Reliable numbers, clear decisions.
Contradictory metrics and manual reporting slow down key decisions. We build a BI system with clear KPI logic and automated updates.
Why this matters
Numbers that show what missing BI costs
Three indicators that make the urgency around structured reporting immediately visible.
0 %
of companies do not use data for decisions
Although almost all companies collect data today, only 26 % make truly data-driven decisions. The main reason: missing unified data foundation and lack of trust in available numbers.
0 %
of analyst time lost to data preparation
Data analysts spend on average 40 % of their working time on data preparation and cleansing rather than actual analysis. A structured BI system shifts this ratio dramatically.
0–0×
ROI from data-driven decisions
Companies that invest in structured business intelligence and actively use it for decisions demonstrably achieve a 5- to 10-fold return on investment compared to competitors without structured analytics.
The reality: and what is possible
Status quo in most companies → With a structured BI system
Without BI system → current reality. With BI system → target state.
Status quo in most companies
Sales, finance, and management calculate the same metric differently. Meetings start with 20 minutes of debating numbers instead of making decisions.
Reporting depends on one person in controlling or IT who assembles data monthly. Leave or resignation stops the process.
BI tools were introduced but are barely used: because dashboards answer the wrong questions or the data is not reliable.
With a structured BI system
Every metric has a unified, documented definition. All departments work from the same foundation. No more interpretation debates.
Reports and dashboards update automatically. Reporting works because the infrastructure works: not because one person assembles it.
Dashboards are opened daily: because they answer the right questions, for the right people, on reliable data.
Where does your company stand on analytics?
15 questions · 2 minutes · free & anonymous
Measurable project results
What a structured BI system changes in daily operations
Not more reports, but reliable numbers that decisions can actually be based on.
Toggle comparison →
Before alpLytics
2 days
Manual effort for monthly reporting
Manual process · error-prone
Before alpLytics
4 versions
KPI definitions in the company
Manual process · error-prone
Before alpLytics
5 days
Time to available metric
Manual process · error-prone
Results vary by starting point. All figures from completed, anonymised projects.
Our approach: ADET methodology
From contradictory numbers to a decision infrastructure
Understanding decisions first
We do not start with data sources: we start with decisions. Which decisions are made regularly in your company? Which data is needed for them: and how reliable is it today? Where do conflicts between different number versions arise? Which metrics are missing entirely? Only this understanding enables a BI system that is operationally used.
Our approach: ADET methodology
From contradictory numbers to a decision infrastructure
Understanding decisions first
We do not start with data sources: we start with decisions. Which decisions are made regularly in your company? Which data is needed for them: and how reliable is it today? Where do conflicts between different number versions arise? Which metrics are missing entirely? Only this understanding enables a BI system that is operationally used.
Metric architecture & system design
Based on the analysis, we develop the metric architecture: unified definitions for all relevant KPIs, calculation logic, data sources, and update intervals. In parallel we design the technical system architecture: data pipelines, transformation layer, reporting layer, and dashboard structure: aligned with your existing infrastructure.
Pipelines, transformations, dashboards
We build the BI system in working increments: data pipelines, transformation logic, data model, reporting layer, and dashboards. Every metric is implemented according to its documented definition and validated against real data. Dashboards are developed in close collaboration with future users: not as a design decision by the consultant.
Independent operation & extension
We hand over the BI system so your team fully understands, operates, and can independently extend it. This includes technical documentation, a metrics handbook, and training for all relevant roles: from technical administration to business use.
„In one of the first projects I managed, we had implemented a BI tool that worked perfectly technically. Three months later nobody opened it anymore. The reason: we had designed the tool from the technology perspective, not from the questions people ask every day. That was my most important lesson in analytics. Since then every project we run starts with the question: which decision should better data improve?"
Dominik Wörz
Founder, alpLytics · Vienna
What you concretely receive
Concrete deliverables
Typical project results
up to – %
less manual reporting effort
–×
faster decision-making foundation
within <– mo.
to daily-used dashboards
Tools & Technologies
Proven technologies
Hover for details · We work tool-agnostically.
100 % Open Source
Keine Lizenzkosten, kein Vendor Lock-in
DSGVO-konform
Alle Tools laufen auf EU-Servern
Toolagnostisch
Das beste Tool für Ihr Problem — nicht mit Provision getrieben
bewährte Tools
in 6 Kategorien
Technologie-Rail
Airbyte
IngestionData integration from 300+ source systems: open source, no vendor lock-in
Typischer Einsatz
Data integration from 300+ source systems: open source, no vendor lock-in
Warum gewählt
Ausgewählt für Stabilität, Wartbarkeit und Team-Fit.
Stack-Fit
Quellsysteme verlässlich anbinden
Why alpLytics
What sets us apart from typical BI projects
No tool setup without a data foundation. No metrics without shared definition. No go-live without training.
Decision-oriented
Tool implementation is not the goal
alpLytics starts every BI project with the question of which decisions in the company should be improved by better data. Only then come metric definitions, data model, and system architecture. This sounds obvious: in practice it rarely is.
Metrics defined together
Not top-down, but with the users
Metrics that only the external consultant understands are not useful metrics. alpLytics develops metric definitions together with the business teams: so future users know the calculation logic, trust it, and can communicate it internally.
Systems that get used
The benchmark is not go-live
The benchmark for a successful BI project is not go-live day. It is whether the system is still used daily six months later. alpLytics plans adoption, training, and handover from the start as part of the project.
Who is this for?
Typical profiles
We prioritise the roles where unreliable reporting causes the greatest operational damage.
CFO
Typical profile
Mid-size company with grown reporting
BI fit is clarified in a 30-minute initial consultation.
CEO
Typical profile
Mid-size company, 50–500 employees
BI fit is clarified in a 30-minute initial consultation.
Head of Sales
Typical profile
B2B company
BI fit is clarified in a 30-minute initial consultation.
Mid-size company with grown reporting
Monthly reporting is produced manually, regularly contains errors, and is never on time. Figures from ERP and CRM do not reconcile.
Mid-size company, 50–500 employees
No reliable overview of the most important metrics: without having to ask someone or wait for a manual report.
B2B company
Pipeline data incomplete, forecasts unreliable, campaign performance not measurable. No reliable view of sales performance.
Frequently asked questions
What clients usually ask
Next step
In 30 minutes you will know where the gap in your reporting lies.
Free initial consultation: we analyse your current reporting situation and show the most sensible first step. No tool pitch.
No automated follow-up · No newsletter · Just an honest conversation