# SERVICE / 04
Dashboards your CEO
actually reads
Finance's 'revenue' doesn't match sales' 'revenue,' and the CEO has noticed. The 47 dashboards nobody opens are a definition problem, not a visualization problem. We build the KPI tree, lock metric definitions with stakeholders before anything is built, and ship dashboards leadership actually opens on Monday morning.
# THE-PROBLEM
why this matters.
Dashboards exist but decisions don't improve. You have 47 reports and nobody agrees on what "revenue" means. Leadership asks for a number and gets it three days later in a PDF.
- Finance, sales, and ops each have their own version of "revenue"
- Reports built by one person who left — nobody can update them
- Decision-makers wait days for a number that should be instant
- User-level tracking that probably violates GDPR, but nobody checked
- New dashboards keep getting built, but old ones never get retired
// symptoms
# IS-IT-FOR-YOU
best fit · not ideal.
- Different teams report different numbers from the same data
- Dashboard proliferation has outpaced dashboard trust
- You already have a data warehouse but no agreed-upon semantic layer
- You want fewer, better dashboards — not more
// best fit for
- Teams without a data warehouse yet (we'd need to build that first)
- "Just make it pretty" visual refreshes of existing reports
- Organizations unwilling to invest the time to align on KPI definitions
// not ideal for
# OUR-APPROACH
how we deliver.
-
Decision mapping
Map which decisions your business makes and which data they actually need. Most dashboards fail because nobody asked this first.
-
KPI framework
Build a hierarchy from board targets down to team inputs. Get stakeholders to agree on definitions before a single dashboard is built.
-
Dashboard build
Power BI or Looker Studio — based on your stack, not our preference. Row-level security, semantic layer, self-serve from day one.
-
Enablement
Your team can create new reports, modify existing ones, and trust the data underneath. No tickets to IT for a new chart.
# OUTCOMES
what good looks like.
- Shorter decision cycles
- 65%
- Version of the truth
- 1
- No IT tickets for reports
- Self-serve
- Privacy-first analytics
- GDPR-safe
# TECH-STACK
technologies we use for business intelligence & strategy.
production-tested tools and frameworks — not a wish list.
# DEFINITION
what is business intelligence & strategy consulting?
Business intelligence consulting transforms fragmented reporting into aligned KPI frameworks and self-serve dashboards that drive faster, evidence-based decisions. We build this in Power BI and Looker Studio with semantic layers and privacy-first design for GDPR.
# FAQ
common questions.
-
We already have Power BI/Looker — do we need to switch tools?
Almost never. The tool is rarely the problem. We fix the data model, metric definitions, and access patterns underneath. Most clients keep their existing BI tool and get 10× more value from it. -
How do you align different teams on the same KPIs?
We run a structured KPI workshop with stakeholders from each team. We define every metric precisely — formula, source, owner, refresh cadence — and get written sign-off before building anything. -
What's a semantic layer and why do we need one?
A semantic layer is a shared definition of your metrics that sits between raw data and dashboards. It ensures 'revenue' means the same thing whether you're in finance, sales, or the board deck. We implement it in dbt or your BI tool's native layer.
ready to put business intelligence into production?
30-min discovery call. we'll bring an architecture sketch and a rough price band.
book-call// or write: hello@saloid.com · gräfelfing · de