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This document discusses various qualitative and quantitative methods for sales forecasting. Qualitative methods include survey methods, expert opinions, market studies, and salesforce opinions. Quantitative methods include trend analysis, graphical analysis, and time series analysis. Time series analysis predicts future sales by analyzing historical relationships between sales and time over many years. Sales forecasting helps companies train salespeople to better interpret customer interactions and improve their forecasting abilities.
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Forecasting and demand measurement
Demand refers to a buyer's willingness and ability to pay for a good or service. Forecasting is predicting the future based on past and present data. Forecasting is used for production planning, sales forecasting, inventory control, and long-term investment growth and stability. Short-term forecasting helps with production scheduling, reducing goods, determining price policies, and short-term financial planning. Long-term forecasting assists with new unit or expansion planning, man-power planning, and long-term financial planning. Forecasting methods include consumer surveys, statistical techniques like trend projection, and graphical and least squares methods.
Steps in Demand Forecasting
This document outlines the steps for demand forecasting and criteria for a good forecasting method. It discusses determining the purpose of the forecast, subdividing the demand program, identifying factors affecting sales, selecting forecasting methods, studying competitors, preparing preliminary sales estimates, analyzing promotion plans, evaluating forecasts, preparing the final forecast, and ensuring the method is accurate, plausible, economical, quick, durable, and flexible.
Demand Forecasting and Market planning
This document discusses demand forecasting techniques used to predict future demand for products and services. It covers qualitative methods like executive opinion and surveys, as well as quantitative time series and causal models. Time series methods explained include moving averages, trend projection using least squares, and exponential smoothing. Causal models relate demand to factors like income, price, and leading economic indicators. The document notes uncertainties in demand forecasting arise from limitations of past data, unrealistic assumptions in models, and changes that are difficult to predict.
Sale Forecasting In Organization1
Sales forecasting is an important process that allows companies to predict future sales and make informed decisions. It involves determining future demand for products and using that information for sales planning, supply chain management, financial planning, and other key business functions. Accurate forecasting requires gathering data, selecting an appropriate forecasting model, and validating results. While forecasting provides many benefits, errors can occur if the data, assumptions, or environment changes in unexpected ways. Overly optimistic or pessimistic forecasts can lead to overproduction or underproduction.
Demand forcasting
Forecasting demand involves predicting future needs based on past patterns. Long-term forecasts inform strategic decisions about products, processes, and facilities. Short-term forecasts guide production decisions over the next few weeks. Common forecasting methods include opinion surveys, statistical analyses of time series data, and linking demand for one product to indicators of demand for related products. Accuracy, simplicity, cost, and ability to reflect changing conditions are criteria for evaluating forecasting techniques.
Sales forecasting
The document discusses sales forecasting, including defining a sales forecast as an estimated amount of sales or units for a future time period based on a marketing plan and market environment. Sales forecasting is necessary to plan cash flow, production capacity, supplies, and hiring. Key factors considered in sales forecasting include past sales trends, economic conditions, pricing, promotions, and competitors' actions. The document then outlines the sales forecasting process, including defining potential market sizes and using top-down or bottom-up approaches to forecast sales at different levels.
Demand forecasting
The document discusses various methods of demand forecasting that can be broadly divided into survey methods and statistical methods. Survey methods include collective opinion, Delphi, consumers' interview, and test marketing. Statistical methods discussed are trend projection, correlation/regression, and barometric techniques. Each method is described along with its advantages and disadvantages. Key factors in choosing a good forecasting method are accuracy, plausibility, cost, availability of data, ability to adapt to changes over time, and flexibility.
Sale forecasting
This document provides information about an individual named Vikash Kumar and discusses market research, sales forecasting, and forecasting methods. It defines market research as determining what to produce, who will purchase items, where purchasers are located, how much to manufacture, when to sell, and how to maximize profits. Sales forecasting is defined as estimating future sales of an item or products. The document outlines short-term and long-term forecasting and their purposes, including planning production, materials, purchases, and workforce. It also discusses forecast errors.
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Forecasting and demand measurement
Demand refers to a buyer's willingness and ability to pay for a good or service. Forecasting is predicting the future based on past and present data. Forecasting is used for production planning, sales forecasting, inventory control, and long-term investment growth and stability. Short-term forecasting helps with production scheduling, reducing goods, determining price policies, and short-term financial planning. Long-term forecasting assists with new unit or expansion planning, man-power planning, and long-term financial planning. Forecasting methods include consumer surveys, statistical techniques like trend projection, and graphical and least squares methods.
Steps in Demand Forecasting
This document outlines the steps for demand forecasting and criteria for a good forecasting method. It discusses determining the purpose of the forecast, subdividing the demand program, identifying factors affecting sales, selecting forecasting methods, studying competitors, preparing preliminary sales estimates, analyzing promotion plans, evaluating forecasts, preparing the final forecast, and ensuring the method is accurate, plausible, economical, quick, durable, and flexible.
Demand Forecasting and Market planning
This document discusses demand forecasting techniques used to predict future demand for products and services. It covers qualitative methods like executive opinion and surveys, as well as quantitative time series and causal models. Time series methods explained include moving averages, trend projection using least squares, and exponential smoothing. Causal models relate demand to factors like income, price, and leading economic indicators. The document notes uncertainties in demand forecasting arise from limitations of past data, unrealistic assumptions in models, and changes that are difficult to predict.
