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Quest Training

Demand Forecasting & Planning Techniques Training Course

Shows how to turn historical data and market signals into reliable demand forecasts using quantitative and qualitative techniques and accuracy measures.

SFD · Supply Chain Planning, Forecasting & Demand ManagementAll Levels#2211ClassroomEnglish , Arabic
Duration
5 Days
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Free substitution at any time · 30+ days' notice: full refund minus 10%. Cancellation policy

Sectors:Procurement, Contracts & Supply ChainCategories:Supply Chain Planning, Forecasting & Demand Management

Course Overview

This advanced course provides a practical framework for improving demand forecasting accuracy and strengthening demand planning decisions across the supply chain. It focuses on converting historical data, market signals, customer requirements, and business intelligence into reliable demand forecasts that support inventory, procurement, production, and distribution decisions. Participants will examine quantitative and qualitative forecasting techniques, demand patterns, seasonality, trends, variability, forecast bias, and forecast accuracy. The course emphasizes selecting appropriate forecasting methods based on data characteristics and business requirements rather than relying on a single forecasting approach. Through practical data analysis, forecasting exercises, scenario planning, and performance diagnostics, participants will learn how to build, evaluate, adjust, and communicate demand forecasts. Particular attention is given to identifying forecast errors and understanding their operational and financial impact on inventory, capacity, service levels, and working capital. The program also addresses collaborative demand planning, exception-based management, forecast governance, and continuous improvement, enabling organizations to establish a disciplined forecasting process that supports faster and more informed supply chain decisions.

Learning Objectives

  • Analyze demand patterns, trends, seasonality, variability, and market signals.
  • Evaluate historical demand data for forecasting purposes.
  • Apply appropriate quantitative and qualitative forecasting techniques.
  • Assess forecast accuracy using relevant performance measures.
  • Identify and address forecast bias and systematic forecasting errors.
  • Evaluate the impact of forecast uncertainty on inventory, capacity, and service levels.
  • Apply statistical and scenario-based approaches to improve forecast reliability.
  • Integrate business intelligence and market information into demand planning.
  • Develop exception-based approaches for managing significant demand changes.
  • Strengthen collaboration between sales, marketing, operations, finance, and supply chain teams.
  • Establish demand forecasting KPIs and performance review mechanisms.
  • Develop a practical demand forecasting and planning improvement framework.

Who Should Attend

This course is designed for demand planners, supply chain planners, inventory planners, procurement professionals, logistics specialists, production planners, and operations professionals involved in forecasting and planning decisions. It is also suitable for supply chain managers, demand planning managers, sales and operations planning professionals, business analysts, commercial planning specialists, and professionals responsible for translating market and customer information into operational plans. The program is particularly relevant to managers and decision-makers seeking to improve forecast reliability, inventory efficiency, production planning, service levels, procurement decisions, and overall supply chain responsiveness.

Learning Outcomes

  • By the end of the course, participants will be able to:
  • Analyze historical demand data and identify meaningful demand patterns.
  • Distinguish between trend, seasonality, variability, and exceptional demand events.
  • Select appropriate forecasting techniques based on data and business conditions.
  • Develop demand forecasts using practical quantitative and qualitative methods.
  • Measure forecast accuracy and identify the sources of forecast error.
  • Detect and correct systematic forecast bias.
  • Evaluate the operational and financial consequences of inaccurate forecasts.
  • Incorporate market intelligence, customer information, and business assumptions into forecasts.
  • Develop scenarios for uncertain or rapidly changing demand conditions.
  • Apply exception-based planning to focus attention on material demand deviations.
  • Establish forecasting KPIs and structured forecast review processes.
  • Prepare an actionable framework for improving demand forecasting and planning performance.

Course Outline

Course Outline:

Day 1

Demand Forecasting Fundamentals & Demand Analysis

  • Role of demand forecasting in supply chain planning
  • Forecasting horizons and planning levels
  • Historical demand data and data quality
  • Demand patterns, trends, seasonality, and variability
  • Identifying demand anomalies and exceptional events
  • Demand segmentation and planning priorities
  • Key factors influencing demand behavior
  • Linking forecasts with inventory, procurement, production, and distribution
  • Practical workshop: Analyze historical demand data and identify key forecasting patterns
Day 2

Quantitative Forecasting Techniques

  • Principles of quantitative demand forecasting
  • Moving averages and weighted moving averages
  • Exponential smoothing approaches
  • Trend-based forecasting
  • Seasonal forecasting techniques
  • Forecast selection based on data characteristics
  • Forecast error measurement and interpretation
  • Comparing alternative forecasting methods
  • Practical workshop: Build and compare multiple demand forecasts using historical data
Day 3

