Sales forecasting involves estimating future sales over a specified period under a predetermined marketing plan. It is important for business planning and resource allocation. There are several methods for sales forecasting including survey methods that obtain expert opinions, mathematical methods using statistical analysis of historical data, and operational methods based on production capacity. Accurate sales forecasting considers factors like general business conditions, market trends, and the company's marketing plans. However, forecasts have limitations since the business environment and consumer behavior can change unpredictably.
Factors effecting selection of distribution channelsShubhanjali -
introduction to distribution
distribution channel
market intermediaries
factors affecting selection of distribution channels:-
1. Nature of product
2. Nature of market
3. Nature of middle men
4. Nature of manufacturing units
5. Competition
6. Govt. rules & policies
conclusion
references
Sales Forecasting
Sales forecasting is the process of a company predicting what its future sales will be. This forecast is done for a particular period of time in the near future, usually the next fiscal year. Accurate sales forecasting enables a company to make informed business decisions. Sales forecasting is easier for established companies that have been operating for a few years than for newer companies. Established companies have years of sales records and can base their forecasts on that past sales data. Newly founded companies have to base their forecasts on less verified information, such as market research and competition analysis to forecast their future business.
Why is Sales Forecasting important?
Sales Forecasting gives insight on whether a company should expand, information about cash flow, and the ability to effectively manage its resources. Without forecasting, a company would be unsure of what inventory level to maintain, unsure on how it should allocate resources across the company, and it would have a hard time predicting future success. Forecasting sales is a crucial business practice, because in addition to helping a company allocate its internal resources effectively, having this data is important for acquiring investment capital. Often, investors want to know what a company’s future expected sales are before making an investment.
Sales organization is a part of the total organization which is given the responsibility of selling of products manufactured by a company
It is another organization within the larger organization which is given the responsibility of selling function
It involves people working together for attaining the sales objectives of the company
It is concerned with planning, organizing, leading and controlling the activities of the sales force
Factors effecting selection of distribution channelsShubhanjali -
introduction to distribution
distribution channel
market intermediaries
factors affecting selection of distribution channels:-
1. Nature of product
2. Nature of market
3. Nature of middle men
4. Nature of manufacturing units
5. Competition
6. Govt. rules & policies
conclusion
references
Sales Forecasting
Sales forecasting is the process of a company predicting what its future sales will be. This forecast is done for a particular period of time in the near future, usually the next fiscal year. Accurate sales forecasting enables a company to make informed business decisions. Sales forecasting is easier for established companies that have been operating for a few years than for newer companies. Established companies have years of sales records and can base their forecasts on that past sales data. Newly founded companies have to base their forecasts on less verified information, such as market research and competition analysis to forecast their future business.
Why is Sales Forecasting important?
Sales Forecasting gives insight on whether a company should expand, information about cash flow, and the ability to effectively manage its resources. Without forecasting, a company would be unsure of what inventory level to maintain, unsure on how it should allocate resources across the company, and it would have a hard time predicting future success. Forecasting sales is a crucial business practice, because in addition to helping a company allocate its internal resources effectively, having this data is important for acquiring investment capital. Often, investors want to know what a company’s future expected sales are before making an investment.
Sales organization is a part of the total organization which is given the responsibility of selling of products manufactured by a company
It is another organization within the larger organization which is given the responsibility of selling function
It involves people working together for attaining the sales objectives of the company
It is concerned with planning, organizing, leading and controlling the activities of the sales force
Forecasting is a necessary and efficient tool that can give a company plenty of competitive advantage. Traditional methods of sales forecasting focused primarily on roll up of committed sales deals display intrinsic weakness due to their monotony of strategy across agreed sales period. This tends to produce inaccuracy in sales forecast, promotes sandbagging and reduces sales motion. Enhanced models centered on identifying weighted revenue through probabilities for opportunities by category also fail to recon in swing deals and ignores new opportunities in the pipelines. In this paper, I propose a better, dynamic method based on probabilities customized for each sales period.
Sales forecasting in the pharmaceutical industry involves predicting future sales based on historical data, market trends, and other relevant factors. It helps companies estimate product demand, plan inventory, allocate resources, and set realistic sales targets. Factors such as regulatory changes, competition, and healthcare trends influence these forecasts. Accurate sales predictions enable pharmaceutical companies to optimize production, manage supply chains efficiently, and adapt strategies to meet market demands, ultimately contributing to business success and effective healthcare product distribution.
This is a presentation covering the concepts of demand forecasting. it includes the meaning of demand forecasting, purpose, scope and factors affecting demand forecasting. It also covers the methods of forecasting for both new and existing products.
Acetabularia Information For Class 9 .docxvaibhavrinwa19
Acetabularia acetabulum is a single-celled green alga that in its vegetative state is morphologically differentiated into a basal rhizoid and an axially elongated stalk, which bears whorls of branching hairs. The single diploid nucleus resides in the rhizoid.