Sale Forecasting In Organization1
Sales forecasting is an important process that allows companies to predict future sales and make informed decisions. It involves determining future demand for products and using that information for sales planning, supply chain management, financial planning, and other key business functions. Accurate forecasting requires gathering data, selecting an appropriate forecasting model, and validating results. While forecasting provides many benefits, errors can occur if the data, assumptions, or environment changes in unexpected ways. Overly optimistic or pessimistic forecasts can lead to overproduction or underproduction.
Demand forcasting
Forecasting demand involves predicting future needs based on past patterns. Long-term forecasts inform strategic decisions about products, processes, and facilities. Short-term forecasts guide production decisions over the next few weeks. Common forecasting methods include opinion surveys, statistical analyses of time series data, and linking demand for one product to indicators of demand for related products. Accuracy, simplicity, cost, and ability to reflect changing conditions are criteria for evaluating forecasting techniques.
Sales forecasting
The document discusses sales forecasting, including defining a sales forecast as an estimated amount of sales or units for a future time period based on a marketing plan and market environment. Sales forecasting is necessary to plan cash flow, production capacity, supplies, and hiring. Key factors considered in sales forecasting include past sales trends, economic conditions, pricing, promotions, and competitors' actions. The document then outlines the sales forecasting process, including defining potential market sizes and using top-down or bottom-up approaches to forecast sales at different levels.
Demand forecasting
The document discusses various methods of demand forecasting that can be broadly divided into survey methods and statistical methods. Survey methods include collective opinion, Delphi, consumers' interview, and test marketing. Statistical methods discussed are trend projection, correlation/regression, and barometric techniques. Each method is described along with its advantages and disadvantages. Key factors in choosing a good forecasting method are accuracy, plausibility, cost, availability of data, ability to adapt to changes over time, and flexibility.
Sale forecasting
This document provides information about an individual named Vikash Kumar and discusses market research, sales forecasting, and forecasting methods. It defines market research as determining what to produce, who will purchase items, where purchasers are located, how much to manufacture, when to sell, and how to maximize profits. Sales forecasting is defined as estimating future sales of an item or products. The document outlines short-term and long-term forecasting and their purposes, including planning production, materials, purchases, and workforce. It also discusses forecast errors.
Sales forecasting
This document discusses sales forecasting, budgeting, and cost control. It defines sales forecasting as the estimated level of company sales based on a chosen marketing plan and assumed environmental conditions. The key steps in sales forecasting include identifying important factors, selecting suitable forecasting methods, developing preliminary forecasts, and evaluating and revising forecasts. Budgeting is defined as an estimate of income and expenditure over a period of time and is an important tool for planning, coordination, communication, motivation, and control. Sales budgets in particular show expected sales units, price per unit, and total expected sales. Budgetary control helps with planning, coordination, communication, motivation, and oversight of an organization.
Forecasting demand
This document discusses qualitative methods for forecasting demand. It describes five qualitative forecasting methods: (1) survey of buyers intentions, (2) test marketing, (3) sales force composite, (4) executive method, and (5) Delphi method. These methods involve subjective judgements from managers, buyers, salespeople, or committees rather than numerical or statistical analysis. The key advantage of qualitative methods is that they are simple and easy to use, but they rely heavily on subjective opinions and can lack accuracy. A combination of qualitative and quantitative methods may provide the best forecast.
Retail Forecasting
This document discusses forecasting techniques used in the retail industry. It outlines the challenges retailers face in forecasting including scale, intermittent demand, and assortment changes. It then describes techniques like large-scale automated forecasting to address these challenges. The document also discusses how forecasting is used for revenue optimization, replenishment, sales forecasting, demand forecasting, and focus forecasting. It provides examples of software used for retail forecasting like SAS Demand Forecasting, Oracle Retail, and SAP. The conclusion emphasizes that forecasts will never be perfect but the goal is accuracy and efficiency.
Bba 1 be 1 u-2.2 demand forecasting
This document discusses demand forecasting techniques. It outlines qualitative techniques like expert opinion and surveys, and quantitative techniques like time series analysis. It describes key methods like the Delphi method, market surveys, test marketing, and time series analysis. Time series analysis breaks down past sales data into trends, seasonal variations, cyclical variations, and random fluctuations to forecast future demand. Accurate forecasting requires knowledge of the product, customers, and business environment.
Demand forecasting-slide share
This document provides an overview of demand forecasting. It defines demand forecasting as estimating future sales based on marketing plans and external forces. It discusses different categories (passive vs active) and timeframes (short vs long term) of forecasts. The key components and methods of demand forecasting are also outlined, including opinion polling, statistical/analytical techniques like trend projection, regression, and econometric analysis. The importance of demand forecasting is emphasized for production planning, sales forecasting, inventory control, economic policymaking, and long-term growth.
Demand forecasting
This document discusses demand forecasting. Demand forecasting involves estimating expected demand over a future period. It can be done at the micro, industry, or macro level. Short term demand forecasting is done for periods under one year and considers immediate changes. Long term forecasting decides business size and expansion. Key steps in demand forecasting include determining objectives, subdividing tasks, identifying demand determinants, selecting methods, evaluating sales, and reporting findings.