Forecast Accuracy, Bias & Demand Uncertainty

  • Forecast accuracy concepts and performance measures
  • Mean absolute error and related forecasting measures
  • Forecast bias and systematic error
  • Identifying root causes of forecasting inaccuracies
  • Managing demand volatility and uncertainty
  • Impact of forecast error on inventory and service levels
  • Scenario analysis for uncertain demand
  • Adjusting forecasts based on business intelligence
  • Practical workshop: Diagnose forecast errors, identify bias, and develop corrective actions
Day 4

Collaborative Demand Planning & Forecast Optimization

  • Integrating sales, marketing, customer, and market information
  • Collaborative demand planning across functions
  • Combining statistical forecasts with business judgment
  • Exception-based demand management
  • Managing promotions, new products, and demand changes
  • Demand consensus and forecast review processes
  • Forecast communication and stakeholder alignment
  • Demand planning dashboards and KPIs
  • Practical workshop: Develop a collaborative demand plan and resolve forecast exceptions
Day 5

Demand Planning Strategy & Continuous Improvement

  • Designing an effective demand forecasting process
  • Forecast governance, ownership, and accountability
  • Establishing demand planning KPIs and targets
  • Integrating demand forecasting with supply planning
  • Improving forecast reliability through continuous review
  • Managing forecasting risks and changing demand conditions
  • Prioritizing forecasting improvement initiatives
  • Sustaining improvements through structured performance management
  • Final workshop: Develop a Demand Forecasting & Planning Improvement Roadmap covering forecasting methods, KPIs, governance, improvement initiatives, responsibilities, and implementation actions

Upcoming Dates

Selected date

London · 15 – 19 Feb 2027 · Classroom

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SalalahScheduled
2 – 6 Nov 2026€5,300—
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TunisiaScheduled
9 – 13 Nov 2026€3,800—
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ViennaScheduled
16 – 20 Nov 2026€5,700—
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AmmanScheduled
22 – 26 Nov 2026€3,100€2,790until 2 Nov
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AmsterdamScheduled
30 Nov – 4 Dec 2026€5,400€4,860until 9 Nov
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BangkokScheduled
7 – 11 Dec 2026€6,100€5,490until 16 Nov
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BakuScheduled
7 – 11 Dec 2026€4,800€4,320until 16 Nov
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BarcelonaScheduled
14 – 18 Dec 2026€5,400€4,860until 23 Nov
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BerlinScheduled
21 – 25 Dec 2026€5,800€5,220until 30 Nov
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CairoScheduled
28 Dec 2026 – 1 Jan 2027€3,300€2,970until 7 Dec
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CasablancaScheduled
4 – 8 Jan 2027€4,300€3,870until 14 Dec
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DammamScheduled
11 – 15 Jan 2027€4,200€3,780until 21 Dec
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DohaScheduled
18 – 22 Jan 2027€4,400€3,960until 28 Dec
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DubaiScheduled
24 – 28 Jan 2027€4,400€3,960until 4 Jan
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IstanbulScheduled
25 – 29 Jan 2027€4,700€4,230until 4 Jan
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Kuala LumpurScheduled
1 – 5 Feb 2027€4,400€3,960until 11 Jan
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LisbonScheduled
8 – 12 Feb 2027€5,400€4,860until 18 Jan
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LondonScheduled
15 – 19 Feb 2027€5,600€5,040until 25 Jan
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MadinahScheduled
22 – 26 Feb 2027€4,200€3,780until 1 Feb
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MadridScheduled
1 – 5 Mar 2027€5,400€4,860until 8 Feb
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MakkahScheduled
8 – 12 Mar 2027€4,200€3,780until 15 Feb
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ManamaScheduled
8 – 12 Mar 2027€4,700€4,230until 15 Feb
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MarrakeshScheduled
15 – 19 Mar 2027€4,300€3,870until 22 Feb
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MilanScheduled
22 – 26 Mar 2027€6,000€5,400until 1 Mar
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MunichScheduled
29 Mar – 2 Apr 2027€5,400€4,860until 8 Mar
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MuscatScheduled
5 – 9 Apr 2027€5,300€4,770until 15 Mar
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OnlineScheduled
11 – 15 Apr 2027€1,700€1,530until 22 Mar
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ParisScheduled
19 – 23 Apr 2027€5,700€5,130until 29 Mar
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RiyadhScheduled
26 – 30 Apr 2027€4,200€3,780until 5 Apr
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RomeScheduled
26 – 30 Apr 2027€5,800€5,220until 5 Apr
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Available in: Istanbul · Dubai · London · Riyadh · Doha · Amsterdam

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