Data Analytics for Managerial Decision Making

Through interactive discussion and hands-on exercises, this program will cover:

• Descriptive analytics: understanding what data to collect and what it is telling you, data visualization techniques to envision important factors and relationships, quantifying your data, data variability, dealing with limited data
• Predictive analytics: foreseeing what is likely to occur based on what has happened in the past, mining your data to predict customer demand and preferences, strategies and tactics for deploying predictive analytics initiatives
• Prescriptive analytics: understanding your data to make better decisions, “what if” scenario analysis, minimizing pitfalls such as process variability and the “flaw of averages”, outcome optimization
• Best-in-practice analytics methods: analytics best practices, implementation challenges, getting started with analytics methods that can be applied to your organization
• You will have an opportunity to become more familiar with these concepts via in-class practices with Excel, which will take about half of the class time. These Excel tools include: conditional formatting, histogram, Pivot tables, simple and multiple regression, data tables, auditing tools, solver optimizer and Monte Carlo simulation.

Benefits

Through this program, you will:

• Learn what analytics is, how it is applied across diverse industries, and how it can be applied to your own organization
• Discover how analytics can generate new business insights and opportunities
• Learn how analytics can mitigate risk, uncertainty and process variability
• Identify challenges in developing analytics strategies
• Experience how spreadsheet models can help solve challenging decisions

Who should attend?

This introductory level program is ideal for middle and upper managers, analysts, project leaders and others in a non-technical field who would like to gain an overview of the concepts and capabilities of business analytics.