Data-Driven Decision-Making and Organizational Excellence
Abstract: Statistical thinking provides a conceptual framework for customer-centered process management, particularly in the area of data-driven decision-making. "Data-driven decision-making" bridges the gap between the three principles of statistical thinking by providing a collection of tools for analyzing data in such a way as to extract process knowledge from the numbers. While statistical thinking helps identify data to explain how process variation affects customers and Statistical methods help extract knowledge from the data, data-driven decision-making applies the knowledge gained to make sound decisions that benefit the customers and the organization. Obtaining dependable process data that accurately and objectively measures customer service is also a challenge. Since good process management depends on access to "good data", a procedure to collect good data is recommended. The importance of distinguishing between common cause variation and special cause variation is also discussed. Managers should beware of applying special cause solutions (training, meetings, counseling, etc.) to common cause situations because they will just make matters worse and waste useful resources.
Keywords: Process management - Statistical thinking - Data-driven decision-making - Measurement systems validation - Common cause - Assignable cause