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Certified Forecasting Professional

Course Overview BUSINESS FORECASTING is an estimate or prediction of future developments in business such as sales, expenditures, and profits. Given the wide swings in economic activity and the drastic effects these fluctuations can have on profit margins, it is not surprising that business forecasting has emerged as one of the most important aspects of corporate planning. Forecasting has become an invaluable tool for businesspeople to anticipate economic trends and prepare themselves either to benefit from or to counteract them. If, for instance, businesspeople envision an economic downturn, they can cut back on their inventories, production quotas, and hirings. If, on the contrary, an economic boom seems probable, those same businesspeople can take necessary measures to attain the maximum benefit from it. Good business forecasts can help business owners and managers adapt to a changing economy.
Training Duration 30 Hours Training Session: 1 Week Session Days : 5 Working Days
Training Schedules Weekdays (Sunday to Thursday) Regular Sessions : 6 Hrs Per day (9am to 2pm or 3.00pm to 9.00 pm) Food & refreshments provided WeekEnds (Friday & Saturday) Fast Track Sessions: 8 Hours per day (9am to 5pm) Food & refreshments provided
Certifications: 1) Certified Financial Risk Management Professional from Laurels Training Institute, Attested by Knowledge & Human Development Authority (KHDA) government of Dubai, UAE РWith Online Worldwide recognition facility 2) Certificate from American Institute of Professional Studies (AIPS) in Financial Risk Management  from USA (After 15 Days of course Completion which will couriered to the attendees office address) РWith Online Worldwide recognition facility
Tests Yes
Learning Aids Yes
Course Material Hard & Soft Copies of Study Material
Language of Instruction English
Instructor Helpline Yes 1. Email 2. Social Media (For Emergency requirements)
Registration Requirements 1. Passport Copy 2. Curriculum Vitae 3. Passport size photographs 4. Course Fee
Mode of Payment: Cash / Cheque / Credit Card / Bank Transfer.
Eligibility Criteria (Who should attend this training) Professionals in planning functions who want to enhance their skill set Students looking to build a career in Business Forecasting Individuals looking to brush up on the basics of the Integrated Planning Function
Course Benefits Course will help management to implement strategic objectives, strategies, processes, planning and controlling. One of the primary focuses of operations management is to effectively manage the resources of an organization so that the organization can maximize the potential of the products or servicses produced or offered by the company. Depending on the organization, operations management can include managing human resources, materials, information, production, inventory, transportation, logistics, purchasing and procurement.
Course Contents / Outline Introduction Need for planning and forecasting Supply Chain Flow and Product Hierarchy The 4 Ws of the Forecasting Process Introduction to Forecasting Techniques Introduction to Business Planning and Forecasting Recap Data Cleansing Introduction to Data Cleansing Detecting Outliers Statistical Outliers Business Event Outliers Correcting Outliers Outlier Detection and Correction Using Forecasting Software Data Cleansing Recap Simple Forecasting Models Simple Methods and Their Utility Introduction to Simple Moving Average The Same As Last Year Simple Forecasting Models Recap Exponential Smoothing Introduction to Exponential Smoothing Exponential Smoothing Family Understanding Additive and Multiplicative Seasonality Smoothing Constants Importance of data length Exponential Smoothing – Pros and Cons Choosing the Right Exponential Smoothing Model Exponential Smoothing – Examples and Computations Exponential Smoothing Modelling Recap Introduction to ARIMA Components of ARIMA Reading the ARIMA model Intermittent & Discrete Data Models Intermittent Demand Series Reading Croston’s Intermittent Demand Pros and Cons of Croston’s Intermittent Data Model Discrete Data Series Intermittent and Discrete Data Models Recap Error Measurement Introduction to Error and Improvement Measurement Measure of Model Fitment R – Squared Behavioral Measure Bias Popular Quantitative Measures Process Measure Forecast Value Add Analyzing the Error Error Measurement Recap New Product Forecasting Using Machine Learning Introduction Need For New Product New Product Classification Types of New Product Forecasting Forecasting by Analogy Similar Product Selection by Machine Learning Best Product Pick Forecasting for new to the world product Planning Function & Process Introduction to Planning Function Key objectives and best practices Key planner skills and success commandments Functional roles and responsibilities Consensus process and forecast cycle Top Down approach Using POS and Syndicated Data

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