How To Select The Right Forecasting Technique?

jaro education
11, August 2024
5:30 pm

Introduction

In the fast-changing world of manufacturing, one has to be a step ahead. Among various steps toward this, accurate forecasting plays a vital role. A good technique in forecasting allows the manager to predict the trends in the market, proper resource allocation, and proper decision-making, among many other benefits. Now, in such a wide sea of methods and techniques, how can you tell which one is the right way? This blog delves into details of various types of forecasts, and the alternatives in methods, comprehensively helping manufacturing managers in their choice.

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A Review of forecasting techniques

Forecasting is an estimate of some future events based on knowledge of past events and analysis. The forecasting in the subject of manufacturing management is quite strategic since demand, production planning, and inventory are the periphery of success.

Qualitative Forecasting Techniques

The qualitative forecasting technique involves judgment and opinion as opposed to numerical data. These methods are particularly used when historical data is of little value, or the activity is new, for instance, the launching of a new product.

Delphi Method

The Delphi approach in forecasting methods is one in which a panel of experts provides their forecasts independently of what the others have to say. These forecasts are then aggregated and, finally, the panel settles the forecast through repeated rounds of discussions. This approach is less influenced by any particular dominant person, hence providing a wholesome forecast.

Market Research

Market research involves obtaining relevant information from the potential customers or population by using tools like surveys, interviews, focus groups, etc. More so, this is extremely useful in informing the tastes and preferences of customers for new products being launched.

Quantitative Forecasting Methods

In quantitative forecasting techniques, one can predict future events through the use of statistics or numerical data. These techniques have, however, been considered more accurate than many of those in the first group.

Time Series Analysis

Time series analysis is the examination of historical data points to identify trends and patterns. Moving averages, exponential smoothing, and the application of ARIMA models are very common forecasting methods for time series analysis.

Causal Models

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