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A. Estimated salary costs

This section allows you to convert the time spent on data quality issues into financial costs for the organization.

How many people in your company or department rely on data for their work?

What is the average annual salary per employee (including benefits)?

How many weeks of paid leave per year does an employee receive?

B. Productivity Loss

Estimate the time wasted managing inaccuracies or inconsistencies in data (missing, inaccurate, duplicate data, etc.).

On average, how many hours per week does an employee spend correcting or compensating for data errors?

C. Cost of Customer Incidents

Understand the financial impact of poor data on customer relationships.

On average, for a given incident, what do you estimate is the cost of customer dissatisfaction caused by poor data?

How often does this type of customer issue occur?


Per weekPer month

D. Costs of operations that must be repeated due to poor data quality

An operation that must be repeated is the result of non-compliance with an order, delivery, service provision, merchandise, etc.

How many operations are carried out per period?


Per weekPer month

What percentage of these operations need to be reworked due to data issues?

What is the average number of hours to rework each operation?

E. Compliance and Risk

Has bad data caused any legal or regulatory issues?

Has your company encountered compliance issues or penalties due to data quality issues?
NoYes

What is the potential cost of the fine?

F. Impact on Strategic Decisions

Include the costs of past bad decisions due to biased reports, dashboards, or AI models. These costs are highly subjective and difficult to assess: the aim here is to provide a low estimate.

Estimate the financial impact of the least costly data-related error of judgment in the past year.

How often do you believe such decisions occur?


Per yearPer quarter

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