Class 6 definition of methods demand forecasting
Demand forecasting is the process of estimating future demand for a product based on factors like past sales, market conditions, and consumer preferences. Accurate demand forecasting is important for several business functions like production planning, inventory control, sales forecasting, and long-term investment decisions. Common methods for demand forecasting include survey methods like asking consumers about future purchase plans, statistical techniques like trend analysis and regression analysis, and expert opinions. While demand forecasting provides estimates, it cannot predict demand with 100% accuracy.
DEAMAND FORCASTING
Demand forecasting predicts future demand for a firm's products and helps with production planning and scheduling, acquiring inputs, financial planning, pricing strategy, and advertising planning. The key steps are specifying objectives, determining the time horizon, selecting a forecasting method, collecting and adjusting data, estimating results, and interpreting them. Common techniques include consumer surveys, expert opinions, statistical methods, and opinion polls. Consumer surveys directly interview a sample of potential consumers to determine future purchase plans, while expert opinions aggregate sales representatives' assessments of demand in their regions.
Demand forecasting | Prof. Sachin Paurush
Demand forecasting is a vital concept in Management Economics. A detailed description of the topic have been jotted down.
Demand forecasting
Demand forecasting involves using past demand information to predict future demand. It is important for production planning, acquiring supplies, financial planning, pricing strategies, and advertising. Both qualitative and quantitative techniques are used. Qualitative techniques like expert opinion and surveys are used when little historical data exists, while quantitative time series analysis of trends, seasons, cycles, and random variations is used for existing products. Forecasting allows production to match demand and helps businesses plan effectively.
Sales forecasting
This document discusses sales forecasting. It begins by defining sales forecasting as projecting expected customer demand for products or services under certain assumptions. Forecasting can be used for strategic planning, finance, marketing, and production. The document then lists some principles of forecasting, noting that forecasts are rarely perfect and more accurate for shorter time periods and grouped data. It discusses internal and external factors that can affect forecasts. The rest of the document outlines different types of forecasting methods, including qualitative methods based on judgments and quantitative methods based on mathematical models. It provides examples of various qualitative and quantitative forecasting methods.
Statistics applied to the interdisciplinary areas of marketing
Optimising price and marketing mix.
Concept of learning. When an account/product has too little sales data, bayesian shrinkage allows us to borrow information from other accounts.
Deals with outliers, by shrinking estimates towards each other.
Allows one hierarchical model instead of multiple models.
More robust, stable estimates with significant regional and account variation in estimates that cannot be done in a classical linear model.
Provides price elasticity measure that shows the impact of price changes on volume
Sales forecasting
The document discusses various methods for sales forecasting. It describes 8 steps in the sales forecasting process: 1) deciding basic issues; 2) identifying important factors; 3) selecting suitable methods; 4) deciding length; 5) preliminary sales forecast; 6) final sales forecast; 7) making operational program; 8) evaluation and revision. It then explains 8 different methods for sales forecasting: executive opinion, experts opinion, sales force opinion, Delphi method, user's expectation, economic indicators analysis, past sales projection, and market test. Statistical methods like trends projection and regression analysis are also mentioned.
Sales forecasting
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.
sales forecasting and its method
This document discusses sales forecasting techniques. It begins with an introduction to sales forecasting and its importance for setting sales quotas and budgets. It then covers qualitative and quantitative forecasting methods. Qualitative methods include jury of executive opinion, Delphi technique, sales force composite, and buyer surveys. Quantitative methods include continuity extrapolation, time series analysis, exponential smoothing, regression analysis, and econometric models. The document emphasizes that both qualitative and quantitative methods are useful for sales forecasting. It concludes that proper demand forecasting enables better business planning and decision making.
Sales forecasting
Sales Forecasting is the process of estimating future sales. Sales forecasts enable companies to make business decisions and predict short-term and long-term performance. Companies can base their forecasts on past sales data, industry-wide comparisons and economic trends.
Sales Forecasting
This document discusses sales forecasting methods. It defines sales forecasting as projecting expected customer demand for products or services at a company for a specific time horizon based on certain assumptions. Accurate forecasts are important for business planning, marketing, and management decisions. Both quantitative and qualitative methods are described. Quantitative methods include the executive opinion method, sales force composite method, and survey of buyer's intentions. Qualitative methods include time series analysis, market test method, and regression analysis. Accurate short, medium, and long term forecasts benefit businesses through improved inventory control, staffing, customer information, sales performance, and financing. Limitations include forecasts containing elements of subjectivity and uncertainty due to changing market conditions.
Demand forecasting
This document discusses demand forecasting. It describes demand forecasting as estimating future demand under constraints. There are short, medium, and long term forecasts. Factors that influence forecasts include the time period, purpose, forecasting methods, product type, and competition. Good forecasting methods are accurate, durable, available, and economical. Common methods are survey methods like consumer surveys and statistical methods like time series analysis and regression. Time series analysis examines trends, seasons, business cycles, and random variations. Forecasting consumer durables is difficult due to changing demographics and market saturation.
