Data-driven Decision Making

Table of Content

1. What is data-driven decision making (DDDM)?​

2. Why is data-driven decision making important?​

3. 5 steps for making data-driven decisions​

​4. Data-driven decision making examples

​5. Benefits of data-driven decision making

​6. Conclusion​

Introduction

Data Driven decision making is the process of collecting data based on your company’s Key Performance indicators or KPs and transforming that data into actionable heights.

Why is data-driven decision making important?​

Data-driven decision making is important because it helps you make decisions based on facts instead of biases. If you’re in a leadership position, making objective decisions is the best way to remain fair and balanced.  ​

The most informed decisions stem from data that measure your business goals and populates in real time. You can aggregate the data you need to see patterns and make predictions with reporting software.​

Decisions you can make with support from data

  • How to drive profits and sales​
  • How to establish good management behavior​​
  • How to optimize operations​
  • How to improve team performance​

5 steps for making data-driven decisions​ ​ ​

  1. Know your vision
  2. ​Find data sources
  3. Organize your data
  4. Perform data analysis
  5. Draw conclusions

Data-driven decision making examples​ ​ ​

  • E-commerce ​
  • Online marketplaces like Amazon track customer journeys and use metrics like click-through rate and bounce rate to identify what items you’re engaging with most. Using this data, retailers are able to show you what you might want without you having to search for it. ​
  • Finance​
  • Financial institutions also use customer data to determine their target market. By grouping consumers based on socioeconomic status, spending habits, and more, financial companies can infer what consumers have the greatest lifetime value and target them. ​
  • Transportation​
  • Data science additionally plays a huge role in determining safe transportation. The report pulls data from all types of motor crashes and evaluates factors like weather and road conditions to discover the source of problems. Using the hard facts, the department can work toward implementing more safety measures. ​
  •  

Benefits of data-driven decision making​ ​ ​

  1. Make Confident Decisions
  2. Guard against biases
  3. Find unresolved questions
  4. Set measurable goals
  5. Improve company processes

Conclusion

With data-driven decision making you gain greater control over the direction of your business and the quality of your decisions. This is because it is based on objective data, concrete evidence and results can be effectively measured in order to assess impact. It increases agility.​

Thank You

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shakki pk
shakki pk
8 months ago

Test

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shakki pk
shakki pk
8 months ago

good information

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