This document discusses forecasting, which involves predicting future events based on past and present data. Forecasting provides managers with information to make important decisions, though it cannot guarantee future outcomes. It uses statistical techniques to analyze data and estimate probabilities. The document also discusses the merits of forecasting, such as providing reliable information for planning, and the limitations, such as potential inaccuracy of long-term forecasts and reliance on assumptions.

1. What is Forecasting? Meaning
Forecasting is a process of predicting or estimating the future based on past and present data.
Forecasting provides information about the potential future events and their consequences for the
organization. It may not reduce the complications and uncertainty of the future. However, it
increases the confidence of the management to make important decisions. Forecasting is the
basis of premising. Forecasting uses many statistical techniques. Therefore, it is also called as
Statistical Analysis.
Peculiarities, characteristics or features of forecasting are as follows:-
1. Forecasting in concerned with future events.
2. It shows the probability of happening of future events.
3. It analysis past and present data.
4. It uses statistical tools and techniques.
5. It uses personal observations.
Merits, significance or importance of forecasting involves following points:-
1. Forecasting provides relevant and reliable information about the past and present events
and the likely future events. This is necessary for sound planning.
2. It gives confidence to the managers for making important decisions.
3. It is the basis for making planning premises.
4. It keeps managers active and alert to face the challenges of future events and the
changes in the environment.
Demerits, criticism or limitations of forecasting involves following points:-
1. The collection and analysis of data about the past, present and future involves a
lot of time and money. Therefore, managers have to balance the cost of
forecasting with its benefits. Many small firms don't do forecasting because of the
high cost.
2. Forecasting can only estimate the future events. It cannot guarantee that these
events will take place in the future. Long-term forecasts will be less accurate as
compared to short-term forecast.
3. Forecasting is based on certain assumptions. If these assumptions are wrong, the
forecasting will be wrong. Forecasting is based on past events. However, history
may not repeat itself at all times.
4. Forecasting requires proper judgement and skills on the part of managers.
Forecasts may go wrong due to bad judgement and skills on the part of some of
the managers. Therefore, forecasts are subject to human error.

2. What is Statistical Quality Control?
Statistics:
Statistics means the good amount of data to obtain reliable results. The Science of statistics
handles this data in order to draw certain conclusions. Its techniques find extensive applications
in quality control, production planning and control, business charts, linear programming etc.
Quality:
Quality is a relative term and is generally explained with reference to the end use of the product.
Quality is thus defined as fitness for purpose.
Control:
Control is a system for measuring and checking or inspecting a phenomenon. It suggests when to
inspect, how often to inspect and how much to inspect, how often to inspect. Control ascertains
quality characteristics of an item, compares the same with prescribed quality standards and
separates defective item from non-defective ones.
Statistical Quality Control (SQC) is the term used to describe the set of statistical tools used by
quality professionals. SQC is used to analyze the quality problems and solve them.
Statistical quality control refers to the use of statistical methods in the monitoring and
maintaining of the quality of products and services.
Objective of Statistical Quality Control
Quality Control is very important for a every company. Quality control includes service quality
given to customer, company management leadership, commitment of management, continuous
improvement, and fast response, actions based on facts, employee participation and a quality
driven culture.
The main objectives of the quality control module are to control of material reception, internal
rejections, clients, claims, providers and evaluations of the same corrective actions are related to
their follow-up. These systems and methods guide all quality activities. The development and
use of performance indicators is linked, directly or indirectly, to customer requirements and
satisfaction, and to management.
Benefits of Statistical Quality Control
1) It provides a means of detecting error at inspection.
2) It leads to more uniform quality of production.
3) It improves the relationship with the customer.
4) It reduces inspection costs.
5) It reduces the number of rejects and saves the cost of material.
6) It provides a basis for attainable specifications.
7) It points out the bottlenecks and trouble spots.
8) It provides a means of determining the capability of the manufacturing process.
9) It promotes the understanding and appreciation of quality control.