Mopex model From Mattcons
The document provides an overview of Mattcons' Operational Excellence Model (MOPEX). Key points include:
- MOPEX helps companies achieve business goals through standardizing processes, lowering costs, and improving cycle times.
- Using methodologies like TPM, Lean Manufacturing, and Kaizen, MOPEX can reduce costs by 20-30% and improve productivity by 30-60%.
- Mattcons has implemented MOPEX for clients in various industries like steel, cement, food processing, and more. Client case studies show improvements in metrics like OEE, downtime, inventory levels, and safety.
Tally for sales&distribution
This document discusses the challenges in sales and distribution for multi-location companies and presents Tally.EEP9 as a solution. It provides an overview of key aspects of the distribution cycle including purchase/import of goods, cost addition, inter-branch transfers, goods in transit tracking, and reporting. The solution allows for uniform master data creation and automatic data synchronization between head office and branch locations for real-time consolidated reporting.
Rkfl Problem Solving
The document discusses various quality control and problem solving tools and techniques including:
- Approaches to problem solving like defining the problem, diagnosing causes, implementing remedies, and maintaining improvements
- Tools for analyzing problems like cause-effect diagrams, checksheets, control charts, histograms, Pareto charts, and scatter plots
- Guidelines for using these tools effectively like how to structure a team, gather and analyze data, identify root causes, and monitor ongoing performance
The overall aim is to provide an overview of a structured approach and key analytical methods for quality improvement and problem solving.
Sales budget ,forcasting and control
This document discusses sales budgeting, forecasting, and control. It covers developing sales budgets to plan and coordinate sales, types of budgets including sales, selling expense, and administrative budgets. Forecasting methods like macro, micro, qualitative, and quantitative are described. Sales forecasting is used for production scheduling, pricing, promotion, and financial planning. Control involves setting standards, evaluating performance, and correcting deviations to optimize sales, profits, and revenue.
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Sales forecasting
This document discusses sales forecasting, budgeting, and cost control. It defines sales forecasting as the estimated level of company sales based on a chosen marketing plan and assumed environmental conditions. The key steps in sales forecasting include identifying important factors, selecting suitable forecasting methods, developing preliminary forecasts, and evaluating and revising forecasts. Budgeting is defined as an estimate of income and expenditure over a period of time and is an important tool for planning, coordination, communication, motivation, and control. Sales budgets in particular show expected sales units, price per unit, and total expected sales. Budgetary control helps with planning, coordination, communication, motivation, and oversight of an organization.
Forecasting demand
This document discusses qualitative methods for forecasting demand. It describes five qualitative forecasting methods: (1) survey of buyers intentions, (2) test marketing, (3) sales force composite, (4) executive method, and (5) Delphi method. These methods involve subjective judgements from managers, buyers, salespeople, or committees rather than numerical or statistical analysis. The key advantage of qualitative methods is that they are simple and easy to use, but they rely heavily on subjective opinions and can lack accuracy. A combination of qualitative and quantitative methods may provide the best forecast.
Retail Forecasting
This document discusses forecasting techniques used in the retail industry. It outlines the challenges retailers face in forecasting including scale, intermittent demand, and assortment changes. It then describes techniques like large-scale automated forecasting to address these challenges. The document also discusses how forecasting is used for revenue optimization, replenishment, sales forecasting, demand forecasting, and focus forecasting. It provides examples of software used for retail forecasting like SAS Demand Forecasting, Oracle Retail, and SAP. The conclusion emphasizes that forecasts will never be perfect but the goal is accuracy and efficiency.
Bba 1 be 1 u-2.2 demand forecasting
This document discusses demand forecasting techniques. It outlines qualitative techniques like expert opinion and surveys, and quantitative techniques like time series analysis. It describes key methods like the Delphi method, market surveys, test marketing, and time series analysis. Time series analysis breaks down past sales data into trends, seasonal variations, cyclical variations, and random fluctuations to forecast future demand. Accurate forecasting requires knowledge of the product, customers, and business environment.
Demand forecasting-slide share
This document provides an overview of demand forecasting. It defines demand forecasting as estimating future sales based on marketing plans and external forces. It discusses different categories (passive vs active) and timeframes (short vs long term) of forecasts. The key components and methods of demand forecasting are also outlined, including opinion polling, statistical/analytical techniques like trend projection, regression, and econometric analysis. The importance of demand forecasting is emphasized for production planning, sales forecasting, inventory control, economic policymaking, and long-term growth.
Demand forecasting
This document discusses demand forecasting. Demand forecasting involves estimating expected demand over a future period. It can be done at the micro, industry, or macro level. Short term demand forecasting is done for periods under one year and considers immediate changes. Long term forecasting decides business size and expansion. Key steps in demand forecasting include determining objectives, subdividing tasks, identifying demand determinants, selecting methods, evaluating sales, and reporting findings.
Class 6 definition of methods demand forecasting
Demand forecasting is the process of estimating future demand for a product based on factors like past sales, market conditions, and consumer preferences. Accurate demand forecasting is important for several business functions like production planning, inventory control, sales forecasting, and long-term investment decisions. Common methods for demand forecasting include survey methods like asking consumers about future purchase plans, statistical techniques like trend analysis and regression analysis, and expert opinions. While demand forecasting provides estimates, it cannot predict demand with 100% accuracy.
