Tag: Corporate Restructuring Mumbai University BMS Notes

The Law of equi-marginal Utility is another fundamental principle of Econo­mics. This law is also known as the Law of substitution or the Law of Maxi­mum Satisfaction. We know that human wants are unlimited whereas the means to satisfy these wants are strictly limited. It, therefore’ becomes necessary to pick up the most urgent wants that can be satisfied with the money that a consumer has. Of the things that he decides to buy he must buy just the right quantity. Every prudent consumer will try to make the best use of the money at his disposal and derive the maximum satisfaction.

Explanation of the Law

In order to get maximum satisfaction out of the funds we have, we carefully weigh the satisfaction obtained from each rupee ‘had we spend If we find that a rupee spent in one direction has greater utility than in another, we shall go on spending money on the former commodity, till the satisfaction derived from the last rupee spent in the two cases is equal.

It other words, we substitute some units of the commodity of greater utility tor some units of the commodity of less utility. The result of this substitution will be that the marginal utility of the former will fall and that of the latter will rise, till the two marginal utilities are equalized. That is why the law is also called the Law of Substitution or the Law of equimarginal Utility.

Suppose apples and oranges are the two commodities to be purchased. Suppose further that we have got seven rupees to spend. Let us spend three rupees on oranges and four rupees on apples. What is the result? The utility of the 3rd unit of oranges is 6 and that of the 4th unit of apples is 2. As the marginal utility of oranges is higher, we should buy more of oranges and less of apples. Let us substitute one orange for one apple so that we buy four oranges and three apples.

Now the marginal utility of both oranges and apples is the same, i.e., 4. This arrangement yields maximum satisfaction. The total utility of 4 oranges would be 10 + 8 + 6 + 4 = 28 and of three apples 8 + 6 + 4= 18 which gives us a total utility of 46. The satisfaction given by 4 oranges and 3 apples at one rupee each is greater than could be obtained by any other combination of apples and oranges. In no other case does this utility amount to 46. We may take some other combinations and see.

We thus come to the conclusion that we obtain maximum satisfaction when we equalize marginal utilities by substituting some units of the more useful for the less useful commodity. We can illustrate this principle with the help of a diagram.

Diagrammatic Representation:

In the two figures given below, OX and OY are the two axes. On X-axis OX are represented the units of money and on the Y-axis marginal utilities. Suppose a person has 7 rupees to spend on apples and oranges whose diminishing marginal utilities are shown by the two curves AP and OR respectively.

The consumer will gain maximum satisfaction if he spends OM money (3 rupees) on apples and OM’ money (4 rupees) on oranges because in this situation the marginal utilities of the two are equal (PM = P’M’). Any other combination will give less total satisfaction.

Let the purchase spend MN money (one rupee) more on apples and the same amount of money, N’M'( = MN) less on oranges. The diagram shows a loss of utility represented by the shaded area LN’M’P’ and a gain of PMNE utility. As MN = N’M’ and PM=P’M’, it is proved that the area LN’M’P’ (loss of utility from reduced consumption of oranges) is bigger than PMNE (gain of utility from increased consumption of apples). Hence the total utility of this new combination is less.

We then, conclude that no other combination of apples and oranges gives as great a satisfaction to the consumer as when PM = P’M’, i.e., where the marginal utilities of apples and oranges purchased are equal, with given amour, of money at our disposal.

Limitations of the Law of Equimarginal Utility

Like other economic laws, the law of equimarginal utility too has certain limitations or exceptions. The following are the main exception.

(i) Ignorance

If the consumer is ignorant or blindly follows custom or fashion, he will make a wrong use of money. On account of his ignorance he may not know where the utility is greater and where less. Thus, ignorance may prevent him from making a rational use of money. Hence, his satisfaction may not be the maximum, because the marginal utilities from his expenditure can­not be equalised due to ignorance.

(ii) Inefficient Organisation

In the same manner, an incompetent organ­iser of business will fail to achieve the best results from the units of land, labour and capital that he employs. This is so because he may not be able to divert expenditure to more profitable channels from the less profitable ones.

(iii) Unlimited Resources

The law has obviously no place where this resources are unlimited, as for example, is the case with the free gifts of nature. In such cases, there is no need of diverting expenditure from one direction to another.

