Data Analytics for
Managerial Decision Making

Effective and decisive decision making is a key ingredient in any successful manager. A significant contributing factor is using evidence-based information for decision making. This can be achieved through professionals equipping themselves with data analytic- and quantitative reasoning- skills.  This Anderson training course focuses strongly on imparting a management perspective on the value of data analytics in decision making. In addition, it will provide insight into how data analytics can be used to support strategic initiatives, to guide policy formulation and to support operational decision making. The training course will emphasise applications of data analytics in management practice and focus on the valid interpretation of data analytics findings.

By attending this Anderson training course, delegates will be able to:

• Understand the power of data analytics as a decision support tool in management
• Critically assess the validity of statistically-generated business information
• Understand the purpose of the different data analytic tools and which one/s to use in given management scenarios
• Know how to meaningfully and validly interpret statistical evidence in a management context
• Be in a position to communicate intelligently with data analytic professionals

This Anderson training course is suitable for a wide range of middle and senior managers who have the responsibility of divisional and organisational success through their decision making. It is also suitable for consultants and professionals who support them. In particular:

• HR managers
• Marketing managers
• Operations and logistics managers
• Financial managers
• Policy support personnel
• Engineers / Technical Specialists

Amongst a wide range of valuable topics, the following will be prioritised:

• Providing data analytics power to the end-user manager using Excel
• Identifying the role of data analytics in the decision making process
• Reviewing a range of management applications of data analytics
• Focusing on the management interpretation of statistical evidence
• Integrating statistical thinking in the management decision making process
• The value of data and data structures as a key prerequisite of data analytics
• Value extraction methods using summary tables and graphs
• Making advanced inferential tools understandable to the layman manager
• Using modeling tools to understand the dynamics of business relationships
• Focusing on the critical evaluation of statistical evidence to guarantee valid information