Quality Improvements, Using Statistics for Decisions

by Sarah Mason










Decisions are constant, from choosing between choices of food items at breakfast to zoom shirt, we are required to make a plan or pick an option. Choice can be based on preference, I like toast, or I like cereal. Choice can be more quantitative. Putting numbers to grade and select the top idea or solution is a practical way to gauge what is values by users and how to make something more fitting.



What are Statistics?


Statistics: the practice or science of collecting and analyzing numerical data in large quantities, especially for the purpose of inferring proportions in a whole from those in a representative sample.


Understanding the past, and present can be provided by analyzing statistics from past and current data. Statistics include counts of features, averages, means, standard deviation, max/min. Statistics also includes more complicated details, correlation and regression. These analyses are specific and describe, diagnose, predict, and prescribe a story based on data.



Value of Statistics in QI


When making business decisions to ensure outcomes, quality becomes important. In most business models Quality Improvement (QI) becomes a constant cycle to maintain and keep a product or service relevant to its users. Whether the process is iterative or waterfall, Agile or ITIL, and many other business models, QI is key to the usability and utility of a product or service.


Using statistics, data shows a story about the past, present, and sometimes predictions for the future for guidance on steering change for ensuring usability and utility. The return on investment of applying statistics for data-backed metrics for improvement to assess, engage, and plan is high with making success 3x more likely in several studies including by Google in business planning. Making a decisions about how to improve a call center is quantitative and qualitative, but finding which types of calls are taking more time by pulling outliers from determining the mean call time and reviewing those that are outside the accepted deviation from the mean, can lead to an assessment of what needs changed based on a report of the type of calls that are not the accepted length in the call center based on taking the descriptive statistics of completed calls in a month.


Conclusion


Statistics are important to guide decisions for solid planning based on facts. The decisions are really based on wisdom and knowledge from the reporting for initiatives from teams or individuals. Providing guidance is the role of statistics for QI, and requires understanding the service or product and people.




Reference: https://www.thinkwithgoogle.com/



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Sarah Mason is a Healthcare Data Analyst and Founder Sarah Mason Consulting LLC.

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