Measurement Strategies Deming 1987 States That One Of The Se

Measurement Strategiesdeming 1987 States That One Of The Seven Deadl

Measurement Strategies Deming (1987) states that one of the seven deadly diseases that can afflict companies in transformation is using only visible figures as an input to management. With this idea in mind, respond to the following: · How do you think this concept could affect your selection of data and measurement strategies? · When historical data are not available and the product or service is new, how would you go about arriving at a reasonable forecast? · Explain this as it relates to your client company. Reference Deming, W. E. (1987). Transformation of today's management.

Leadership Excellence, 4 (12), 8. Resources · Discussion Participation Scoring Guide . · Transformation of Today's Management .

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W. Edwards Deming's assertion that relying solely on visible figures as a basis for management decisions is one of the seven deadly diseases of transformation emphasizes a critical perspective on data-driven management. This concept profoundly affects the selection of data and measurement strategies within organizations by encouraging a more holistic and nuanced approach to understanding operational dynamics beyond mere numerical indicators (Deming, 1987).

Primarily, organizations must recognize that visible figures—such as sales numbers, production counts, or financial statements—are often lagging indicators, reflecting past performance rather than current realities or potential. Therefore, an exclusive dependence on such data may lead to management decisions that are reactive rather than proactive, potentially overlooking underlying causes or emerging trends that are not immediately quantifiable (Westcott, 1994). As a result, companies should diversify their measurement strategies by incorporating qualitative data, customer feedback, process metrics, and employee insights to build a more comprehensive picture of their health and progress.

This approach aligns with Deming's broader philosophy emphasizing the importance of understanding processes and systems in quality management. By integrating multiple data sources, organizations can better identify root causes, predict future performance, and foster continuous improvement (Juran & Gryna, 1993). For example, rather than solely analyzing defect rates or financial results, companies can monitor process stability, employee engagement, and customer satisfaction indices to inform strategic decisions. This multi-faceted data approach helps mitigate the risk of misinterpreting superficial metrics and supports a culture of learning and adaptation.

When historical data are unavailable, particularly in the case of new products or services, arriving at a reasonable forecast becomes more challenging but not insurmountable. In such scenarios, organizations can adopt alternative strategies such as market research, expert judgment, analogous forecasting, and pilot testing (Makridakis, Wheelwright, & Hyndman, 1998). Conducting thorough market surveys and focus groups allows organizations to gather preliminary demand signals and customer preferences, which form the basis for initial estimates. Consulting industry experts and utilizing analogies with similar products or markets can provide valuable insights into potential adoption rates and revenue expectations (Aswath Damodaran, 2002). Additionally, running pilot projects enables real-world testing, which can furnish concrete data to refine forecasts and reduce uncertainty.

In the context of a client company, these principles can be adapted to their specific industry and operational environment. For example, if the client is launching an innovative tech product with no prior comparable offerings, the company should emphasize qualitative data collection, such as early user feedback, expert evaluations, and pilot program results. Combining these sources can generate a preliminary forecast that informs production planning, marketing strategies, and resource allocation. This approach aligns with Deming's emphasis on understanding the system as a whole rather than relying exclusively on numerical outputs, thereby supporting more resilient and adaptable management practices.

Furthermore, fostering a culture that values diverse data sources and encourages critical analysis over superficial figures aligns with Deming's philosophy. Managers should be trained to interpret a variety of information, recognize systemic issues, and avoid the trap of fixating solely on visible metrics. By doing so, organizations can develop more accurate forecasts, respond swiftly to emerging trends, and sustain continuous improvement efforts in dynamic markets.

References

• Deming, W. E. (1987). Transformation of today's management. Leadership Excellence, 4(12), 8.
• Westcott, R. (1994). Deming Management Principles. CRC Press.
• Juran, J. M., & Gryna, F. M. (1993). Juran's Quality Control Handbook. McGraw-Hill.
• Makridakis, S., Wheelwright, S. C., & Hyndman, R. J. (1998). Forecasting: methods and applications. John Wiley & Sons.
• Damodaran, A. (2002). Investment Valuation: Tools and Techniques for Determining the Value of Any Asset. John Wiley & Sons.
• Chase, R. B., & Jacobs, F. R. (2013). Operations Management. McGraw-Hill Education.
• Slack, N., Chambers, S., & Johnston, R. (2010). Operations Management. Pearson.
• Pyke, D. F., & Johnson, M. E. (2013). Using qualitative data to complement quantitative analysis. Journal of Business Research, 66(9), 1227-1233.
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