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Quest Training

Advanced Demand Planning & Forecasting Analytics Training Course

Applies statistical analysis and advanced forecasting to complex demand patterns, diagnosing forecast error and bias to make planning decisions more reliable.

SFD · Supply Chain Planning, Forecasting & Demand ManagementAll Levels#2212ClassroomEnglish , 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 analytical framework for improving demand planning, forecasting accuracy, and decision-making across complex supply chain environments. It focuses on using demand data, statistical analysis, business intelligence, and advanced forecasting techniques to improve the quality and reliability of planning decisions. Participants will work with demand patterns, seasonality, trends, variability, forecast error, bias, and demand drivers to understand why forecasts deviate from actual demand. The course emphasizes analytical diagnosis rather than simply producing forecasts, enabling planners to identify the causes of forecast inaccuracies and determine appropriate corrective actions. The program integrates advanced forecasting analytics with inventory, supply, capacity, procurement, and service-level decisions. Participants will learn how to use scenario analysis, exception management, segmentation, and performance analytics to translate demand insights into more effective supply chain plans. Through practical exercises and business cases, participants will develop advanced demand planning capabilities, establish analytical performance measures, and build a structured improvement approach that connects forecasting quality with operational and financial outcomes.

Learning Objectives

  • Analyze complex demand patterns using advanced forecasting analytics.
  • Evaluate trends, seasonality, variability, demand drivers, and exceptional demand events.
  • Apply advanced quantitative forecasting techniques to different demand profiles.
  • Diagnose forecast error, bias, and structural weaknesses in forecasting processes.
  • Compare forecasting models and select appropriate approaches based on data characteristics.
  • Apply segmentation techniques to differentiate forecasting and planning priorities.
  • Use scenario analysis to evaluate uncertain and rapidly changing demand conditions.
  • Integrate market intelligence and business assumptions into analytical forecasts.
  • Assess the impact of forecast quality on inventory, capacity, service levels, and working capital.
  • Develop advanced demand planning KPIs and analytical dashboards.
  • Apply exception-based analytics to focus planning resources on material demand deviations.
  • Develop an advanced framework for continuous improvement of demand forecasting performance.

Who Should Attend

This course is designed for demand planners, supply chain planners, forecasting specialists, inventory planners, business analysts, and professionals responsible for demand analysis and forecasting performance. It is also suitable for supply chain managers, demand planning managers, sales and operations planning professionals, commercial planning specialists, procurement and inventory managers, and analysts who use demand intelligence to support operational decisions. The program is particularly relevant to professionals managing complex demand environments, large product portfolios, high demand variability, seasonal markets, or organizations seeking to strengthen analytical and data-driven planning capabilities.

Learning Outcomes

  • By the end of the course, participants will be able to:
  • Analyze complex historical demand datasets and identify significant demand patterns.
  • Segment products or demand streams according to forecasting characteristics and business priorities.
  • Select and apply appropriate advanced forecasting methods.
  • Compare forecasting model performance using relevant accuracy measures.
  • Diagnose forecast bias, error patterns, and root causes of poor forecast performance.
  • Identify key demand drivers and assess their influence on forecast outcomes.
  • Build demand scenarios for uncertain, volatile, or rapidly changing market conditions.
  • Integrate statistical forecasts with market intelligence and business assumptions.
  • Translate demand analytics into inventory, supply, capacity, and procurement decisions.
  • Develop exception-based planning processes based on material forecast deviations.
  • Build analytical dashboards and KPIs for demand planning performance.
  • Prepare an advanced demand forecasting improvement roadmap linked to operational and financial outcomes.

Course Outline

Course Outline:

Day 1

Advanced Demand Analytics & Demand Pattern Diagnosis

  • Advanced demand planning concepts and analytical requirements
  • Historical demand data quality and preparation
  • Trend, seasonality, variability, intermittency, and demand volatility
  • Identifying demand patterns and structural changes
  • Demand drivers and causal factors
  • Product and demand segmentation
  • Detecting anomalies and exceptional demand events
  • Linking demand characteristics to forecasting strategy
  • Practical workshop: Analyze a complex demand dataset and develop demand segments and planning priorities
Day 2

Advanced Forecasting Models & Model Selection

  • Advanced quantitative forecasting principles
  • Moving averages and exponential smoothing applications
  • Trend and seasonal forecasting
  • Forecast model comparison and selection
  • Measuring forecast accuracy and forecast error
  • Forecast bias and systematic error detection
  • Model performance by product, market, and planning horizon
  • Selecting forecasting approaches based on demand characteristics
  • Practical workshop: Build, compare, and evaluate multiple forecasting models using historical demand data
Day 3