Normal Labour/ Stages of Labour/ Mechanism of LabourWasim Ak
Normal labor is also termed spontaneous labor, defined as the natural physiological process through which the fetus, placenta, and membranes are expelled from the uterus through the birth canal at term (37 to 42 weeks
This slide is special for master students (MIBS & MIFB) in UUM. Also useful for readers who are interested in the topic of contemporary Islamic banking.
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...Levi Shapiro
Letter from the Congress of the United States regarding Anti-Semitism sent June 3rd to MIT President Sally Kornbluth, MIT Corp Chair, Mark Gorenberg
Dear Dr. Kornbluth and Mr. Gorenberg,
The US House of Representatives is deeply concerned by ongoing and pervasive acts of antisemitic
harassment and intimidation at the Massachusetts Institute of Technology (MIT). Failing to act decisively to ensure a safe learning environment for all students would be a grave dereliction of your responsibilities as President of MIT and Chair of the MIT Corporation.
This Congress will not stand idly by and allow an environment hostile to Jewish students to persist. The House believes that your institution is in violation of Title VI of the Civil Rights Act, and the inability or
unwillingness to rectify this violation through action requires accountability.
Postsecondary education is a unique opportunity for students to learn and have their ideas and beliefs challenged. However, universities receiving hundreds of millions of federal funds annually have denied
students that opportunity and have been hijacked to become venues for the promotion of terrorism, antisemitic harassment and intimidation, unlawful encampments, and in some cases, assaults and riots.
The House of Representatives will not countenance the use of federal funds to indoctrinate students into hateful, antisemitic, anti-American supporters of terrorism. Investigations into campus antisemitism by the Committee on Education and the Workforce and the Committee on Ways and Means have been expanded into a Congress-wide probe across all relevant jurisdictions to address this national crisis. The undersigned Committees will conduct oversight into the use of federal funds at MIT and its learning environment under authorities granted to each Committee.
• The Committee on Education and the Workforce has been investigating your institution since December 7, 2023. The Committee has broad jurisdiction over postsecondary education, including its compliance with Title VI of the Civil Rights Act, campus safety concerns over disruptions to the learning environment, and the awarding of federal student aid under the Higher Education Act.
• The Committee on Oversight and Accountability is investigating the sources of funding and other support flowing to groups espousing pro-Hamas propaganda and engaged in antisemitic harassment and intimidation of students. The Committee on Oversight and Accountability is the principal oversight committee of the US House of Representatives and has broad authority to investigate “any matter” at “any time” under House Rule X.
• The Committee on Ways and Means has been investigating several universities since November 15, 2023, when the Committee held a hearing entitled From Ivory Towers to Dark Corners: Investigating the Nexus Between Antisemitism, Tax-Exempt Universities, and Terror Financing. The Committee followed the hearing with letters to those institutions on January 10, 202
How to Make a Field invisible in Odoo 17Celine George
It is possible to hide or invisible some fields in odoo. Commonly using “invisible” attribute in the field definition to invisible the fields. This slide will show how to make a field invisible in odoo 17.
Executive Directors Chat Leveraging AI for Diversity, Equity, and InclusionTechSoup
Let’s explore the intersection of technology and equity in the final session of our DEI series. Discover how AI tools, like ChatGPT, can be used to support and enhance your nonprofit's DEI initiatives. Participants will gain insights into practical AI applications and get tips for leveraging technology to advance their DEI goals.
Model Attribute Check Company Auto PropertyCeline George
In Odoo, the multi-company feature allows you to manage multiple companies within a single Odoo database instance. Each company can have its own configurations while still sharing common resources such as products, customers, and suppliers.
Exploiting Artificial Intelligence for Empowering Researchers and Faculty, In...Dr. Vinod Kumar Kanvaria
Exploiting Artificial Intelligence for Empowering Researchers and Faculty,
International FDP on Fundamentals of Research in Social Sciences
at Integral University, Lucknow, 06.06.2024
By Dr. Vinod Kumar Kanvaria
2. Definition
According to Henry Fayol : To foresee means both to assess the
future and make provision for it.
According to WJ Stanton : “Sales forecasting is an estimate of sales
during some specified future period of time and under a
predetermined marketing plan of the firm.”
3. Features
Estimate of sales
Predicting future
Projection for budgeting and planning purpose
For single or entire product line
Short term or long term
Considers environmental factors
Rational human behaviour
Result of demand forecasting
4. Importance and Objects
Foundation of planning
Allocation of resources
Key factor in business operation
Basis of sales planning
Major role in success
Help in profitability
Help in purchasing
Help in production planning
Help in strategy formulation
5. Conti….
Estimate of future sales
Encourage research and development
Better inventory control
Sales inventory control
Sales quota determination
Better financial planning
Better human resource planning
Facilitate distribution channels
Basis for establishing new industrial unit
Expansion of business
6. Sales forecasting period
Short term forecasting
To know the short term fluctuations
Estimation of inventory requirement
To determine sales quota
Estimation of manpower need
Estimation of working capital
7. Medium term forecasting
It is for 1 to 5 years
Business budgeting
To determine dividend policy
To determine financial planning
Long-Term forecasting
To establish a new factory
Search and development activities
Long term production planning
Capacity utilization
8. Factors influencing the sales forecast
General business conditions- taxation, pricing, bank credit etc.
