Sound familiar?
- Monday mornings are spent exporting CSVs and building the same spreadsheet
- Sales, finance and operations quote different numbers for the same thing
- You only see last month's performance halfway through this month
- Power BI was set up but the data behind it is unreliable
- Nobody can drill into a figure to see what makes it up
Key facts
- Data pulled automatically from accounting, CRM, ecommerce and operational systems
- One agreed definition for each metric, written down and coded once
- Dashboards built into a web app, or data modelled for Power BI or Looker Studio
- Scheduled reports by email or Microsoft Teams
- Drill-down from a headline figure to the underlying records
- Role-based access so each person sees the right numbers
The real problem is rarely the chart
Most reporting problems are data problems wearing a chart costume. Revenue means one thing to sales (orders taken), another to finance (invoices raised, excluding VAT) and another to operations (orders shipped). Customer names are spelled three ways across three systems. One export includes cancelled orders and another does not. A beautiful dashboard built on that will still start arguments.
So dijitul developments starts with definitions. Before we draw anything, we agree with you exactly what each metric means, which system it comes from, how it handles refunds, credits, VAT and timing, and who owns it. That metric dictionary becomes part of the project documentation, and the code follows it to the letter.
Good definitions also cover time. Is a sale counted on the order date, the invoice date or the payment date? Is a week Monday to Sunday? Does the financial year start in April? Small choices like these are why two honest people produce different numbers from the same data, and settling them once removes a surprising amount of friction from management meetings.
Getting the data in one place
Dashboards need clean, joined data. We build connectors that pull from each source on a schedule or as events happen:
- Accounting: the Xero API, QuickBooks Online API or Sage for invoices, payments, aged debt and profit and loss.
- Sales and CRM: your CRM's API, or the database of a custom CRM.
- Ecommerce: Shopify, WooCommerce, Magento or OpenCart orders, products and customers.
- Operations: job systems, stock systems, booking systems and spreadsheets that cannot be retired yet.
- Marketing: Google Analytics 4 and advertising platforms where relevant.
Data lands in a reporting database, usually PostgreSQL, where it is cleaned, de-duplicated and joined. Customers are matched across systems, currencies and VAT are handled consistently, and every row records where it came from and when. Each sync is logged, and failures alert someone rather than leaving a dashboard quietly stale.
Built-in dashboards or Power BI?
| Option | Suits | Considerations |
|---|---|---|
| Dashboards inside a bespoke web app | Operational screens used all day, customer-facing reporting, tight integration with workflows | No per-user BI licences; fully custom; built and changed by developers |
| Power BI | Businesses already on Microsoft 365 with analysts who want to build their own reports | Per-user licensing applies for sharing; quality depends on the data model underneath |
| Looker Studio | Lightweight marketing and sales reporting, Google Workspace users | Free to use; less suited to complex finance logic |
We often do both: a clean reporting database that Power BI or Looker Studio connects to for analysts, plus a few operational dashboards built into the business's own web application for staff who need live figures without learning a BI tool.
Dashboards people use
A dashboard should answer a question someone actually asks. We design each one around a role: a director's weekly view of sales, margin, cash and pipeline; a warehouse manager's live view of orders due out today; a credit controller's list of overdue accounts ranked by risk. Each headline figure links to the records behind it, so a surprising number can be checked in two clicks. Comparisons against last period, last year and target sit next to every key figure, because a number without context means little.
Scheduled reports deliver the same information to people who will not log in: a PDF in the inbox at 7am on Monday, or a message in a Microsoft Teams channel. Alerts fire when something crosses a threshold, such as a large order cancelled or cash below a set level.
Adding AI to reporting
Once the data is clean, AI becomes useful. We can add plain-English questions over your reporting data, written summaries of what changed this week, and anomaly flags on unusual movements. The AI works from the agreed definitions and shows the query behind each answer, so finance can trust it. See AI integration for how we keep it accurate and private.
Getting started
We start with a free chat and a list of the decisions your dashboards should support. Then we audit the data sources, write the metric dictionary, and give a fixed-price quote. Dashboards are often the first visible win in a bigger bespoke software programme, and they frequently reveal which systems integration work will save the most time. Get in touch.
What we deliver
- A metric dictionary agreed with your team
- Data connectors and scheduled syncs from each source system
- A reporting database or warehouse with clean, joined data
- Interactive dashboards with filters and drill-down
- Scheduled email and Teams reports and threshold alerts
- Exports for finance and board packs
How it works and what it costs
Every project gets a fixed-price quote after a free initial chat and a short scoping stage. You own the code and the data.
Free chat
Tell us the problem in plain English: what you do now, what goes wrong and what "better" looks like. No charge, no obligation.
Scoping
We map the processes, systems and data involved, agree what is in and out, and write it down so there are no surprises.
Fixed-price quote
You get a fixed price for the agreed scope, or a phased plan for bigger builds, so you can start small and prove it works.
Build and test
We build in short stages you can see and try, test against real data, then go live carefully with a rollback plan.
Hand over and look after
You own the code and the data. We can host it, support it and keep improving it, or hand it to your own team.
Frequently asked questions
Can you build a dashboard from Xero data?
Yes. dijitul pulls invoices, payments, aged debt and profit and loss from the Xero API on a schedule into a reporting database, then combines it with sales and operational data. Dashboards can live in a web app or in Power BI.
Should we use Power BI or a custom dashboard?
It depends who uses it. Power BI suits analysts building their own reports in a Microsoft 365 business. Custom dashboards suit operational screens and customer-facing reporting without per-user BI licences. dijitul often provides a clean data model for Power BI plus a few built-in dashboards.
Why do our reports show different numbers?
Usually because each system defines metrics differently, for example orders taken versus invoices raised, or figures with and without VAT. dijitul starts every reporting project by agreeing one definition per metric and coding it once.
Can reports be emailed automatically?
Yes. Scheduled reports can arrive as a PDF or summary email, or as a message in a Microsoft Teams channel, at whatever times you choose. Alerts can also fire when a figure crosses a threshold you set.
How much does a reporting project cost?
dijitul quotes after a free chat and a short audit of your data sources, because the number of systems and the state of the data drive the effort. You receive a fixed-price quote for the agreed scope.
Related
Tell us what you need to build
Free chat, clear scope, fixed-price quote. You own everything we build.