behaviour.
The ROI of Changing the Reporting Operating Model
At this point, the conversation quite naturally turns to investment.
Because on the surface, it can feel as though you already have what you need. The tooling is in place, the resource exists, and reporting is being delivered, even if it is not always as quickly or consistently as you would like. However, the return on changing the model is not driven by producing more reports.
It comes from removing the inefficiencies and constraints that sit around them. One of the most immediate areas of impact is time.
When reporting is dependent on a small number of individuals, whether internal analysts or external consultants, a significant amount of time is spent waiting. Waiting for requests to be prioritised, waiting for changes to be made, and often repeating cycles of refinement before something is considered usable. That delay is rarely measured directly, but it accumulates quickly across teams and functions.
Alongside this is the cost of rework.
Where definitions are not centralised, the same logic is recreated multiple times across different reports, often by different people. Small discrepancies lead to further investigation, validation, and in some cases complete rebuilds. What appears to be incremental effort becomes a continuous drain on both time and resource.
There is also a less visible, but equally important, cost associated with missed opportunities.
When insight is delivered reactively, decisions are made later than they should be, or in some cases without the full context available. In fast-moving environments, the ability to act early is often where the greatest value sits. By shifting to a more structured, proactive model, organisations typically see improvements in three key areas.
Productivity increases as analysts spend less time building and maintaining reports, and more time on higher value activity, while business users are able to answer more of their own questions without waiting.
Decision making accelerates as insight is delivered earlier and in a more usable format, allowing teams to respond more quickly to both risk and opportunity.
Confidence improves as consistent definitions reduce the need for validation, allowing conversations to focus on action rather than accuracy.
Importantly, this is not about replacing existing investment. It is about ensuring that the investment already made is able to deliver its full value.
How We Approach This at Panintelligence
By the time organisations come to us, they are rarely asking for more dashboards. What they are looking for is a way to reduce dependency, increase confidence, and enable the business to operate at pace.
The way we approach this is centred on creating structure without removing flexibility.
We start by centralising definitions within a governed semantic layer, ensuring that metrics are defined once and used consistently across the organisation. This removes duplication, reduces ambiguity, and allows users to interact with data without introducing inconsistency.
From there, we focus on making insight more proactive. Rather than relying on users to seek out information, reporting is scheduled, distributed, and designed to highlight what requires attention, allowing the business to respond more quickly and with greater clarity.
Crucially, this is combined with an approach to self-service that enables users to explore and drill into data within controlled boundaries, giving them the ability to answer their own questions without needing to rely on a central resource for every request.
The role of the analyst does not disappear, but it evolves. Instead of acting as a bottleneck, they become an enabler, focusing on higher-value work while the wider business becomes more self-sufficient.
Reframing the Question
At this point, the conversation changes quite naturally.
It is no longer about whether you have the tools or the people to build reports.
It becomes a question of whether your approach allows you to use data consistently, confidently, and at the pace the business requires. Most organisations today have already solved the challenge of creating dashboards.
The more difficult, and more important challenge, is ensuring that data can be used effectively across the business without introducing delay, dependency, or inconsistency.
What worked when reporting demand was lower does not always hold up as expectations increase.
That is the shift and once you address it, reporting stops being something you produce, and becomes something the business operates with.
