Analytical Tools and Techniques

Course Code: DIGTR 143

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Course Sector:

Digital Transformation and Innovation

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Introduction

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Analytical tools and techniques are vital for strategic business analysis, customer analysis, and data analysis, as they empower organizations to make data-driven decisions, gain a competitive edge, reduce costs, enhance the customer experience, manage risks, allocate resources efficiently, drive innovation, measure performance, target marketing efforts, and plan for scalability and growth. In today's data-driven business environment, these tools are essential for staying competitive, adapting to changing markets, and delivering superior products and services.

This course is designed to provide participants with a robust foundation in analytical tools and techniques that can be applied in diverse business contexts. It covers industry analysis, strategic analysis, external business environment analysis, customer requirements analysis, and data analysis. This course will aid in strengthening the capacity of participants to use data analysis for informed decision-making and strategy development.

Gain a comprehensive understanding of the broad spectrum of analytical tools suitable for various analytical scenarios, including industry analysis, strategic analysis, external business environment analysis, customer requirements analysis, and data analysis. Understand when and how to apply these tools effectively in different contexts.
Identify and evaluate industry trends, competitive forces, and strategic opportunities for their organizations through industry and strategic analysis models.
Assess and analyse the external business environment comprehensively by examining political, economic, social, technological, environmental, and legal factors (PESTEL analysis) and understanding their impact on organizational strategies.
Analyse customer requirements effectively through segment and target customer groups, understand their needs, preferences, and behavior, and align products and services accordingly to enhance customer satisfaction and loyalty.
Explore concepts and tools for effective data analysis such as data sources, data cleaning, exploratory data analysis (EDA), statistical techniques, and the ability to extract actionable insights from data.

Business and technology leaders

- Business Unit Managers

- Business Development Consultants

- General Managers / Regional Managers

- Senior and mid-level leaders

- individual leaders of all levels in the organization

- Art Director

- Marketing Consultants

- Marketing Development Manager

STRATEGIC TOOLS

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

STRATEGIC TOOLS

SPACE Matrix for evaluating different strategies around four parameters
QSPM Model for evaluating different strategies based on 10 to 20 factors

ANALYTICAL TOOLS AND TECHNIQUES FOR CUSTOMER SERVICE

The Kano Model to better understand customer requirements
The use of segmentation to improve strategic focus
Assigning values to customers to distinguish profitable customers from unprofitable customers

ANALYTICAL TOOLS AND TECHNIQUES FOR CUSTOMER SERVICE

How to use a ranking table based on customer expectations
The Quality Function Deployment model for translating customer requirements into design processes
Generating new ways of satisfying customers by using the Buyer Utility Map
Conducting customer surveys

DATA ANALYSIS WITH STATISTICS

Different approaches for analysing large volumes of data
Identifying important quality control practices related to databases
Methods and techniques for reducing errors and missing data in surveys
Quantitative vs. Qualitative and Discrete vs. Continuous
Methods and techniques of expressing a distribution of data visually

DATA ANALYSIS WITH STATISTICS

Three important measures for describing a distribution
Four different levels of measurement that are commonly applied in statistics
Three methods and techniques of expressing correlations in data
Regression analysis and express linear relationships

Boost certificate of completion

BOOST's Professional Attendance Certificate “BPAC” is always given to the delegates after completing the training course, and depends on their attendance of the program at a rate of no less than 80%, besides their active participation and engagement during the program sessions.

ENDORSED EDUCATION PROVIDER

Flexible deadlines

Customized dates accordance to your schedule

Shareable Certificate

Earn certificate upon completion

COURSE METHODOLOGY

Our Training programs are implemented by combining the participants' academic knowledge and practical practice (30% theoretical / 70% practical activities).

At The end of the training program, Participants are involved in practical workshop to show their skills in applying what they were trained for. A detailed report is submitted to each participant and the training department in the organization on the results of the participant's performance and the return on training. Our programs focus on exercises, case studies, and individual and group presentations.

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TRAINING COURSE: Analytical Tools and Techniques