(iv) Hold of Custom and Fashion

A consumer may be in the strong clutches of custom, or is inclined to be a slave of fashion. In that case, he will not be able to derive maximum satisfaction out of his expenditure, because he cannot give up the consumption of such commodities. This is specially true of the conventional necessaries like dress or when a man is addicted to some into­xicant.

(v) Frequent Changes in Prices

Frequent changes in prices of different goods render the observance of the law very difficult. The consumer may not be able to make the necessary adjustments in his expenditure in a constantly changing price situation.

Consumer Surplus is the difference between the price that consumers pay and the price that they are willing to pay. On a supply and demand curve, it is the area between the equilibrium price and the demand curve

For example, if you would pay 76p for a cup of tea, but can buy it for 50p; your consumer surplus is 26p

Diagram of Consumer Surplus

Producer Surplus

• This is the difference between the price a firm receives and the price it would be willing to sell it at.
• Therefore it is the difference between the supply curve and the market price.

Consumer Surplus and Marginal Utility

The demand curve is derived from our marginal utility. If the marginal utility of a good is greater than the price, then that is our consumer surplus.

1. Firms can reduce consumer surplus if they have market power. This enables them to raise prices above the competitive equilibrium.
2. In a monopoly, a firm will maximise profits by reducing consumer surplus.
3. Another way to reduce consumer surplus is to engage in price discrimination. Charging different prices to different groups of consumers. Those with inelastic demand will see their consumer surplus reduced. More on Price discrimination. To completely eliminate consumer surplus, a firm would need to engage in first-degree price discrimination this means charging the consumer the highest price they are willing to pay.
4. To gain market power, a firm could advertise to create brand loyalty, this will make demand more inelastic

Significance of consumer surplus

• In competitive markets, firms have to keep prices relatively low, enabling consumers to gain consumer surplus. If markets were not competitive, the consumer surplus would be less and there would be greater inequality.
• A lower consumer surplus leads to higher producer surplus and greater inequality.
• Consumer surplus enables consumers to purchase a wider choice of goods.

Decision Support system (DSS) is a computerized program used to support determinations, judgments, and courses of action in an organization or a business. A DSS sifts through and analyzes massive amounts of data, compiling comprehensive information that can be used to solve problems and in decision-making.

Typical information used by a DSS includes target or projected revenue, sales figures or past ones from different time periods, and other inventory- or operations-related data.

A DSS can be used by operations management and planning levels in an organization to compile information and data and synthesize it into actionable intelligence. This allows the end user to make more informed decisions at a quicker pace.

The DSS is an information application that produces comprehensive information. This is different from an operations application, which would be used to collect the data in the first place. A DSS is primarily used by mid- to upper-level management, and it is key for understanding large amounts of data.

For example, a DSS could be used to project a company’s revenue over the upcoming six months based on new assumptions about product sales. Due to the large amount of variables that surround the projected revenue figures, this is not a straightforward calculation that can be done by hand. A DSS can integrate multiple variables and generate an outcome and alternate outcomes, all based on the company’s past product sales data and current variables.

The primary purpose of using a DSS is to present information to the customer in a way that is easy to understand. A DSS system is beneficial because it can be programed to generate many types of reports, all based on user specifications. A DSS can generate information and output it graphically, such as a bar chart that represents projected revenue, or as a written report.

As technology continues to advance, data analysis is no longer limited to large bulky mainframes. Since a DSS is essentially an application, it can be loaded on most computer systems, including laptops. Certain DSS applications are also available through mobile devices. The flexibility of the DSS is extremely beneficial for customers who travel frequently. This gives them the opportunity to be well-informed at all times, which in turn provides them with the ability to make the best decisions for their company and customers at any time.

Process of Decision Support Systems (DSS):

1. Data Input:

Gathering relevant data from various sources, both internal and external.

2. Data Processing:

Analyzing and processing data using models, algorithms, and analytical tools.

3. Knowledge Base:

Utilizing a knowledge base to store relevant information, rules, and decision criteria.

4. User Interface:

Providing a user-friendly interface for querying and interacting with the system.

5. Model Execution:

Executing models and simulations to generate insights and scenarios.

