Data scattered everywhere
“Our data is scattered everywhere.”
Scattered data is expensive in a way that never appears on a budget line. Consolidating it is less about a warehouse and more about deciding, once, where each fact lives.
What it looks like day to day
- Important numbers live in spreadsheets on individual machines
- Two reports on the same subject disagree
- Nobody can reproduce last quarter's figures
- Answering a simple question takes a day
What changes
Same capabilities. One system instead of several.
The modules below are the ones that answer this problem. On the left of the switch they are where most businesses keep them today; on the right they are on one engine, reading and writing the same records.
Scattered
The same capabilities, spread across tools that were each the right answer to a smaller problem.
How G1 approaches it
- Decide the system of record for each kind of data — and stick to it
- Import the history that matters; archive the rest honestly
- Define measures once so the same name means the same thing
- Export freely: the data stays yours, in a standard shape
Modules
What you would actually switch on.
Activated when they earn their place, not sold as a suite. The status on each one is the real one.
- PlannedExplore
Business intelligence
The wider data layer, for when finance is only part of the question.
- AvailableExplore
Analytics
Analysis on the live ledger, not a copy of last month's export.
- In developmentExplore
Documents
The paperwork attached to the record it belongs to.
- In developmentExplore
KPIs
Measures defined once, so nobody argues about the denominator.
- In developmentExplore
Customers
One customer record, whichever part of the business is looking.
Where it shows up
Industries where this is common.
Not a claim about who we work with — a note on where this situation tends to appear.
The human layer
Technology when you need it. Expertise when you need it.
Some of this is configuration. Some of it is a decision someone has to sit down and make with you. These are the people-shaped parts of solving this particular problem.
Data analysis
Analysis on your own data, for the questions that matter to your business. Margin, cost drivers, customer profitability, working capital — explained, not just charted.
- Definitions agreed before the numbers are argued about
- Drivers identified, not just variances reported
- Analysis you can repeat next quarter
Systems architecture
A view of the whole estate rather than one system at a time. Which tool is the system of record for what, how data moves, and what happens when you add the next one.
- One system of record per kind of data
- Integrations that reduce work rather than add it
- A path for the next system, before it arrives
Implementation
Configuration, migration and the unglamorous work of agreeing opening balances. The point is a system people actually use, not a go-live date that is technically met.
- Chart of accounts and dimensions designed once, used everywhere
- History migrated and reconciled before the first posting
- People trained on their own data, not a demo company
Usually next to it
Problems that tend to travel together.
Data scattered everywhere
Tell us how this actually plays out in your business.
We will show you which parts of G1 apply, what is live today and what is not — and say so when the answer is that you do not need us.