The Five Retail and Distribution Reports Worth Building in Power BI First

Your retail or distribution business has Business Central, Power BI and plenty of data. But your managers still export spreadsheets to figure out what is selling, which inventory is sitting too long and where margins are disappearing.

The problem is not necessarily missing software. It is that nobody has agreed which information matters most or how to calculate it consistently.

The good news is that you do not need 25 dashboards to fix this. You need five useful reports, built in the right order, with reliable data behind them.

These are the retail distribution Power BI reports to prioritize, and what each requires from Business Central.

Why the order you build them in matters more than the list itself

Most reporting projects begin with a list of everything management wants:

• Sales performance
• Inventory turnover
• Customer profitability
• Supplier scorecards
• Labour productivity
• Forecast accuracy

Then somebody tries to build everything simultaneously. That creates five separate arguments about data definitions, five sets of integration requirements and five dashboards nobody completely trusts.

Tip: start with the report that addresses your most expensive operational problem.

The order below is a practical starting point, not a universal ranking.

1. Sell-through by store and SKU

This is where we would start for most multi-location retailers.

Sell-through measures how much available merchandise was sold during a defined period. A common calculation is units sold divided by units available for sale, but you must agree whether that denominator includes beginning inventory, receipts or both.

Consider a store that begins the month with 80 units and receives another 40. It sells 72. Using beginning inventory plus receipts as the denominator, sell-through is 60%. That tells the merchandise team something useful.

Now compare that SKU across 15 stores.

One location may sell through quickly while another has stock sitting untouched. The buying team can make a better decision about replenishment, allocation or transfers. Business Central can provide item, location, sales and inventory transaction information.

But there is a catch. If your point-of-sale system holds detailed store transactions outside Business Central, you need that data too. Do not assume every retail transaction is represented in Business Central at the level required for analysis.

Build this report first when your biggest problem is merchandise allocation and replenishment.

2. Inventory aging and dead stock

This is often the first report we recommend for distributors.

You need to know which inventory is consuming working capital without generating sufficient demand. Start with inventory value by item, location and age category. For example, you might define aging bands as 0–30, 31–90, 91–180 and more than 180 days.

Those are proposed management categories, not Microsoft defaults or universal industry standards.

Then separate slow-moving inventory from genuinely obsolete inventory. An item that has not sold for six months may be dead stock in one business and perfectly normal inventory in another.

Business Central provides item ledger entries, value entries, posting dates, quantities and inventory costs. But aging is not as simple as subtracting the last sales date from today. You need to decide whether you are measuring:

• Time since receipt
• Time since last movement
• Remaining inventory by receipt layer
• Time since last sale

Those produce different answers.

3. Margin by customer and by channel

Revenue tells you who buys the most. Margin tells you who contributes to the business.

Business Central can provide sales revenue, posted costs, customers, items, dimensions and related financial information. But define the margin before building the dashboard.

Gross margin based on recorded cost of goods sold is not the same as contribution margin after freight, payment fees, commissions and other channel-specific expenses. If those costs live outside Business Central, you need additional sources.

Also decide how returns, rebates and subsequent cost adjustments affect the calculation. A report that compares channels using inconsistent cost definitions is worse than having no comparison. We would build a reliable gross-margin model first.

4. Supplier on-time delivery and fill rate

Purchasing needs more than a list of late purchase orders. It needs to know which suppliers consistently deliver what they promised. Two useful measures are on-time delivery and fill rate:

• On-time delivery compares the actual receipt date with an agreed target date.
• Fill rate measures the quantity supplied against the quantity requested or due, using a defined measurement period.

For example, if a supplier was expected to deliver 200 units and delivered 150 by the agreed date, the quantity-based fill rate for that commitment is 75%.

Be careful with the date. If you overwrite the original date every time a supplier changes its commitment, the report can make unreliable suppliers look dependable.

Business Central contains purchase orders, purchase lines, expected receipt dates and posted receipt information. It may not preserve every historical supplier promise in the form your scorecard requires. If original commitments and subsequent revisions are not captured, you need to start collecting that information before claiming to measure supplier reliability accurately.

This is a good example of a report exposing a process problem rather than a software problem.

5. Labour against sales by location

This report belongs near the top of the list for store-based retailers. It compares labour consumption with sales activity at the location level.

Common measures include labour cost as a percentage of sales, sales per labour hour and labour hours against transaction volume.

Consider two stores generating the same weekly revenue. One uses 400 paid labour hours. The other uses 520.

That difference deserves investigation, but it does not automatically mean the second store is inefficient. It may operate longer hours, handle more returns, provide installation services or have a different mix of transactions. The report needs enough context to support a fair comparison.

Business Central may contain sales and payroll-related financial postings. It generally should not be assumed to contain detailed employee schedules, clock-in and clock-out records or actual labour hours. Those often live in payroll, timekeeping or workforce-management systems.

Power BI can combine the sources. But location identifiers, payroll periods, sales dates and labour-cost allocations need to match. Start with sales per paid labour hour and labour cost as a percentage of net sales. Then add operational context before turning the results into performance targets.

What each one needs from Business Central, and what it does not hold

Before development begins, map the data sources.

For relatively contained requirements, Power BI can retrieve data through Business Central APIs and combine it with other sources. Do not introduce Microsoft Fabric solely because you are building five dashboards. First establish the data volumes, refresh requirements, integration needs and reporting architecture.

The trap of building all five at once

Five reports sound manageable. But each introduces decisions about data ownership, definitions, permissions, refresh schedules and validation. Build all five simultaneously and those decisions multiply.

You may discover that the same customer has different identifiers across systems, that item categories are inconsistent or that store locations are named differently in payroll and Business Central.

We recommend completing one report end to end:

1. Agree on the calculation.
2. Validate the results against source transactions.
3. Confirm who owns the metric.
4. Test the refresh process.
5. Put it in front of the people making decisions.

Then build the next one using the definitions and data model already established.

Where to start

Start with the business decision you are currently making without reliable information.

• If purchasing cannot identify excess stock, build inventory aging.
• If merchandising cannot compare product performance across stores, build sell-through.
• If finance cannot explain why revenue is growing while profitability is not, start with margin.

Choose one report. Define the metric. Identify the required data. Validate the numbers.

Then expand.

Qixas Group works across Business Central, Power BI and Microsoft Fabric, with deep experience in retail and distribution operations. We help organizations improve the systems they already have before adding more technology.