Analytical Tools and Techniques
Classroom based course with study materials, lecturer support and CPD Hours included
London Training For Excellence
Summary
- Tutor is available to students
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Overview
Description
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
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