Forecast Analytics, Scenarios & Demand Uncertainty

  • Advanced forecast error analysis
  • Root cause analysis of forecast deviations
  • Managing demand volatility and uncertainty
  • Scenario-based demand forecasting
  • Sensitivity analysis and alternative demand assumptions
  • Promotional, seasonal, and exceptional demand impacts
  • Incorporating market intelligence and business judgment
  • Evaluating the operational and financial consequences of forecast uncertainty
  • Practical workshop: Diagnose forecast deviations and develop alternative demand scenarios
Day 4

Demand Planning Analytics & Supply Chain Integration

  • Translating demand analytics into supply decisions
  • Linking demand forecasts with inventory and safety stock
  • Demand-driven capacity and procurement planning
  • Exception-based demand management
  • Demand analytics for service-level decisions
  • Integrating sales, marketing, finance, operations, and supply chain inputs
  • Demand planning dashboards and advanced KPIs
  • Analytical prioritization of planning exceptions
  • Practical workshop: Convert demand insights into an integrated inventory, supply, and capacity response
Day 5

Advanced Demand Planning Strategy & Continuous Improvement

  • Designing an advanced demand planning operating framework
  • Forecast governance, accountability, and planning ownership
  • Establishing advanced forecasting KPIs and performance targets
  • Continuous model and process improvement
  • Managing forecast risk and changing demand conditions
  • Prioritizing analytical improvement opportunities
  • Linking forecast performance to financial and operational outcomes
  • Building a sustainable data-driven demand planning culture
  • Final workshop: Develop an Advanced Demand Planning & Forecasting Analytics Roadmap covering analytical methods, KPIs, forecasting priorities, improvement initiatives, governance, and implementation actions

Upcoming Dates

Selected date

Milan · 15 – 19 Mar 2027 · Classroom

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CityDatesPrice per ParticipantEarly Bird
TunisiaScheduled
2 – 6 Nov 2026€3,800—
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ViennaScheduled
9 – 13 Nov 2026€5,700—
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AmmanScheduled
15 – 19 Nov 2026€3,100—
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AmsterdamScheduled
23 – 27 Nov 2026€5,400€4,860until 2 Nov
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BakuScheduled
30 Nov – 4 Dec 2026€4,800€4,320until 9 Nov
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BangkokScheduled
7 – 11 Dec 2026€6,100€5,490until 16 Nov
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BarcelonaScheduled
7 – 11 Dec 2026€5,400€4,860until 16 Nov
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BerlinScheduled
14 – 18 Dec 2026€5,800€5,220until 23 Nov
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CairoScheduled
21 – 25 Dec 2026€3,300€2,970until 30 Nov
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CasablancaScheduled
28 Dec 2026 – 1 Jan 2027€4,300€3,870until 7 Dec
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DammamScheduled
4 – 8 Jan 2027€4,200€3,780until 14 Dec
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DohaScheduled
11 – 15 Jan 2027€4,400€3,960until 21 Dec
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DubaiScheduled
17 – 21 Jan 2027€4,400€3,960until 28 Dec
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IstanbulScheduled
25 – 29 Jan 2027€4,700€4,230until 4 Jan
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Kuala LumpurScheduled
25 – 29 Jan 2027€4,400€3,960until 4 Jan
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LisbonScheduled
1 – 5 Feb 2027€5,400€4,860until 11 Jan
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LondonScheduled
8 – 12 Feb 2027€5,600€5,040until 18 Jan
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MadinahScheduled
15 – 19 Feb 2027€4,200€3,780until 25 Jan
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MadridScheduled
22 – 26 Feb 2027€5,400€4,860until 1 Feb
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MakkahScheduled
1 – 5 Mar 2027€4,200€3,780until 8 Feb
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ManamaScheduled
8 – 12 Mar 2027€4,700€4,230until 15 Feb
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MarrakeshScheduled
8 – 12 Mar 2027€4,300€3,870until 15 Feb
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MilanScheduled
15 – 19 Mar 2027€6,000€5,400until 22 Feb
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MunichScheduled
22 – 26 Mar 2027€5,400€4,860until 1 Mar
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MuscatScheduled
29 Mar – 2 Apr 2027€5,300€4,770until 8 Mar
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OnlineScheduled
4 – 8 Apr 2027€1,700€1,530until 15 Mar
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ParisScheduled
12 – 16 Apr 2027€5,700€5,130until 22 Mar
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RiyadhScheduled
19 – 23 Apr 2027€4,200€3,780until 29 Mar
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SalalahScheduled
26 – 30 Apr 2027€5,300€4,770until 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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