Forecasting basics, client expectations and questions

Impact_Analytics

Module 1: Introduction to IA Forecasting

1. 1. Overview of IA Forecast engine
    - - Introduction to IA forecasting
      - How is IA forecasting different from others
      - Workflow of IA forecasting
  2. Key components of IA forecasting process
    - - Store Clustering
      - Lost Sales Imputation
      - Model building and evaluation
      - Model Deployment and Orchestration
  3. Additional modules in IA forecasting
    - - Omnichannel forecasting
      - New store handling
      - Supersession
      - Size curve calculations

Module 2: Forecasting - Roles & Responsibilities

1. 1. What are the roles and responsibilities of different teams in a forecasting engagement
    - - Key steps and forecasting RACI
      - Workstream identification & process management
      - Business understanding and EDA
      - Input Data Quality Control
  2. How can the client team review the forecasts
    - - How to check if forecasts are off?
      - Key reasons as to why forecasts can be off?
      - How do we fix the forecasts in each case?
      - How to check if business requirements are met after modeling?

Module 3: Communicating Forecast Results

1. 1. Presenting Forecasts Effectively
    - - Key drivers and insights
      - Decision accuracy and steering away from forecast accuracy
      - Accuracy expectation setting + What to do in cases of low confidence
  2. Handling Common Client Questions
    - - Addressing Uncertainty and Risks
      - Explaining Methodology and Assumptions
      - Providing Actionable Recommendations

Module 4: Setting up a successful forecast engagement

1. 1. Best practices during go-live, hypercare & support and maintenance
    - - Setting up forecast alerts and expectations
      - Handover and support and maintenance expectation setting
      - Continuous monitoring and communication protocol
  2. Engagement set-up success tracker
    - - Taking the engagement set-up assessment test