DEAMAND FORCASTING
Demand forecasting predicts future demand for a firm's products and helps with production planning and scheduling, acquiring inputs, financial planning, pricing strategy, and advertising planning. The key steps are specifying objectives, determining the time horizon, selecting a forecasting method, collecting and adjusting data, estimating results, and interpreting them. Common techniques include consumer surveys, expert opinions, statistical methods, and opinion polls. Consumer surveys directly interview a sample of potential consumers to determine future purchase plans, while expert opinions aggregate sales representatives' assessments of demand in their regions.
Demand forecasting | Prof. Sachin Paurush
Demand forecasting is a vital concept in Management Economics. A detailed description of the topic have been jotted down.
Demand forecasting
Demand forecasting involves using past demand information to predict future demand. It is important for production planning, acquiring supplies, financial planning, pricing strategies, and advertising. Both qualitative and quantitative techniques are used. Qualitative techniques like expert opinion and surveys are used when little historical data exists, while quantitative time series analysis of trends, seasons, cycles, and random variations is used for existing products. Forecasting allows production to match demand and helps businesses plan effectively.
Sales forecasting
This document discusses sales forecasting. It begins by defining sales forecasting as projecting expected customer demand for products or services under certain assumptions. Forecasting can be used for strategic planning, finance, marketing, and production. The document then lists some principles of forecasting, noting that forecasts are rarely perfect and more accurate for shorter time periods and grouped data. It discusses internal and external factors that can affect forecasts. The rest of the document outlines different types of forecasting methods, including qualitative methods based on judgments and quantitative methods based on mathematical models. It provides examples of various qualitative and quantitative forecasting methods.
Statistics applied to the interdisciplinary areas of marketing
Optimising price and marketing mix.
Concept of learning. When an account/product has too little sales data, bayesian shrinkage allows us to borrow information from other accounts.
Deals with outliers, by shrinking estimates towards each other.
Allows one hierarchical model instead of multiple models.
More robust, stable estimates with significant regional and account variation in estimates that cannot be done in a classical linear model.
Provides price elasticity measure that shows the impact of price changes on volume
Sales forecasting
The document discusses various methods for sales forecasting. It describes 8 steps in the sales forecasting process: 1) deciding basic issues; 2) identifying important factors; 3) selecting suitable methods; 4) deciding length; 5) preliminary sales forecast; 6) final sales forecast; 7) making operational program; 8) evaluation and revision. It then explains 8 different methods for sales forecasting: executive opinion, experts opinion, sales force opinion, Delphi method, user's expectation, economic indicators analysis, past sales projection, and market test. Statistical methods like trends projection and regression analysis are also mentioned.
Sales forecasting
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.
sales forecasting and its method
This document discusses sales forecasting techniques. It begins with an introduction to sales forecasting and its importance for setting sales quotas and budgets. It then covers qualitative and quantitative forecasting methods. Qualitative methods include jury of executive opinion, Delphi technique, sales force composite, and buyer surveys. Quantitative methods include continuity extrapolation, time series analysis, exponential smoothing, regression analysis, and econometric models. The document emphasizes that both qualitative and quantitative methods are useful for sales forecasting. It concludes that proper demand forecasting enables better business planning and decision making.
Sales forecasting
Sales Forecasting is the process of estimating future sales. Sales forecasts enable companies to make business decisions and predict short-term and long-term performance. Companies can base their forecasts on past sales data, industry-wide comparisons and economic trends.
Sales Forecasting
This document discusses sales forecasting methods. It defines sales forecasting as projecting expected customer demand for products or services at a company for a specific time horizon based on certain assumptions. Accurate forecasts are important for business planning, marketing, and management decisions. Both quantitative and qualitative methods are described. Quantitative methods include the executive opinion method, sales force composite method, and survey of buyer's intentions. Qualitative methods include time series analysis, market test method, and regression analysis. Accurate short, medium, and long term forecasts benefit businesses through improved inventory control, staffing, customer information, sales performance, and financing. Limitations include forecasts containing elements of subjectivity and uncertainty due to changing market conditions.
Demand forecasting
This document discusses demand forecasting. It describes demand forecasting as estimating future demand under constraints. There are short, medium, and long term forecasts. Factors that influence forecasts include the time period, purpose, forecasting methods, product type, and competition. Good forecasting methods are accurate, durable, available, and economical. Common methods are survey methods like consumer surveys and statistical methods like time series analysis and regression. Time series analysis examines trends, seasons, business cycles, and random variations. Forecasting consumer durables is difficult due to changing demographics and market saturation.
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Statistics applied to the interdisciplinary areas of marketing
Statistics applied to the interdisciplinary areas of marketing
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Mopex model From Mattcons
The document provides an overview of Mattcons' Operational Excellence Model (MOPEX). Key points include:
- MOPEX helps companies achieve business goals through standardizing processes, lowering costs, and improving cycle times.
- Using methodologies like TPM, Lean Manufacturing, and Kaizen, MOPEX can reduce costs by 20-30% and improve productivity by 30-60%.
- Mattcons has implemented MOPEX for clients in various industries like steel, cement, food processing, and more. Client case studies show improvements in metrics like OEE, downtime, inventory levels, and safety.