6. Results Presentation:

Presenting results through reports, dashboards, and visualizations.

7. User Feedback:

Gathering feedback from users to improve system performance.

Attributes of a DSS

• Adaptability and flexibility
• High level of Interactivity
• Ease of use
• Efficiency and effectiveness
• Complete control by decision-makers
• Ease of development
• Extendibility
• Support for modeling and analysis
• Support for data access
• Standalone, integrated, and Web-based

Characteristics of a DSS

• Support for decision-makers in semi-structured and unstructured problems.
• Support for managers at various managerial levels, ranging from top executive to line managers.
• Support for individuals and groups. Less structured problems often requires the involvement of several individuals from different departments and organization level.
• Support for interdependent or sequential decisions.
• Support for intelligence, design, choice, and implementation.
• Support for variety of decision processes and styles.
• DSSs are adaptive over time.

Benefits of DSS

• Improves efficiency and speed of decision-making activities.
• Increases the control, competitiveness and capability of futuristic decision-making of the organization.
• Facilitates interpersonal communication.
• Encourages learning or training.
• Since it is mostly used in non-programmed decisions, it reveals new approaches and sets up new evidences for an unusual decision.
• Helps automate managerial processes.

Disadvantages of Decision Support Systems:

• Complex Implementation:

Implementing DSS may require specialized skills and technical expertise.

• High Initial Costs:

The initial investment in DSS development and implementation can be substantial.

• Dependency on Data Quality:

DSS effectiveness heavily relies on the quality and accuracy of input data.

• Resistance to Change:

Users may resist adopting new decision-making processes facilitated by DSS.

• Security Concerns:

DSS may handle sensitive information, raising security and privacy issues.

• Overemphasis on Technology:

Overreliance on technology may overlook the human element in decision-making.

• Limited Flexibility:

Some DSS may lack flexibility to adapt to rapidly changing business environments.

• Integration Challenges:

Integrating DSS with existing systems may pose compatibility and integration challenges.

• Learning Curve:

Users may face a learning curve when adopting new DSS tools and interfaces.

• Maintenance Requirements:

Regular maintenance and updates are necessary to keep DSS effective and up-to-date.

Components of a DSS

(i) Database Management System (DBMS)

To solve a problem the necessary data may come from internal or external database. In an organization, internal data are generated by a system such as TPS and MIS. External data come from a variety of sources such as newspapers, online data services, databases (financial, marketing, human resources).

(ii) Model Management System

It stores and accesses models that managers use to make decisions. Such models are used for designing manufacturing facility, analyzing the financial health of an organization, forecasting demand of a product or service, etc.

(iii) Support Tools

Support tools like online help; pulls down menus, user interfaces, graphical analysis, error correction mechanism, facilitates the user interactions with the system.

Classification of DSS

There are several ways to classify DSS. Hoi Apple and Whinstone classifies DSS as follows:

(i) Text Oriented DSS

It contains textually represented information that could have a bearing on decision. It allows documents to be electronically created, revised and viewed as needed.

(ii) Database Oriented DSS

Database plays a major role here; it contains organized and highly structured data.

(iii) Spreadsheet Oriented DSS

It contains information in spread sheets that allows create, view, modify procedural knowledge and also instructs the system to execute self-contained instructions. The most popular tool is Excel and Lotus 1-2-3.

(iv) Solver Oriented DSS

It is based on a solver, which is an algorithm or procedure written for performing certain calculations and particular program type.

(v) Rules Oriented DSS

It follows certain procedures adopted as rules.

(vi) Rules Oriented DSS

Procedures are adopted in rules oriented DSS. Export system is the example.

(vii) Compound DSS

It is built by using two or more of the five structures explained above.

Types of DSS

(i) Status Inquiry System

It helps in taking operational, management level, or middle level management decisions, for example daily schedules of jobs to machines or machines to operators.

(ii) Data Analysis System

It needs comparative analysis and makes use of formula or an algorithm, for example cash flow analysis, inventory analysis etc.

(iii) Information Analysis System

In this system data is analyzed and the information report is generated. For example, sales analysis, accounts receivable systems, market analysis etc.

