Data & AI / Business intelligence

Your data,
finally clear.

From data scattered across five systems to decisions in real time. We gather, model and visualise your company’s information in clear dashboards, so you can stop deciding on gut feel and start deciding on what is actually happening.

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What it is

From scattered data to
clear decisions.

Business intelligence (BI) means gathering the data your company already generates, modelling it so it is consistent and visualising it in a way that supports decisions. The result is dashboards and KPIs: screens where each person sees, at a glance, how the things that matter to them are going and what they should do about it.

The key is not the charts but what sits beneath them: a single, reliable data model where “customer”, “sale” or “margin” mean the same thing across the whole organisation. That is the real leap —from having data (lots of it, split up and contradictory) to having information everyone trusts. A good dashboard does not hand you figures; it tells you where to look and what is out of the ordinary.

BI is part of our data and artificial intelligence practice, and it is almost always the best place to start: high impact, low risk and a foundation that makes everything else possible. Without ordered, trustworthy data, no predictive analytics or AI is worth much; with it, every decision becomes faster and more honest.

Problems it solves

When the data exists
but does not arrive in time.

Reports that live in Excel

Every month, someone spends days copying data, pasting tables and rebuilding the same report by hand. By the time it is ready, it is already out of date.

Numbers that do not match

“Why do your sales figures differ from finance’s?” Without a shared model, every spreadsheet tells a different story and no one trusts the number.

Decisions in the dark

Choices get made on gut feel or on what happened last time, because the data exists but is buried across five systems no one connects.

Every team with its own version

Sales looks at the CRM, marketing at its platform, operations at the ERP. Six dashboards, six truths and no meeting where everyone sees the same thing.

Reports that arrive too late

By the time the monthly report is on the table, the problem has already passed. The information lands when it is too late to act on it.

No real time

Knowing how the business is doing today —not last month— means an email, a call and a wait. The picture is always from yesterday.

What we measure by area

One indicator for
each question.

Every area has its decisions and, therefore, its metrics. These are the KPIs we are asked for most, by department:

Sales — pipeline, conversion rate, average deal size and close forecast
Finance — revenue, spend, cash flow, overdue accounts and budget variance
Operations — output, lead times, incidents, stock and SLA compliance
Marketing — cost per lead, CAC, return by channel and sales cycle
HR — headcount, turnover, absenteeism and time to hire
Customer support — ticket volume, response time, SLA and satisfaction

Cases by department

What each team
sees.

Department	What it needs to see	Decision it enables
Leadership	Business health on one screen: revenue, margin, cash and targets.	Spot deviations early and prioritise where to step in.
Sales	Pipeline by stage, conversion, average deal size and close forecast.	Focus effort where the odds of closing are highest.
Finance	Revenue, spend, cash flow, overdue accounts and budget variance.	Anticipate cash pressure and control spend in real time.
Operations	Output, lead times, incidents, stock and SLA compliance.	See bottlenecks as they happen, not in the month-end report.
Marketing	Cost per lead, CAC, return by channel and time to sale.	Reallocate budget to the channel that actually drives business.

The core idea

A good dashboard doesn’t give you data: it tells you what to do.

Benefits and outcomes

What you can
expect.

A single source of truth

No more arguments over “which number is right”. A shared model and agreed definitions: everyone sees the same thing.

Information in real time

Know how the business is doing today, not last month. The data refreshes on its own, at the frequency each decision needs.

Self-service

Each person opens their own dashboard, filters and finds their answer without depending on IT or waiting for Friday’s report.

Catch problems earlier

A deviation, a customer going quiet, a margin slipping: the dashboard flags it while there is still time to act.

Decisions with data

Less “I think” and more “this is what it shows”. The conversation changes when everyone looks at the same evidence.

Fewer hours on reports

The time spent copying, pasting and reconciling spreadsheets goes back into analysis and decisions —which is where value lives.

Tools and approach

The tool matters less
than the model.