Tally for sales&distribution
This document discusses the challenges in sales and distribution for multi-location companies and presents Tally.EEP9 as a solution. It provides an overview of key aspects of the distribution cycle including purchase/import of goods, cost addition, inter-branch transfers, goods in transit tracking, and reporting. The solution allows for uniform master data creation and automatic data synchronization between head office and branch locations for real-time consolidated reporting.
Rkfl Problem Solving
The document discusses various quality control and problem solving tools and techniques including:
- Approaches to problem solving like defining the problem, diagnosing causes, implementing remedies, and maintaining improvements
- Tools for analyzing problems like cause-effect diagrams, checksheets, control charts, histograms, Pareto charts, and scatter plots
- Guidelines for using these tools effectively like how to structure a team, gather and analyze data, identify root causes, and monitor ongoing performance
The overall aim is to provide an overview of a structured approach and key analytical methods for quality improvement and problem solving.
Sales budget ,forcasting and control
This document discusses sales budgeting, forecasting, and control. It covers developing sales budgets to plan and coordinate sales, types of budgets including sales, selling expense, and administrative budgets. Forecasting methods like macro, micro, qualitative, and quantitative are described. Sales forecasting is used for production scheduling, pricing, promotion, and financial planning. Control involves setting standards, evaluating performance, and correcting deviations to optimize sales, profits, and revenue.
Market Analysis Tools
The document discusses various tools that can be used to analyze markets and the external environment of an organization. It describes macro environmental factors like PEST analysis that assess political, economic, social and technological issues outside a company's control. Micro factors closer to the organization include competitors, marketing intermediaries, and suppliers that can influence operations. SWOT analysis examines internal strengths and weaknesses as well as external opportunities and threats. Product analysis assesses customer needs while portfolio analysis evaluates a company's range of products. Competitor benchmarking also allows comparison to other businesses.
Planning, Sales Forecasting, and Budgeting
The document discusses strategic planning, sales forecasting, and budgeting. It defines strategic planning as deciding on long-term objectives and strategies. Marketing plays a key role in strategic planning by providing market information and developing competitive advantages. Sales strategy is developed from marketing strategy through marketing mix and promotional strategies. There are qualitative and quantitative methods for sales forecasting, including executive opinion, regression analysis, and moving averages. The sales budget estimates sales volume and expenses for purposes of planning, coordination, and control.
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Sales forecasting
Help for the brand leader on how to do forecasting, the analytics behind it as well as the importance.
price discounting strategy. As a result, the hotel decided to focu.docx
price discounting strategy. As a result, the hotel decided to focus on the government market because of the hotel's location.
The government market is price-sensitive (there is an allowable per diem) and not as quality-conscious, and the hotel could selectively discount to this large-volume market. Once again, it is important to point out that marketing planning is a continuous process. Marketing managers must evaluate the situation and adapt to changes that occur. Evaluating the success of the marketing plan is the moment of truth. Managers develop a plan to increase the probability of success, and once the plan is implemented, it is important for management to monitor the results. Any variance from the predicted results should be identified, evaluated, and corrected.
As the environment changes or the results vary, management may need to return to the appropriate step to reformulate marketing strategy or the action plans. The marketing planning process continues as a dynamic procedure, with sufficient flexibility allowing for changes in strategies, action plans, or implementation schedules.
SALES FORECASTING
190 CHAPTER 5 DEVELOPING A MARKETING PLAN
SALES FORECASTING 189
One of the most critical components of a marketing plan is the forecast for sales. Sales forecasting is the process for determining current sales and estimating future sales for a product or service. The success of the firm often results from the accuracy of forecasts. The decisions about the elements of the marketing mix—product-service mix, price, promotion, and distribution— that are made during the situation analysis are based on sales forecasts.
Sales forecasting The process for determining current sales and estimating future sales for a product or service.
Sales Forecasting Techniques
Sales forecasting techniques are separated" into two broad categories: quantitative techniques and qualitative techniques. Quantitative techniques use past data values and employ a set of rules to obtain estimates of future sales. Qualitative techniques rely on judgment or intuition and tend to be used when data are not readily available. Quantitative methods can be further classified as either causal or time series. Both types of quantitative methods use trends in historical data to predict future sales; however, causal analysis techniques establish a cause and effect relationship between variables and the results. Using historical data to establish the relationship between sales and other factors that are believed to influence sales. These techniques model the relationships
Expert opinion
Marketers look to a panel of experts with knowledge of the industry and the marketplace to provide a forecast.
Delphi technique The Delphi technique involves collecting forecasts, developing composites, and sending the data to those participating several times until a consensus results.
Sales force forecast
This technique aggregates the sales forecast of each .
Mkt
Forecasting involves predicting the future by analyzing past and present data. Sales forecasting predicts future sales over a period based on factors like past performance, economic conditions, and market trends. Qualitative forecasting techniques incorporate expert judgment and include consumer surveys, sales force polling, executive opinions, and the Delphi technique. While qualitative techniques allow for rich data, they are also time-intensive and subject to human biases. Quantitative techniques provide structure but lack nuanced insights. An ideal approach combines both.
