How can you use statistics to evaluate your organization's decisions?

Decision-making is a crucial skill for any organization, but how can you measure the quality and impact of your choices? Statistics can help you answer this question by providing objective and reliable methods to collect, analyze, and interpret data related to your decisions. In this article, you will learn how to use statistics to evaluate your organization's decisions in four steps: defining your objectives, selecting your metrics, collecting your data, and interpreting your results.

1 Define your objectives

Before you can use statistics to evaluate your decisions, you need to have a clear idea of what you want to achieve and why. Your objectives should be specific, measurable, achievable, relevant, and time-bound (SMART). For example, if you want to improve your customer satisfaction, you should define what aspects of satisfaction you want to improve, how much improvement you want to see, how you will measure it, and by when. Having SMART objectives will help you focus your data collection and analysis, and avoid irrelevant or misleading information.

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Mohamed Ajdal DBA, CPCA®,PCM® ,Doctorate in Business Administration(In Progress)

FMCG Retail Expert +15 years | Professional Certified Marketer PCM® | CMA Certified Category Analyst CPCA® ,"It's not just about conveying the information, but how you tell the story to ensure the audience enjoys it."
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Statistics is one of the crucial steps you have to consider. You can use it to make a scorecard, which compares your current situation with your target or desire situation. You have to be sure that the process to convert raw data to clear information will be done in a good way.

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2 Select your metrics

Once you have defined your objectives, you need to choose the metrics that will help you measure your progress and performance. Metrics are quantitative indicators that reflect the key aspects of your decisions and their outcomes. For example, if your objective is to increase your sales, some possible metrics are revenue, profit margin, conversion rate, and customer retention. You should select metrics that are aligned with your objectives, easy to measure, consistent, and comparable. You should also avoid using too many or too few metrics, as this can make your evaluation confusing or incomplete.

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Erwin Hohn

Director at Institut IPA
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A correlation between what you want done & the metric you have chosen does not necessarily imply that the behaviour drives the metric. e.g. there is a correlation between towns with zoos & road traffic accidents (RTAs). This does not imply that zoos cause RTAs. Rather you need to look for the "hidden factor" that links them i.e. population density. More population dense areas are more likely to have zoos AND RTAs. Therefore, be sure that you understand the links between what you want to happen & the way you want to measure it. If you don't, you may have a serious flaw in the way you are assessing performance - especially if you are trying to measure things indirectly e.g. engagement leading to turnover.

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3 Collect your data

After you have selected your metrics, you need to collect the data that will help you calculate them. Data collection is the process of gathering and recording information from various sources, such as surveys, interviews, observations, experiments, or records. You should use reliable and valid methods to collect your data, and ensure that your sample size is large enough to represent your population. You should also follow ethical and legal standards to protect the privacy and confidentiality of your data sources. Data collection can be time-consuming and costly, so you should plan ahead and allocate enough resources for this step.

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4 Interpret your results

The final step is to interpret your results and draw conclusions from your data. Data interpretation is the process of applying statistical techniques and tools to analyze and summarize your data, and to test your hypotheses and assumptions. You should use appropriate methods for your data type and level of measurement, such as descriptive statistics, inferential statistics, correlation, regression, or hypothesis testing. You should also use visual aids, such as charts, graphs, or tables, to present your results clearly and effectively. Data interpretation can help you identify patterns, trends, relationships, or differences in your data, and to evaluate the significance and impact of your decisions.

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5 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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How can you use statistics to evaluate your organization's decisions?

1

2

3

4

5

1 Define your objectives

2 Select your metrics

3 Collect your data

4 Interpret your results

5 Here’s what else to consider

Decision-Making

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How can you use statistics to evaluate your organization's decisions?

1

2

3

4

5

1 Define your objectives

2 Select your metrics

3 Collect your data

4 Interpret your results

5 Here’s what else to consider

Decision-Making

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