Data Analytics for Managerial Decision-Making Training

Course Category : Administrative Development

This course enables participants to turn data into insights, insights into decisions, and decisions into organisational value by leveraging data analytics as a decision-support tool for management.
Duration: 5 Training Days
Level: Intermediate–Advanced

Introduction

This course addresses the growing need for managers and business professionals to base their choices on evidence rather than intuition. It highlights how data analytics can support strategic initiatives, inform policy, and guide day-to-day operational decision-making.
Participants will explore descriptive, inferential, and predictive analytics; learn to interpret statistical outputs critically; understand sampling and hypothesis testing; and link analytical findings to real managerial decisions. By the end, they will have greater confidence in using data as a reliable decision-support system..

Targeted Specializations

Professionals in management support roles.
Business and data analysts in corporate and public sectors.
Managers and supervisors who work with periodic reports and metrics.
Planning, quality, performance management, and KPI officers.
Anyone seeking to derive more decision-making value from data analytics.

Targeted Skills

Managerial data analysis skills.
Statistical thinking linked to KPIs.
Interpreting statistical evidence for decisions.
Applying descriptive, inferential, and predictive analytics.
Producing tables, dashboards, and visual summaries.
Integrating quantitative reasoning into managerial decision-making.

Expected Outcomes

Recognise the value of data analytics as a managerial decision-support tool.
Distinguish between different data types and prepare data for analysis.
Apply descriptive analytics to profile business/managerial data clearly.
Interpret statistical evidence (averages, variability, relationships) for decisions.
Understand the foundations of statistical inference and sampling.
Use hypothesis testing to compare groups and support managerial options.
Explore predictive modelling and data mining for management applications.
Integrate statistical thinking into regular management reports and KPIs.

Training Topics Index

The quantitative landscape in management.
Thinking statistically about management applications (identifying KPIs).
Integrative elements of data analytics.
Data as the raw material – types, quality, preparation.
Exploratory data analysis using Excel (pivot tables).
Using summary tables and visual displays to profile data.

Numerical descriptors for profiling sample data.
Measures of central and non-central location.
Measuring variability and dispersion.
Examining distributions (skewness, bimodal patterns).
Analysing relationships between numerical measures.
Breakdown analysis of key managerial indicators.

Foundations of statistical inference.
Quantifying uncertainty – the normal distribution.
The importance of sampling and sampling methods.
Understanding the sampling distribution.
Confidence interval estimation and interpretation.
Applied example.

Rationale and process of hypothesis testing.
Type I and Type II errors.
Single-population tests (single mean tests).
Two independent population mean tests.
Matched-pairs test situations.
Comparing means across multiple populations (managerial ANOVA).

Exploiting statistical relationships for prediction.
Building regression-based models.
Model evaluation and interpretation.
Overview of data mining – descriptive vs. predictive.
Managerial applications of data mining.
Reporting analytical insights for management action.

Course Features

Modern and practical content
Real-world examples and leadership exercises
Pre- and post-course assessments to measure impact
Accredited certificate with QR code verification

Data Analytics for Managerial Decision-Making Training