SLE ECONOMICS
Demand forecasting involves estimating future demand for a product or service based on past data and consumer behavior analysis. There are several types of demand forecasting including passive, active, firm-level, industry-level, and national-level forecasting. Common demand forecasting methods include surveys, expert opinions, sales force opinions, and market experimentation. An effective forecasting method should be simple, accurate, economical, flexible, and able to provide quick results. Demand forecasting is important for business planning, budgeting, management decision making, and evaluating performance.
6 Demand forecasting
This document discusses demand forecasting methods used by businesses. It describes short-term and long-term demand forecasting and their purposes. Short-term forecasting relates to existing production capacity and helps with pricing and financial policies, while long-term forecasting informs new plant planning and product demand. The document also outlines survey methods like opinion surveys of salespeople and expert opinions, as well as statistical methods like time series analysis, barometric techniques, and regression/correlation analysis that use past data to project future trends.
Demand forecasting
Demand forecasting involves anticipating future demand for a company's products and services under uncertain competitive conditions. It is essential for production planning, purchasing raw materials, and other business decisions. Demand can be forecasted qualitatively using opinion surveys of consumers, salespeople, and experts, or quantitatively using statistical techniques like trend projection, regression analysis, and econometrics that analyze historical demand data and its relationships to economic indicators. Accurate demand forecasting is important for production planning, inventory control, sales forecasting, budgeting, and long-term growth strategies.
demandforecasting-180917122131.pptx
Demand forecasting involves anticipating future demand for an organization's products and services under uncertain competitive conditions. Accurate forecasts are essential for production planning, purchasing inputs, and other business decisions. There are qualitative and quantitative forecasting methods. Qualitative methods include consumer surveys, salesforce opinions, and expert panels. Quantitative methods use historical sales data and statistical analysis, such as time series analysis, regression analysis, and econometric modeling of economic factors. Accurate demand forecasting is important for production planning, sales forecasting, inventory control, and long-term strategic planning.
Forecasting method
Sales forecasting is a difficult area of management. Most managers believe they are good at forecasting
Forecasting methods by Neeraj Bhandari ( Surkhet.Nepal )
This document discusses various forecasting methods used to predict future outcomes when historical data is available or not. It describes subjective qualitative methods like sales force composites, customer surveys, and Delphi techniques that rely on expert opinions. Objective quantitative methods include causal models that examine factors influencing outcomes and time series analysis of historical trends, seasonality, and levels. The document also outlines short, medium, and long-term forecasting horizons and the appropriate techniques for each.
sales presentation
This document discusses techniques for transforming customer information into sales knowledge and forecasting. It covers key elements like knowledge gathered by sales forces, forecasting processes, ethics in sales management, and forecasting techniques. Some techniques discussed include using customer and distributor surveys, statistical models, judgment-based approaches like executive opinions, and combining multiple forecasting methods to improve accuracy. The document also notes limitations of forecasting like data quality, rapid market changes, and forecasting time horizon and costs.
Sales Management - Unit-1.pptx
1. The document discusses sales management, including defining it as the management of a firm's sales operations. It covers the objectives of sales management such as growing revenue, setting sales volumes, and improving production.
2. Sales forecasting methods are explained, including qualitative methods like expert opinion and quantitative methods like time series analysis. Sales planning and control involves setting goals, analyzing the current situation, preparing action plans, and setting performance metrics.
3. The document provides an overview of key concepts in sales management, forecasting, and planning, outlining definitions, objectives, methods, and the sales planning and control process in 3 sentences or less.
Demand Forcasting
This document discusses demand forecasting techniques used by product managers. It defines demand forecasting as using statistical data and market determinants to predict future demand. There are two types of forecasts: passive, which assume no changes to company actions, and active, which account for likely changes. Short term forecasts relate to periods under a year and are used for production, sales, pricing and target policies. Long term forecasts cover multiple years and are used for business, workforce and financial planning. The document outlines various demand forecasting techniques including consumer and opinion polls, market experiments, and analytical methods.
Demand forecasting: Techniques
Demand forecasting is predicting future demand for the product. In other words, it refers to the prediction of a future demand for a product or a service on the basis of the past events and prevailing trends in the present.
Process of Forecasting, Techniques of forecasting,
- Prof. (Dr.) Sachin Paurush
Qualitative Demand Forecasting.pptx
This document discusses qualitative methods for forecasting demand for fast-moving consumer goods (FMCG). It describes qualitative forecasting methods like the Delphi method, market surveys, and executive opinions that do not use math. These methods gather opinions from experts, customers, salespeople, and executives. The document provides examples of FMCG companies that use qualitative methods and presents a case study of a fashion retailer that improved demand forecasting, inventory management, and customer satisfaction by combining qualitative and quantitative forecasting.