(iv) Accounting System

It keeps track of accounting and finance related information, for example, final account, accounts receivables, accounts payables, etc. that keep track of the major aspects of the business.

(v) Model Based System

Simulation models or optimization models used for decision-making are used infrequently and creates general guidelines for operation or management.

Decision Support Systems Role in Decision making process

1. Data Aggregation and Analysis:

   • Role of DSS:
     • Gathers and aggregates relevant data from various sources.
     • Analyzes data using advanced modeling and analytical techniques.
   • Impact on Decision Making:
     • Provides decision-makers with a comprehensive view of relevant information.
     • Enables in-depth analysis for better-informed decisions.

2. Scenario Simulation:

   • Role of DSS:
     • Allows for the creation and simulation of different decision scenarios.
     • Models the potential outcomes of various decision options.
   • Impact on Decision Making:
     • Assists decision-makers in understanding the consequences of different choices.
     • Supports proactive decision-making by exploring potential scenarios.

3. Decision Modeling and Optimization:

   • Role of DSS:
     • Utilizes mathematical models to represent decision problems.
     • Optimizes decision variables to achieve the best outcomes.
   • Impact on Decision Making:
     • Provides decision-makers with quantifiable and objective insights.
     • Optimizes resource allocation and decision parameters.

4. Access to Real-Time Information:

   • Role of DSS:
     • Integrates with systems to provide real-time data updates.
     • Ensures decision-makers have access to the latest information.
   • Impact on Decision Making:
     • Enables timely decision-making based on current and relevant data.
     • Supports agility and responsiveness in dynamic business environments.

5. User-Friendly Interfaces:

   • Role of DSS:
     • Provides intuitive and user-friendly interfaces for interaction.
     • Allows users to easily input queries and interact with the system.
   • Impact on Decision Making:
     • Reduces the learning curve for users, fostering widespread adoption.
     • Enhances accessibility for decision-makers across different levels.

6. Collaboration Support:

   • Role of DSS:
     • Facilitates collaboration by allowing multiple users to interact with the system.
     • Supports shared decision-making processes.
   • Impact on Decision Making:
     • Encourages teamwork and collective decision-making.
     • Improves communication and coordination among decision-makers.

7. Information Presentation:

   • Role of DSS:
     • Presents insights through visualizations, reports, and dashboards.
     • Transforms complex data into easily understandable formats.
   • Impact on Decision Making:
     • Enhances comprehension by presenting information in a digestible manner.
     • Supports quick and effective decision-making.

8. Risk Assessment and Mitigation:

   • Role of DSS:
     • Assesses potential risks associated with decision options.
     • Recommends strategies to mitigate identified risks.
   • Impact on Decision Making:
     • Helps decision-makers make informed choices while considering potential risks.
     • Supports the development of risk-conscious decision-making strategies.

9. Feedback Mechanism:

   • Role of DSS:
     • Establishes a feedback loop for continuous improvement.
     • Collects feedback from users to enhance system performance.
   • Impact on Decision Making:
     • Enables continuous learning and improvement in decision-making processes.
     • Incorporates user insights for refining decision support functionalities.

An Executive Information System can be defined as a specialized Decision Support System. This type of the system generally includes the various hardware, software, data, procedures and the people. With the help of all this, the top level executives get a great support in taking and performing the various types of the decisions. The executive information system plays a very important role in obtaining the data from the different sources, then help in the integration and the aggregation of this data. After performing these steps the resulting information is displayed in such a pattern that is very easy to understand.

Executive information system is ‘a computer based system that serves the information that is needed by the various top executives. It provides very rapid access to the timely information and also offers the direct access to the different management reports.’

Executive Information System is very user friendly in the nature. It is supported at a large extent by the graphics.

Executive support system can be defined as the comprehensive executive support system that goes beyond the Executive Information System and also includes communications, office automation, analysis support etc.

According to Watson, Executive Information System / executive support system depends on some of the factors that can be summarized as the follows

1. Internal factors

• Need for the timely information.
• Need for the improved communications.
• Need for the access to the operational data.
• Need for the rapid status updates on the various business activities.
• Need for the access to the corporate database.
• Need for very accurate information.
• Need for the ability to identify the various historical trends.

