Techniques and Analytical Tools

Some of the tools discussed in the course include SWOT (Strengths Weaknesses Opportunities Threats), Porter’s Five Forces, Kano Model for Customer Requirements, Segmentation Analysis, Buyer Utility Maps, Data Profiling, and Correlation Analysis. This five-day course describes several analytical tools that you would use for strategic business analysis, customer analysis, and data analysis.

Objective

The objective of this course is to give the learner a wide range of tools that can be used in different analytical situations. This would include industry analysis, strategic analysis, external business environment analysis, customer requirements analysis, and data analysis. The course describes in detail specific analytical models that anyone can use for a better understanding of the organization and its external operating environment.

Course Outline

Strategic Tools

After completing this session, you will be able to apply the following models:

• STEEP and PEST for broad environmental scans to facilitate external thinking
• Porter’s Five Forces to better understand an industry around those forces that define every industry
• SWOT for assessing the internal strengths and weaknesses of a company and the external threats and opportunities
• McKinsey 7 S Model for assessing an organization in terms of 7 parameters
• Ansoff Matrix for evaluating your strategy against the marketplace
• SPACE Matrix for evaluating different strategies around four parameters
• QSPM Model for evaluating different strategies based on 10 to 20 factors

Customer Tools

After completing this session, you will be able to:

• Apply the Kano Model to better understand customer requirements
• Apply the use segmentation to improve your strategic focus
• Assign values to customers so you can better distinguish profitable customers from unprofitable customers
• Apply a ranking table based on customer expectations
• Apply the Quality Function Deployment model for translating customer requirements into your design processes
• Generate new ways of satisfying customers by using the Buyer Utility Map
• Conduct customer surveys

Data Analysis with Statistics

After completing this session, you will be able to:

• Recognize different approaches for analysing large volumes of data
• Identify important quality control practices related to databases
• Devise ways for reducing errors and missing data in surveys
• Differentiate Quantitative vs. Qualitative and Discrete vs. Continuous
• Design ways of expressing a distribution of data visually
• Identify three important measures for describing a distribution
• Identify four different levels of measurement that are commonly applied in statistics
• Identify three ways of expressing correlations in data
• Apply regression analysis and express linear relationships