Market analysis and selling
Market Analysis - Meaning, Dimensions of a Market, Sales Forecasting - Meaning, Short Term Forecasts, Medium Term Forecast, Long Term Forecast, Importance of Sales Forecasting, Methods of Sales Forecasting - Qualitative
Techniques, Expert Opinion, Delphi Technique, Consumer
Survey, Method Sales Force, Estimate Sales Hierarchy Estimate, Quantitative Techniques, Moving Averages, Sales Ratio Method. Market Share Projection, Regression Analysis,
Sales Quota - Meaning, Types of Sales Quota, Sales Value or Financial Quota, Sales Volume Quota, Activity, Combination Quota, Factors Determining Fixation of Sales Quota, Sales Territory, Reasons - Setting up or Reviewing Sales Territories, Assigning Salesman to Territories, Use of IT in Territory Management, Reasons/Advantages of Setting Sales Territories,
Selling, Process of Selling, Methods of Closing Sales, Reasons for Unsuccessful Closing, Theories of Selling, Stimulus – Response Theory, Product Orientation Theory, Need Satisfaction Theory, Selling Skills, Conflict Management in Sales, Task Process, Process Process, Relationship Process, Functional Conflict, Dysfunctional Conflict, Methods to Resolve Conflicts. Consumer Selling v/s Organizational Selling, National Selling v/s International Selling
Planning and decision making.pptx
Planning is the process by which managers establish goals and define methods to achieve them. It involves selecting objectives and actions through decision making among alternatives. Planning is goal-oriented, looks ahead, involves choice and decision making, and is a continuous and flexible process that aims for efficiency. However, planning can also lead to rigidity and reduce creativity if not implemented properly. Strategic planning defines long-term vision and goals, while management by objectives aligns objectives across an organization. Forecasting uses past data to predict the future, and both qualitative and quantitative methods inform planning assumptions and decision making.
Forecasting
Forecasting involves estimating future demand for products and services and the resources needed to meet that demand. Forecasts are critical inputs for business planning and budgeting across finance, human resources, and operations functions. Forecasting allows organizations to better plan for short-term demand fluctuations, manage materials, make manpower decisions, and support strategic long-term decision making. Forecasts can be done at international, product, or geographic levels over short-term (1-3 months), mid-term (12-18 months), or long-term (5-10 years) horizons. Data sources for forecasts include sales force estimates, point-of-sale data, industry reports, economic indicators, and subjective expert knowledge. Both qualitative methods
Sales forcasting, budget and Cost control
This document provides an overview of sales forecasting, budgeting, and cost control. It defines each topic and outlines key factors, methods, steps, and advantages/limitations. For sales forecasting, it discusses definition, importance, factors affecting forecasts, common methods like time series analysis and regression analysis. For budgets, it defines budgetary control and outlines budget types, objectives, principles, and advantages/disadvantages. It also describes the process of budget control. Finally, it defines cost control and discusses techniques like standard costing and variance analysis to establish norms and take corrective actions.
SUPPLY CHAIN MANAGEMENT
The document provides an overview of supply chain management. It discusses key aspects of supply chain operations including planning, sourcing, production, and delivery. It also covers topics like forecasting, inventory management, purchasing, and vendor selection. The goal of supply chain management is to satisfy customer demand in a cost-effective manner through effective planning and coordination across various entities in the supply chain.
Sales forcecasting ppt
This presentation discusses sales forecasting. It defines sales forecasting as predicting future sales based on past demand information. The presentation outlines the steps in sales forecasting as defining objectives, analyzing important factors, selecting methods, collecting data, implementing decisions, and revising forecasts. Both qualitative methods like executive opinion, Delphi method, and surveys, and quantitative methods like moving averages, exponential smoothing, decomposition, and regression analysis are covered. The conclusion emphasizes that sales forecasting can increase revenue, profitability, and customer base for businesses.
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Sales presentation
- 3. SALESFORCASTING IS PREDICTING THE FUTURE SALES IN AN ORGANISATION
- 4. QUALITATIVE METHODS: Survey Method- It is based on the opinion of buyers and consumers. It is useful with respect to industrial products but not as far as consumer goods are concerned. According to this method, a company first of all selects potential buyers/consumers. It then collects their opinions for forecasting
- 5. Expert Opinion - According to this method, a company invites the opinions of executives and consultants who are acknowledged experts in studying sales trend. On the basis of their opinions, it forecasts future sales. This estimate is also made on the basis of past performance. But it doesn’t take into consideration of the future trends
- 6. Market Studies Method- This method is commonly used by marketers for consumer goods. It is also known as The Market Test Method. A market test provides data about consumers and the marketing mix. Some people use this method as a market experiment method. According to this method market experiments are conducted on changing consumer behaviour, price, advertising expenditure etc.
- 7. SalesForce Opinion Method- This method estimates the buyer’s intention from experienced personnel in the sales force. They can easily forecast for their respective territories. Territory wised forecast are consolidated at the branch level and the branch level forecast are consolidated at the corporate level. This method can be used only when the firm has competent high calibered sales personnel.
- 8. QUANTITATIVE METHODS Trend Method - This method provides a rough trend of the forecast on the basis of past experience. It does not, however, take into account the changing environment. It is a simple method for business forecasting on the basis of past performance Graphical Method- In this method the data's are plotted on a graph paper and a graph is drawn for a number of years. This is a simple and inexpensive method.
- 9. Time Series Method- The time series analysis method predicts the future sales by analyzing the historical relationship between sales and time. Although the actual number of years included in a time series analysis will vary from company to company, as a general rule, managers should include as many years as possible to ensure that important sales trends do not get undetected. They are divided into 2. Free hold or graphical method 3. Semi-Average Method 4. Moving Average Method 5. Least Square Method(sales/years)
- 10. Through sales forecasting the companies can make their sales people better forecasters, by training them to better interpret their interactions with the customers.