Analytics for Leaders and Managers (ALaM)

Program Objectives

• Develop an Understanding of Data Analytics: Equip leaders with the necessary knowledge to understand and interpret data analytics.
• Enhance Decision-Making Capabilities: Improve the capability of leaders to make data-driven decisions.
• Foster Data Communication Skills: Enable participants to effectively communicate analytical findings.
• Encourage the Application of Analytics in Business Problems: Teach leaders how to apply analytics to solve real-world business challenges.
• Promote the Use of Predictive Analytics and Machine Learning: Provide knowledge on advanced analytical techniques like predictive analytics and machine learning to solve business problems.

Program Outline

1. Getting Started
2. Introduction to the importance of quantitative thinking.
3. Understanding your role as a consumer of analytics.
4. Gather the Right Information
5. Do you need All that Data?: Assessing the necessity and relevance of data in decision-making.
6. Ask your Scientists for Data and Analytics: How to work effectively with data scientists and analysts to get the information you need.
7. How to Design a Business Experiment?: Steps for designing experiments to test hypotheses and gather data.
8. Know the Difference between your Data and Metrics: Understanding what metrics are important and how they differ from mere data collection.
9. Fundamentals of A/B Testing: Introduction to A/B testing methodologies for comparing the effectiveness of different strategies.
10. Can your Data be Trusted?: Ensuring the reliability and credibility of your data sources.
11. Analyze the Data
12. Predictive Analytics Primer: Introduction to predictive analytics, including forecasting and customer behavior prediction.
13. Understanding Regression Analysis: Exploring how regression analysis helps in decision-making and when to act on correlations.
14. Can Machine Learning Solve your Business Problem? Evaluation of when and how machine learning can be applied to solve business issues.
15. A Refresher on Statistical Significance: Understanding the importance of statistical significance in analytics.
16. Linear Thinking in a Non-Linear World: Challenges of linear thinking in complex problem solving.
17. Pitfalls of Data-Driven Decisions: How to avoid common mistakes in data-driven decision making.
18. Communicate Your Findings
19. Emphasizing the importance of communication in making data useful and actionable.
20. Techniques for effective data presentation and visualization.

Training Completion Certificate

Participants will receive a certificate upon successful completion of the program, which involves passing assessments and actively participating in all scheduled activities.