2. External Factors

• Increasing and intensifying the global competition.
• Rapidly changing the business environment.
• Need to be more proactive.
• Need to access the external database.
• Increasing the various government regulations.

Characteristics of the Executive Information System

1. Informational characteristics

• Flexibility and ease of use
• Provides the timely information with the short response time and also with the quick retrieval
• Produces the correct information
• Produces the relevant information
• Produces the validated information

2. User interface/orientation characteristics

• Consists of the sophisticated self help
• Contains the user friendly interfaces consisting of the graphic user
• Can be used from many places
• Offers secure reliable, confidential access along with the access procedure
• Is very much customized
• Suites the management style of the individual executives

3. Managerial / executive characteristics

• Supports the over all vision, mission and the strategy
• Provides the support for the strategic management
• Sometimes helps to deal with the situations that have a high degree of risk
• Is linked to the value added business processes
• Supports the need/ access for/ to the external data/ databases
• Is very much result oriented in the nature

Capabilities of Executive Information System

(i) Helps in accessing the aggregated or macro or global information.

(ii) Provides the user with an option to use the external data extensively.

(iii) Enables analysis of the address and the hoc queries.

(iv) Shows the trends, the ratios and the various deviations.

(v) Helps in incorporating the graphic and the text in the same display, which helps to have a better view.

(vi) It helps in the assessment of the historical as also the latest data.

(vii) Problem indicators can be highlighted with the help of the Executive Information System / executive support system.

(viii) Open ended problem explanation with the written interpretations can be done with the help of the Executive Information System / executive support system.

(ix) Offers management by the exception reports.

(x) Utilizes the hyper text and the hyper media.

(xi) Offers generalized computing.

(xii) Offers telecommunications capacity.

Executive Information System Process

• Data Collection:

EIS gathers data from various internal and external sources, including databases, reports, and external data feeds.

• Data Processing:

The collected data undergoes processing, including validation, aggregation, and transformation to ensure accuracy and relevance.

• Data Storage:

Processed data is stored in a centralized repository, often a data warehouse, for easy retrieval and analysis.

• Information Retrieval:

Executives can query the EIS to retrieve specific information based on their needs. The system uses user-friendly interfaces for ease of interaction.

• Data Analysis and Reporting:

EIS provides tools for data analysis, generating reports, summaries, and visualizations that offer insights into key performance indicators (KPIs) and relevant metrics.

• Trend Identification:

The system identifies trends and patterns within the data, allowing executives to understand historical performance and anticipate future developments.

• Decision Support:

EIS assists executives in decision-making by providing relevant and timely information. It may include decision support tools and models for scenario analysis.

• Alerts and Notifications:

EIS monitors predefined thresholds and conditions, triggering alerts or notifications to executives when significant events or deviations occur.

• Strategic Planning Support:

EIS contributes to strategic planning by offering insights into market trends, competitive intelligence, and the organization’s overall performance.

• Integration with External Data:

EIS often integrates with external data sources, such as industry reports, economic indicators, and market research, to provide a comprehensive view.

• Customization for Executives:

EIS is customizable to meet the specific needs and preferences of individual executives, allowing them to focus on the information most relevant to their roles.

• User Interface and Accessibility:

EIS features user-friendly interfaces that provide easy access to information, ensuring that executives can quickly navigate and retrieve the data they require.

• Feedback Mechanism:

Executives can provide feedback on the usefulness and relevance of the information provided, contributing to system refinement and improvement.

• Security Measures:

EIS incorporates robust security measures to safeguard sensitive executive-level information and ensure data confidentiality.

Benefits of Executive Information System

(i) Achievement of the various organizational objectives.

(ii) Facilitates access to the information by integrating many sources of the data.

(iii) Facilitates broad, aggregated perspective and the context.

(iv) Offers broad highly aggregated information.

(v) User’s productivity is also improved to a large extent.

(vi) Communication capability and the quality are increased.

(vii) Provides with the better strategic planning and the control.

(viii) Facilitates pro-active rather than a reactive response.

(ix) Provides the competitive advantage.

(x) Encourages the development of a more open and active information culture.

(xi) The cause of a particular problem can be founded.

