CHAPTER ONE

INTRODUCTION

1.1 BACKGROUND OF THE STUDY

Over the last several decades there has been much speculation about the role of computers in management. Predictions that computers would take over many management functions encouraged counter claims that computers could have only minimal impact since most management functions cannot be automated. The experience to date has fallen between the two extremes. Although very few management functions have been automated, advances in information retrieval, processing, and display technologies have certainly led to significant computer applications that help people perform management functions. Ever since, Management Information System replaced Electronic data process system as the popular term denoting computer applications in business, computer aided decision making in organizations has been the object of high hopes. Although the computer industry has enjoyed remarkable success in transforming the way business transactions and data are processed. MIS and management science professionals have been disappointed by the relatively limited use of these systems for managerial decision making. In these circumstances decision support systems emerged as new, practical approach for applying computers and information to the decision problems faced by management.

Decision support systems (DSS) represent a point of view on the role of the computers in the management decision making process. Decision support implies the use of computers to [Alter, Steven, 2000] Assist managers in their decision processes in semi-structured and unstructured tasks, Support, rather than replace, managerial judgment, Improve the effectiveness of decision-making rather than its efficiency. The second term in phrase is support. A DSS supports and does not replace the manager. This emphasis on enhancement of decision making exploits those aspects of computers and analytical techniques that are appropriate for the problem and leaves the remainder to the manager. Many problems have components that can be structured and others that require subjective assessments. In pricing some consumer products, for example, management intuition alone is inadequate, a computer model alone is also inadequate, but the two together may be most effective.

Compared with effectiveness, efficiency implies a narrowing of focus in order to get a specific job done. Typically, it takes the form of minimizing time, cost, or effort to complete a given activity. Effectiveness, on the other hand implies a broadening of focus in order to find out what set of activities should be considered. It requires defining and searching a decision space to become more confident that the goal itself is relevant and appropriate,

In the aggregate, inventories affect the economy through business cycles. Individually they provide the means by which we can effectively organize operations such as purchasing, manufacturing and distribution so that ultimately the end user receives any desired level of service. At the level of the firm, inventory is among the largest investment made and therefore logically deserves to be treated as a major policy variable highly responsive to the plans and style of top management. In general the larger the inventory the easier it is to plan operations and work force levels, the easier it is to reduce costs of purchasing, manufacturing and shipping, the easier it is to provide prompt customer service (Aggarwal, S., 2011). At the same time, a larger inventory also requires a larger investment of money and has associated with higher costs such as storage, handling, risk of obsolescence and data processing. The management tries to balance these latter costs against the advantages achieved from stocking larger amounts in inventory As such solving an inventory model is a structured problem. But some features like policy analysis, analyzing alternate models, coordinating multiple items etc,, make the inventory system design semi- structured. So the analytical power and computational ability of the computer can be rightly combined with the intervention of the management to formulate a decision support system.

1.2 STATEMENT OF THE PROBLEM

Developments in information technology (IT) over the past two decades have enabled many organizations to establish computer-based information management system (MIS) to improve inventory management. Most of these systems are mainly used to record transactions, produce management reports, and monitor inventory status. They lack the ability to help inventory managers to choose the correct model by analyzing the data kept by the system to identify the inventory environment. To maintain optimal inventory operations in a company, the management will have to continuously review and update the accumulated data, the selection of suitable models and the computation of new optimum values of ordering decisions. This is needed because the conditions in relation to the demand, the cost elements, the supply, the lead time, etc., are likely to change with time. The complexity of such a problem will greatly increase as a result of a large number of stock items in the inventory.

Pepsi bottling company for instance stock thousands of items which results in a very large number of records being generated. The analysis of such huge amounts of information is beyond manual human capacity or traditional computational methods. For a company to be more competitive, it has to face the challenge of reducing the processing costs. This issue is closely related to the effectiveness of inventory management which can help to reduce both the storage and the labour operating expenses. A small percentage reduction in inventory can be transformed into significant operating profit.

1.3 OBJECTIVE OF THE STUDY

The main objective of the decision support system for inventory management is to provide advice to inventory managers to achieve an efficient and effective inventory management practice. To achieve the stated objective, the following specific objectives were laid out:

i. Provide a system which provides a graphical presentation of sales and stock over a period of time to aid in decision making.

ii. To reveal the pattern of individual stock purchase and sale and identify the vital or critical information regarding the stock

iii. Develop a system which helps the management in planning, monitoring, and optimizing resources to ascertain their financial position at any time.

iv. The system should be able to forecast based on some present information the model to use in stocking the system.

v. To provide higher level authentication mechanism to prevent unauthorized access.

1.4 SCOPE OF THE STUDY

The research focuses on deriving a smart solution system, also referred to as decision support system, to help lower high inventory costs due to lack of forecasting, analysis and control in Pepsi bottling company. The proposed system employs three different methods which take in to account the major issues of price and quantity of items being replenished and maintained. The system works by using real data from already-established computerized inventory database. The proposed system is designed to extract data from inventory database of the co-operating companies, analyze the data to specify the demand patterns and lead time distributions. It uses this information to select an appropriate inventory model for that particular environment, calculate the optimal order quantity, update the inventory status of the item, and present output to the user in both numerical and graphical format.

1.5 SIGNIFICANCE OF THE STUDY

This thesis will be of utmost importance to mangers that use inventory support system as it helps to lower high inventory costs due to lack of forecasting, analysis and control in regular inventory management system. The proposed system employs three different methods which take in to account the major issues of price and quantity of items being replenished and maintained. Therefore, the developed system significantly reduces inventory costs and help maintaining an optimal level of merchandizing inventory.

Also the result of this study will be of importance to scholars researching the field of automatic health management as it will serve as a reference to them. As a reference material, it could generate other researchers’ interests in the unfinished part of this research, especially in the full implementation and deployment of the system.

1.6 LIMITATION OF THE STUDY

Most constraint experienced during the course of writing this project is during the actual software development. PHP algorithm needed to provide accurate decision pattern for manages to follow were difficult to obtain. This made me go for the available but less preferred codes for the implementation. Although the project intended objectives were met, better codes would give a strong and faster system.

Also detailed information about the major operations of my case study was difficult to obtain, the personnel manager was a little diplomatic in answering my questions in order to reveal information that may indent the company’s image, though that did not stop me from writing and researching for detailed information.

1.7 PROJECT ORGANISATION

This study is developed under five chapters. The first chapter introduces the research topic, stating the background of the intended project, statement of the problems, project objectives, its significance to the society and overall scope.

The second chapter reviews related literature on decision support system and their usage in inventory management. It analyses previous research works, their limitations and need for the development of better decision system for experts.

The third chapter discusses the methodology used for the project development, the limitations of the currently used detection system and reasons the intended system should be chosen over the current system. It also showcases the design processes of the new system.