Weekly operating review
- Data loads overnight from operational systems
- Agreed KPI definitions calculate automatically
- Exceptions are highlighted by site and team
- Managers add commentary in the dashboard
- Leadership reviews one shared view
Dashboards and data platforms your business can trust.
Good decisions need one version of the numbers. VYSA consolidates data from the systems you run and builds the reporting your teams rely on.
Signs the current setup is holding you back.
- “Sales and finance bring different revenue figures to the same meeting.”
- “The Monday report depends on one person’s spreadsheet and one person’s week off.”
- “We can’t tell which customers are profitable without a week of exports.”
- “Our customer list has the same account under four spellings.”
What it is
Most businesses don't lack data. They lack agreement. Sales, operations and finance each pull their own exports, apply their own definitions and arrive at meetings with different numbers.
VYSA builds data platforms and dashboards around agreed definitions: what counts as a sale, a margin, a late order or an active customer. Data is consolidated from your systems on a schedule, so reports refresh instead of being rebuilt.
Where you already use a BI tool your team likes, we integrate with it and focus on the data model underneath. The definitions and the pipeline are what you should own.
Problems it solves
Different numbers in every meeting
Each team calculates the same measure differently, so time goes on arguing about the data instead of acting on it.
Reports built by hand
Someone exports, pastes and formats the same report every week, and it breaks when they're away.
Data stuck in separate systems
Sales, stock, jobs and finance can't be viewed together without manual joining.
Customer and product lists that disagree
The same customer or item exists several times with different names and codes.
Dashboards nobody opens
Reports were designed around available data rather than the decisions people need to make.
Example workflows
Customer profitability
- Orders, returns and service costs are consolidated
- Costs are allocated by agreed rules
- Margin is calculated per customer and product
- Sales sees which accounts to grow or reprice
Master data cleanup
- Duplicate customers and products are detected
- Data owners approve merges and corrections
- Clean records sync back to source systems
- New duplicates are blocked at entry
What VYSA might build
Data pipelines
Scheduled loads from your operational systems, with checks when something fails.
Data warehouse
A central store modeled around your business, not around each source system.
KPI definitions
Agreed, documented calculations that every report uses consistently.
BI dashboards
Views designed around the decisions each role makes, from the floor to the board.
Master data
One trusted list of customers, products, suppliers and locations.
Management reporting
Monthly and weekly packs that refresh rather than being rebuilt.
Alerts
Notifications when a measure crosses a threshold that someone cares about.
What we integrate rather than rebuild
Commodity problems already have excellent answers. We connect them to your system instead of rebuilding them.
Existing BI tools
If your team already uses a BI platform well, we feed it a clean model rather than replacing it.
Cloud data infrastructure
Storage and compute run on mature cloud data services in accounts you own.
Source system APIs
We read from your CRM, ERP, accounting and operational tools through their supported interfaces.
Spreadsheet sources
Where a spreadsheet is the real source, we connect it in a controlled way until it can be retired.
What changes day to day once it’s live.
Meetings start from the same number
Time moves from debating the figure to deciding what to do about it.
Reports that refresh themselves
Weekly and monthly packs update on schedule, whoever is on holiday.
Definitions written down
Anyone can check how a measure is calculated and who owns it.
Problems noticed early
Exceptions surface while they are small, not at the end of the quarter.
What you own at the end.
Your data platform is built as an asset of the business. How code, data and infrastructure are handed over is agreed in the project agreement before work starts, so there is no ambiguity about what you hold.
The definitions, pipelines and warehouse live in accounts you control. VYSA Care is available to run and extend the platform, but it is optional. The aim is that you stay because VYSA is useful, not because your numbers depend on us.
A typical rollout
- First: one decision, one dashboardWe pick the decision that matters most, agree its definitions and build the pipeline and view behind it. A single trusted number proves the approach before more is added.
- Then: more sources & shared measuresFurther systems load into the warehouse and the KPI library grows across teams. Each new source reuses the definitions and checks already in place.
- Later: master data & alertsDuplicate customers and products are cleaned at the source, and alerts flag measures that cross a threshold. Both rely on a model that is already stable and understood.
Relevant industries
Related systems
Questions
Do we need to replace our BI tool?
Usually not. If your team already uses a BI tool well, we focus on the data model and pipelines underneath so the tool shows numbers people can trust.
Which systems can you pull data from?
Most systems with a supported API or export, plus databases and controlled spreadsheets. We confirm each source during discovery.
How do you make sure the numbers are right?
We agree definitions with the people who own each measure, document them and test results against known figures before anyone relies on a dashboard.
How long does it take?
It depends on the number of sources and the state of the data. After discovery we plan in phases, usually starting with one decision area and expanding from there.
Tell us how this part of the business runs today. We’ll show you what a better system looks like.
Bring the spreadsheets, the workarounds and the tools you rely on. We’ll map what a Data & Analytics built around your operation would include, what to integrate and what to retire.