{"id":11347,"date":"2026-10-27T10:22:47","date_gmt":"2026-10-27T09:22:47","guid":{"rendered":"https:\/\/powerbi.pl\/?p=11347"},"modified":"2026-10-27T10:24:23","modified_gmt":"2026-10-27T09:24:23","slug":"keeping-the-cost-of-poor-quality-under-control-with-power-bi","status":"publish","type":"post","link":"https:\/\/powerbi.pl\/en\/blog\/microsoft-power-bi-en\/keeping-the-cost-of-poor-quality-under-control-with-power-bi","title":{"rendered":"Keeping the Cost of Poor Quality Under Control with Power BI"},"content":{"rendered":"

The Cost of Quality Goes Far Beyond Customer Complaints<\/strong><\/h2>\n

The Cost of Poor Quality, or COPQ, includes both problems detected internally and those that reach the customer. ASQ distinguishes, among other categories, internal failure costs, external failure costs, appraisal costs, and prevention costs.<\/p>\n

From a business perspective, the most important point is that many of these costs are not recorded in a single accounting category.<\/p>\n

A production defect may be booked as material consumption. Additional transportation may appear as a logistics expense. Service work may be included in labor costs, while lost sales may never appear directly in the accounting system at all.<\/p>\n

When this information remains fragmented, management can see the consequences of quality problems in many different areas but cannot determine their total financial impact.<\/p>\n

Power BI Can Connect Quality, Finance, and Operations<\/strong><\/h2>\n

Building a complete picture usually requires data from several systems. ERP provides information on material costs, production expenses, and adjustments. MES can provide data on defects, production efficiency, and downtime. A quality management system stores information about nonconformities, while CRM or service systems contain customer complaints and service requests.<\/p>\n

This is why the foundation of the analysis is an appropriately designed data model in Power BI<\/a>. A nonconformity should be connected with the relevant product, batch, production line, supplier, customer, and specific costs. Only then can the organization move beyond a simple defect count and analyze the financial consequences of quality problems.<\/p>\n

For manufacturing companies, it is also useful to combine quality data with reporting on OEE, equipment failures, MTBF, MTTR, and downtime costs<\/a>. Quality issues rarely exist in isolation. They may be related to machine condition, process settings, material quality, or frequent changeovers.<\/p>\n

Which Costs Should Be Included in the Report?<\/strong><\/h2>\n

One of the biggest mistakes would be to reduce quality reporting to the number of customer complaints and the defect rate. For executives, financial information is far more useful.<\/p>\n

A dashboard can show quality costs as a percentage of revenue, cost per unit, and changes over time.<\/p>\n

Depending on the nature of the business, the analysis may include:<\/p>\n