Executive Information System Disadvantages

• Costly Implementation:

The initial investment in designing, implementing, and maintaining an EIS can be substantial, including costs for hardware, software, training, and ongoing support.

• Complexity and Customization:

EIS can be complex to implement, and customization to fit specific executive needs may require a high level of expertise and effort.

• Dependency on Data Quality:

The effectiveness of EIS is highly dependent on the quality of the underlying data. Inaccurate or incomplete data can lead to flawed insights and decisions.

• Integration Challenges:

Integrating EIS with existing information systems within the organization can be challenging, especially in environments with diverse data sources and formats.

• Resistance to Change:

Executives and organizational members may resist adapting to new technologies and processes, potentially hindering the successful adoption of EIS.

• Security Concerns:

EIS often deals with sensitive and confidential information. Ensuring robust security measures is crucial to prevent unauthorized access and protect against data breaches.

• Learning Curve:

Executives and users may face a learning curve when using new EIS tools and interfaces, which can temporarily impact productivity.

• Overemphasis on Technology:

Overreliance on EIS may lead to a reduction in the importance of human intuition and experience in decision-making, potentially overlooking nuanced aspects.

• Limited Flexibility:

Some EIS solutions may lack flexibility to adapt quickly to changes in business environments or evolving executive information needs.

• Maintenance Requirements:

Ongoing maintenance is essential for EIS to remain effective. This includes updates, troubleshooting, and ensuring compatibility with evolving technologies.

• Data Overload:

EIS, when presenting a large volume of information, may lead to information overload for executives, making it challenging to focus on critical data points.

• Potential for Misinterpretation:

Executives may misinterpret presented information, especially if they lack a comprehensive understanding of the data sources, models, or assumptions used.

• Dependency on IT Support:

Executives may become overly dependent on IT support for system-related issues, potentially slowing down decision-making in case of technical problems.

• Ethical Considerations:

The use of EIS raises ethical concerns related to the privacy and responsible use of sensitive information, requiring organizations to establish clear guidelines and policies.

Executive Information System Role in Decision making process

• Access to Critical Information:

EIS provides top executives with quick and easy access to critical information relevant to their roles. This information includes key performance indicators (KPIs), financial metrics, market trends, and strategic data.

• Real-Time Data Monitoring:

Executives can monitor real-time data through EIS, allowing them to stay informed about the current state of the organization and external factors that may impact decision-making.

• Strategic Planning Support:

EIS assists in strategic planning by offering insights into long-term trends, market dynamics, and competitive intelligence. Executives can align organizational goals with available resources and external opportunities.

• Decision Support Tools:

EIS incorporates decision support tools such as data analytics, modeling, and scenario analysis. These tools help executives evaluate various decision options and their potential outcomes.

• Performance Measurement:

Executives can use EIS to measure the performance of different departments, business units, or projects, enabling data-driven assessments and informed decision-making.

• Risk Management:

EIS supports risk management by identifying potential risks and uncertainties. Executives can use this information to develop strategies for mitigating risks and making more informed decisions.

• Facilitation of Communication:

EIS facilitates communication among top executives by providing a centralized platform for sharing information, insights, and collaborative decision-making.

• Aggregation of Information:

EIS aggregates information from diverse sources, including internal databases, external market reports, and operational systems. This aggregation provides a comprehensive view for decision-makers.

• Customization for Executives:

EIS allows executives to customize dashboards and reports based on their specific information needs. This ensures that executives focus on the most relevant data for their decision-making processes.

• Performance Evaluation:

Executives can use EIS to evaluate the performance of strategic initiatives, allowing for adjustments and refinements in alignment with organizational goals.

• Alerts and Notifications:

EIS includes alert mechanisms that notify executives of critical events or deviations from established benchmarks, enabling proactive decision-making.

• Benchmarking:

Executives can compare the organization’s performance against industry benchmarks and competitors, aiding in strategic positioning and goal setting.

• Data Visualization:

EIS employs data visualization techniques such as charts and graphs to present complex information in a visually comprehensible format, aiding executives in understanding trends and patterns.

• Feedback Loop:

EIS establishes a feedback loop where executives can provide feedback on the effectiveness of decisions made and the relevance of information presented, contributing to continuous improvement.