Analysis for Management Decisions

Course Introduction

Data is a powerful tool that is available to organizations at a staggering scale. When harnessed correctly, it has the potential to drive decision-making, impact strategy formulation, and improve organizational performance.

According to report by business intelligence company Micro Strategy, 56 percent of respondents said data analytics led to “faster, more effective decision-making” at their companies. Other benefits cited include:

This OXFORD MANAGEMENT Analysis for Management Decisions training course will highlight:

• Guide to Data & Analytics
• Descriptive Analytics
• Diagnostic Analytics
• Predictive Analytics
• Prescriptive Analytics

Objectives

At the end of this Analysis for Management Decisions training course, you will learn to:

• Identify difference between Data Science vs. Data Analytics
• Apply Data Analytics In Business
• Apply Descriptive Analytics
• Apply Diagnostic Analytics
• Apply Predictive Analytics
• Apply Prescriptive Analytics

Training Methodology

This training course is practical with hands-on training on MS Excel & Power-BI Desktop. 20% of the training course is theory built. 80% uses MS Excel & Power-BI Desktop. Laptops will be made available duration of the training. In addition, the book 'Microsoft Excel & Power-BI & Data Analytics “Will be distributed at the training course, in electronic copies.

Organisational Impact

The Organisation will have the following benefits;

• Improved efficiency and productivity
• Better financial performance
• Identification and creation of new product and service revenue
• Improved customer acquisition and retention
• Improved customer experiences
• Competitive advantage

Personal Impact

The participants will have the following benefits from this Analysis for Management Decisions training course;

• Learn how can you harness the power of data and experience these benefits
• Learn how to analyze data effectively can enable you to draw conclusions, predictions, and actionable insights to drive impactful decision-making
• Improve the skills for professionals in a variety of job roles
• Perform numerical or general data analysis
• Shaping and combining data for the purpose of analysis

Who Should Attend?

This Analysis for Management Decisions training course is suitable to a wide range of professionals but will greatly benefit:

• Marketers, who utilize customer data, industry trends, and performance data from past campaigns to plan marketing strategies
• Product managers, who analyze market, industry, and user data to improve their companies’ products
• Finance professionals, who use historical performance data and industry trends to forecast their companies’ financial trajectories
• Human resources and diversity, equity, and inclusion professionals, who gain insights into employees’ opinions, motivations, and behaviors and pair it with industry trend data to make meaningful changes within their organizations

Course Outline

DAY 1

A Beginner’s Guide to Data & Analytics

• Data science vs. Data analytics
• Data science in business
• Data analytics in business
• Data literacy
• Data ecosystem & lifecycle
• Data privacy & ethics
• Data integrity
• Building your data & analytical skill set
• 7 data & analytics skills you need
• How to improve your skills
• The data-driven decision-making framework

DAY 2

Descriptive Analytics

• Traffic and engagement reports
• Financial statement analysis
• Demand trends
• Aggregated survey results
• Progress to goals
• Data visualization techniques

DAY 3

Diagnostic Analytics

• Hypothesis testing
• Correlation vs. Causation
• Diagnostic regression analysis
• Examining market demand
• Explaining customer behavior
• Identifying technology issues
• Improving company culture

DAY 4

• Regression analysis
• Single linear regression
• Multiple regression
• What if analysis
• Logical functions
• Data tables
• Scenarios

DAY 5

Prescriptive Analytics

• Venture capital: Investment decisions
• Sales: Lead scoring
• Content curation: Algorithmic recommendations
• Banking: Fraud detection
• Product management: Development and improvement
• Marketing: Email automation