Changing market conditions
Conditions within the industry
Internal policy
Marketing plans
Foreign trade conditions.
9. Procedure of Sales Forecasting
Determination of goals
Determination of the factors affecting sales
Selection of technique
Collection of data
Analysis the market potential
Forecasting of sales
Converting industry forecasting to company
Sales forecasting
Preparing operational programme & budget
Derivation of sales volume objectives.
Evaluation of revision of forecast.
10. Methods and Techniques of Sales Forecasting
1. Survey Method
2. Mathematical Method
3. Operational Method
11. Survey Method : Opinions of experts, sales people, executive and customers.
A) Executive opinion : Obtaining the views of top executive regarding future sales.
Merits:
Oldest and simplest technique
Quick and easy to do
Good for small, medium size and young firms.
Inclusion of competition and economic climate.
Demerits:
Unscientific
Time consuming
Difficult to teach this method
Increases the workload of key executives.
12. Prudent Manager Forecasting
It is a variation of first method where a company asked to assume the position of purchaser from
a customer’s point of view.
Delhi Method : It begins with a group of knowledgeable individual, who give their opinion for
estimating future sales. Sales each person makes a prediction without knowing how others in the
group have responded.
Merits
Innovative
Combine judgement
It prevents from influencing
Demerits
Lack of necessary information
13. Sales composite
Collecting and estimate from each salesperson, they expect to sale in future. Also knows as grass root approach.
Merits
Confidence in forecasting
Accuracy
Most Useful
Bottom-up approach
Utilizes the knowledge of salesman.
Demerits
Time consuming
Lack of experience
Over-estimate and under estimate
14. Detecting differences in figures method-
The salesperson produces figures for his product and the area manager produces figures for the
salesperson’s territory then they meet and discuss about their differences in figures.
Survey of wire intentions- Contacting potential customers and questioning them about whether or
not they would purchase the purchase at the price asked.
Merits:
Information obtained directly from the customers
Demerits:
Time consuming
Expensive
Large sample is required
Inaccuracy in information.
15. Product testing and test marketing
When new product launches in market. It is difficult to do sales forecasting on the basis of provisions
sales figures. Then few samples of the product are provided to the potential users before hand and
noting their reactions by asking them the weaknesses of the product.
Merits:
Direct interactions
Cost saving due to small number of samples
Demerits:
Time consuming
Poor evaluation of product.
16. 2. Mathematical Method: (Mathematical & Statistical Technique )
Moving Average Technique – Predict that sales in the coming period will be equal to sales in the
last period.
Merits:
Easy to compute
Easy to apply
Demerits:
Unreliable
Difficult to study the impact of factors that will be arise in future but were not present in past.
17. Exponential smoothing model : It represents a weighted sum of all past numbers with the
heaviest weight placed on the most recent data.
Merits:
Determine the degree of sales with confidence
Demerits:
It is useful for short range sales only.
Regression Analysis: Sales total are plotted for each past time period. It determines and measure
the association between company sales and other variables.
18. Projection of past sales: To set the sales forecast as current year actual sales can be made by
adding a set percentage of last year sale or moving average for several past years.
Time Series Analysis: Statistical procedure for studying historical sales data including long term
trend, cyclical changes, seasonsal variations and irregular fluctuations.
Merits: Useful for long term forecasting
Demerits: Difficult to predict and analyse
Market Factor Analysis: Future demand is related to the behaviour of certain market forces or
factors.
Correlation – Association between potential sales and market factors affecting its sale.
Z (zee) Chart – It shows the monthly sales and cumulative sales.
19. Operational Method - Information about the companies capacity and financial requirements.
Must Do Calculation – Based on the sales volume needed to generate sufficient cash to cover fixed
and variable cost. Management may forecast the sales volume on the basis of profit goal.
Capacity Based Forecast – The owner of the company develops this method according to the capacity
of production.
Econometric Model Building – It represent a set of relationship among sales and different demand
determining independent variables (Durable goods)
Other Techniques –
Leading Indicators – To define and establish a linear regression relationship between some
measurable variables.
Simulation – It is a process of analysis to arrive at forecasting.
Diffusion model : When a new product is introduced in market (Which is not extension/redesign of
old product)
20. Limitations of sales forecasting
Changes in business environment
Change in consumer behaviour
Lack of accurate data
Based on assumptions
Uncertain growth rate
Expensive method
Mathematical complexity
Lack of expert and qualified forecasters
Influence of psychological factors
Lack of sales history.