Power BILooker StudioMetabaseGrafanaTableauData warehouseSelf-service BISingle source of truthSQLETL / ELTdbtSemantic layer

We choose the tool by your ecosystem and by who will use the dashboards, not by fashion. Underneath there is always a clean data model and a single source of truth; that is what makes a dashboard trustworthy.

The CPPA method

From raw data to
everyday decisions.

Define the KPIs

We start with decisions, not charts. What questions does each person need to answer? That is where the metrics that actually matter come from, each with an exact definition everyone agrees on.

Model the data

We gather the sources (CRM, ERP, spreadsheets, platforms), clean them and combine them into one coherent model. Making “customer” mean the same thing across the company is half the work.

Build the dashboards

We design clear dashboards with visual hierarchy: the important things large, the detail one click away. Fast, readable on mobile and built to answer questions, not to impress.

Adopt and improve

We train the teams, define who maintains what and refine with real usage. A dashboard nobody looks at is worthless; we measure adoption and let it evolve.

Dashboard examples

How it looks
in practice.

Sales dashboard

Pipeline by stage and owner
Conversion rate and average deal size
Close forecast for the month
Top products and customers
Alerts for stalled opportunities

Finance panel

Revenue and spend for the period
Cash position and forecast
Variance against budget
Overdue accounts and ageing
Margins by business line

Operations control

Production volume and status
Delivery times and delays
Open incidents and SLA
Stock levels and stockouts
Productivity by team or shift

Leadership KPI board

Revenue, margin and target
Cash and runway
Customer acquisition and retention
Indicators per area at a glance
Traffic light for critical deviations

Risks and mitigation

Why some BI projects
fail.

A BI project rarely fails because of the technology. It fails because of the data, the wrong metrics or because nobody uses it. Here is how we prevent that:

Dirty, ungoverned data

A pretty dashboard on bad data multiplies the confusion. Before we visualise anything, we secure data quality and define who owns each source. Without data governance there is no trust.

Vanity metrics

Measuring for the sake of it fills screens with numbers that change no decision. We focus on actionable KPIs: every indicator must connect to something someone can do when they see it.

Nobody uses it

The number-one cause of BI failure is not technical, it is adoption. We counter it with clear design, real training and dashboards built with the team that will use them, not just for them.

Report sprawl

Left unchecked, everyone builds their own version and we are back to the chaos of a thousand spreadsheets. We establish governance: certified reports, single definitions and one shared source of truth.

Frequently asked questions

What exactly is business intelligence?

Business intelligence (BI) is the set of practices and tools for gathering your company’s data, modelling it and turning it into visual information —dashboards, KPIs, reports— that supports decisions. In short: turning scattered data into clear answers to business questions.

Which tool do you build it with?

The one that fits your case best, not the one that is trending. We usually work with Power BI, Looker Studio, Metabase, Tableau or Grafana, depending on your ecosystem, budget and who will use the dashboards. The tool matters least; what makes the difference is the data model underneath.

Where does the data come from?

From the systems you already use: CRM, ERP, spreadsheets, marketing platforms, databases, support tools and more. We connect them, unify them into a common model and —if the volume calls for it— centralise them in a data warehouse. You do not need to change how you operate.

Can it be seen in real time?

Yes, where it adds value. Many indicators refresh perfectly well every hour or every morning; others —operations, support, same-day sales— make sense near real time. We set the frequency by the decision each figure informs, without overpaying for a real time nobody checks at 3 a.m.

Can anyone on the team use it?

That is the goal: self-service BI. We design dashboards anyone can read and filter without knowing SQL or asking IT for help. Each person accesses what concerns them, with clear permissions, and finds their answer in seconds.

How long does it take to be ready?

A first high-impact dashboard is usually in production in weeks, not months. We start with the case that hurts most —typically sales or finance— get it live and expand from there. The timeline depends mostly on the state of your data, not on the dashboard design.

Related services

Keep exploring.

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Which decision are you making in the dark?

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Want to see how we read a business through its data? Read ourCPPA X-RAY on 100 Montaditos.

Your data,
finally clear.

From scattered data to
clear decisions.