Design And Implementation Of Sales Forecasting System
The design and implementation of a Sales Forecasting System encompass the strategic development and practical execution of a tool that leverages historical data and analytical techniques to predict future sales trends. This sophisticated system integrates various elements, including data analytics, machine learning algorithms, and predictive modeling, to analyze patterns, identify correlations, and make accurate predictions regarding future sales performance. The system involves the meticulous curation of sales data, incorporating factors such as seasonal variations, market demand, and historical sales figures. Through the seamless integration of these components, the Sales Forecasting System provides businesses with actionable insights, enabling them to make informed decisions, optimize inventory management, and enhance overall operational efficiency. This comprehensive approach to sales forecasting contributes to improved business planning and facilitates a proactive response to market dynamics, fostering sustainable growth and competitiveness.
TABLE OF CONTENT
Certification
Dedication
Acknowledgement
Abstract
Table of content
CHAPTER ONE: GENERAL INTRODUCTION
- Introduction
- Aims and objectives
- Significant of the study
- Research methodology
- Scope of the study
- Organization of the report
- Definition of terms
CHAPTER TWO: LITERATURE REVIEW
2.1 Review of past works
2.2 Overview of sales forecasting
2.3 Direct extrapolation of sales
2.4 Casual approaches to sales methodology
2.5 Choosing the right forecasting methodology
CHAPTER THREE
3.1 Method of data collection
3.2 Analysis of existing system
3.3 Problem of existing system
3.4 Proposed of system specification
3.5 Advantages of the proposed system
3.6 Design and implementation methodologies
CHAPTER FOUR: DESIGN, IMPLEMENTATION AND DOCUMENTATION OF THE SYSTEM
4.1 Design of the system
4.1.1 Output design
4.1.2 Input design
4.1.3 File design
4.1.4 Procedure design
4.2 Implementation of the systems
4.2.1 Hardware support
4.2.2 Software support
4.3 Documentation of the system
4.3.1 Program documentation
4.3.2. Operating the system
4.3.3 Maintaining the system
CHAPTER FIVE: SUMMARY, CONCLUSION AND RECOMMENDATION
5.1 Summary
5.2 Experienced gained
5.3 Conclusion
5.4 Recommendation
References
Appendix
- System flowchart
- Program Flowchart
- Source listing
- Computer output
CHAPTER ONE
1.0 INTRODUCTION
1.1 GENERAL INTRODUCTION
Forecasting is the process of making predictions of the future based on past and present data and analysis of trends. Sales forecasting is the ability to forecast future sales base on past months sales. Sales forecasting system uses several proven models such as qualitative versus quantitative model, average approach model, casual /econometrics forecasting model, linear regression model etc., these model are proven models use over the years by different financial institutes.
Chapter one introduces the research work and the problem definition of the research, and to know the aim of this research work, research justification tells us why it is important to research on this topic; it also covers areas like scope and limitation of study which entails the boundary of this work. Definition of terms gives summarize what each chapter entails.
1.2 PROBLEM DEFINITION
This research work was undertaken to uncover some of the problems with conventional sales forecasting management systems. Where accountant has to calculate using a specific sales model formula in forecasting on a regular basis. Using these conventional method pose lots of constraint on sales forecasting as it takes lots of time forecasting using which ever model is adopted by the sales manager or accountant or financial adviser.
1.3 SIGNIFICANT OF THE STUDY
- Produce intelligent sales forecasts, more quickly, more effectively and with one of the tedious manual processes associated with using spreadsheets for the forecasting of demand.
- Rapid Implementation: The application can be implemented very quickly. Data can be sourced from any ODBC/OLEDB data source or from flat files.
- Forecast revenue and profit as well as quantities: The computer based sales forecasters allow forecasts to be made not just for volume, but also for selling prices, cost of goods etc.
- A versatile software tools: Empower your forecasters to productively forecast, plan and re-plan sales, prepare budgets, monitor, monitor, review and report, all within a single, easy to use system.
1.4 AIM AND OBJECTIVES
Sales forecasting is the prediction of future sales performance based on previous sales history, upcoming events, statistical analysis or anything else that may influence sales. The project is aimed at developing a computer based application that plan purchasing and inventory system of a company. Sales forecasting is an important tool used by many business to fulfill several objectives.
- To develop software that serves as the basis of marketing or sales planning.
- To design a system that helps in financial planning and reporting or budgeting.
1.5 SCOPE OF THE STUDY
What is required is a system that support judgment forecasting, which takes the drudge out of retrieving and analyzing data, and which allows sales marketing managers, finance managers and general manager to work cooperatively on their components of the forecasting, planning and review process, within a common, shared but secure systems environment.
1.6 ORGANIZATION OF THE REPORT
Chapter one contains the general introduction which is the chapter that sheds a clear light on what the project is all about. It also contains state of the problems, significant of the study, objectives of the project as well as the scope of the study.
1.7 DEFINITION OF TERMS
Amiss: Is inappropriate or out of place.
Contingency: Is a future event or circumstance which is possible but cannot be predicted with certainty.
Chronological: A record of events following the order in which they occurred.
Linear Regression: Is a statistical analysis that shows the relationship between two variables.
Methodology: Is a system of methods used in a particular area of study.
Minimize: Is to reduce something to the least possible amount.
Maximize: Is to increase to the greatest possible amount or degree.
Minimum: Is the lowest known or lowest possible number, quantity or degree.
Optimistic: Is hopeful and confident about the future.
Product: Is anything that can be offered to a market that might satisfy a want or need. In retailing, products are called merchandise. In manufacturing, products are bought as raw materials and sold as finished goods.
Prediction: Is a statement about an uncertain event.
Pragmatism: Is a philosophical movement that includes those who claim that an ideology or proposition is true if it works satisfactorily, that the meaning of a proposition is to be found in the practical consequences of accepting it and that unpractical ideas are to be rejected.
Quantitative: It refers to a type of information based in quantities or else quantifiable data (objective properties) as opposed to qualitative information which deals with apparent qualities (subjective properties).
Sales: – Is the act of taking goods or service which has value and contributes to the utility of individual to the market.
Variable: It is a characteristic, number or quantity that increases or decreases over time, or takes different values in different situations.
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