Data-Driven Decision-Making Model

16 6 by Kavithalaya

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Make decision-making more interactive and insightful! The Data-Driven Decision-Making Model combines multiple-choice, word cloud, open-ended, ranking, spider scale, and traffic light activities to evaluate information, gather perspectives, prioritize options, and improve strategic planning. Target Audience: Managers, analysts, entrepreneurs, consultants, and business teams.

Category Analytics

1 - Content

2 - Content

3 - Content

4 - Content

5 - Word Cloud

What comes to mind when you think of data-driven decision-making?

6 - Multiple Choice

Which of the following is a key principle of data-driven decision-making?

1. Data Collection
2. Intuition-Based Decisions
3. Random Guessing
4. Ignoring Data
5. Data Analysis

7 - Ranking

Rank the following challenges in data-driven decision-making from most to least significant:

1. Data Quality Issues
2. Resistance to Change
3. Lack of Training
4. Insufficient Technology

8 - Open Ended

What is your main takeaway from today's session?

9 - Word Cloud

Name a challenge you face when making decisions with data

10 - Multiple Choice

How effective is your current data dashboard setup?

1. Poor
2. Fair
3. Excellent

11 - Open Ended

What’s your biggest question when interpreting a data set?

12 - Scales

Rate your team’s current data capabilities across the following traits:

1. Data literacy
2. Analytical thinking
3. Use of BI tools
4. Data storytelling
5. Collaboration on insights

13 - Scales

How confident are you in these aspects of your decision-making process?

1. Trust in data sources
2. Timeliness of data
3. Clarity of visualizations
4. Actionability of insights
5. Stakeholder buy-in

14 - This or That

After making a data-informed decision, what should you do?

1. Measure the outcome
2. Assume the decision worked

15 - QA

What would help your team make better data-driven decisions?

16 - Content

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