Picture a mid-size textile wholesaler. Sales are up thirty percent compared to last quarter. But at the end of the month, the owner checks the bank account and finds almost nothing there. The accountant says the turnover looks fine. The sales manager says orders are coming in strong. So where has the money gone? In most cases the answer hides in two places: goods sitting in the warehouse and outstanding invoices waiting to be collected from customers. Watching these three numbers separately — sales, inventory and receivables — is no longer enough. You need to see all three together.
This is exactly what business intelligence (BI) software is designed to do. A BI program pulls together data from different parts of a company — the accounting ledger, stock movements and customer account balances — and presents summary figures on a single screen. This is not a tool reserved for large corporations. A mid-size trading or manufacturing firm can benefit from the same kind of reporting. In Turkey, accounting and ERP (enterprise resource planning) packages such as LOGO, Netsis and Mikro include reporting modules that serve this purpose. Some companies take a simpler route: they export data from their accounting program and combine it in a spreadsheet. The method differs but the goal is the same — getting three key figures side by side.
A sales figure on its own tells you very little. Say you invoiced five hundred thousand lira worth of goods during the month. That sounds positive. But what share of that was collected immediately, and what share was sold on credit? What is the average payment term on credit sales? Are customers actually paying on time, or are they stretching their terms? Without answers to these questions, celebrating a strong sales month is premature. A BI program turns these questions into numbers. Which customers have overdue balances, how long have those balances been outstanding, what is the total open receivables figure — all of this becomes visible in one place.
The inventory side tells a similar story. Goods sitting in the warehouse represent money tied up in physical form. The question is how long they have been sitting there. Inventory turnover — the average number of days it takes for goods to arrive and then be sold — is a straightforward measure of this. When turnover slows, the cash locked inside that stock increases. If you ordered a seasonal product three months early and sales moved slowly, the warehouse fills up and cash stops moving. A BI program shows inventory age: which product lines are moving quickly, which ones are stalling. Seeing this on a weekly basis gives you time to adjust purchasing decisions before the problem compounds.
The real value comes from reading all three figures together. When sales are climbing but collections are not keeping pace and inventory is not turning over, that combination is an early warning signal. It means cash will tighten within a few weeks. You do not need to wait for the end-of-month balance sheet to discover this. A simple weekly table that puts these three numbers side by side gives the business owner a signal several weeks in advance. When that signal appears, the steps to take are clear: push harder on collections, slow down new purchasing, or speak to the bank before things become urgent. Wait for the signal to arrive late, and those same steps become much harder to execute.
Setting up this kind of reporting is not complicated. If your accounting program is being updated regularly — meaning invoices, receipts and stock movements are entered day by day — the remaining task is simply designing the right report. Some ERP packages include ready-made templates for this. In other companies, the accountant or finance officer builds the table manually in a spreadsheet once a week. What matters is building the habit. Fifteen minutes each week looking at these three figures is enough to catch most end-of-month surprises before they arrive.
Before setting any of this up, ask yourself one honest question: is the data in your accounting program complete and accurate? Are invoice dates, payment terms and collection records entered without gaps? If the underlying data is unreliable, even the most capable reporting tool will give you misleading results. Data discipline comes first; reporting comes second. Companies that reverse this order end up with attractive-looking tables that lead to wrong decisions. Companies that get the data right first find that a weekly glance at these three figures clearly explains why cash tightens even as revenue grows — and gives them the time to do something about it.
This article was originally written in Turkish by Gökhan MERCANOĞLU on April 19, 2004 and has been automatically translated into English and other languages using machine translation.