Everything you need to know about the techniques of decision making. Decision-making needs to be accurate and rational to be effective.

Decision-making becomes a challenging exercise especially when decisions are complex and have implications on major stakeholders. Success of an organisation depends on corrective decision-making.

Right decisions may bring success, whereas a wrong decision may ruin an organisation. For the purpose of carrying out decision-making procedure, a wide variety of decision-making techniques are adopted.

The techniques of decision making can be studied under the following heads:- 1. Qualita­tive Techniques 2. Quantitative Techniques.


Some of the qualitative techniques of decision making are:-

1. Intuitive Approach 2. Delphi Technique 3. Brainstorming 4. Nominal Group Technique (NGT) 5. Multi-Voting 6. Didactic Interaction.

Some of the quantitative techniques of decision making are:-

1. Management Information Systems (MIS) 2. Decision Support System (DSS) 3. Decision Tree 4. The Delphi Technique 5. Decision Matrix 6. Cost Benefit Analysis 7. Payback Analysis 8. Simulation 9. Network Analysis 10. Operations Research.

Techniques of Decision Making: Qualitative and Quantitative Techniques

Techniques of Decision Making

There are various techniques of decision making.


They fall into two broad categories:

1. Qualita­tive, and

2. Quantitative.


1. Qualitative techniques – Intuitive approach to decision making is qualitative in nature.

2. Quantitative techniques – Such techniques include MIS, DSS, decision-tree and the Delphi method.

Intuition is an individual’s innate belief about something without conscious consider­ation.

1. Qualitative Techniques:


It is making a choice without the use of conscious thought or logical inference. It is important for a manager to develop his intuitive skills because they are as important as rational analysis in many decisions.

The Intuitive Approach to Decision Making:

When managers make decisions solely on hunches and intuition they are practising manage­ment as though it were wholly an art based only on feelings. The intuitive approach refers to the approach used when managers make decisions based largely on hunches and intuitions.

Rational Approaches to Decision Making Revisited:

Approaches to decision making that attempt to evaluate factual information through the use of some type of deductive reasoning are referred to as rational approaches.


The following points discuss two types of rational approaches:

a. The Optimising Approach:

The optimising approach (sometimes called the rational or scientific approach) to decision making includes the following steps:

i. Recognise the need for a decision.


ii. Establish, rank and weigh the decision criteria.

iii. Gather available information and data.

iv. Identify possible alternatives.

v. Evaluate each alternative with respect to all criteria.


vi. Select the best alternative.

Once the need to make the decision is known, criteria must be set for expected results of the decision. These criteria should then be ranked and weighed according to their relative importance.

Next, factual data relating to the decision should be collected. After that, all alternatives that meet the criteria are identified. Each is then evaluated with respect to all criteria. The final decision is based on the alternative that best meets the criteria.

Limitations of the Optimising Approach:

The optimising approach to decision making is no doubt an improvement over the intuitive approach. But it is not without its problems and limitations.

First, the assumptions on which the approach is based are often unrealistic; decision makers do not always have clearly defined criteria for making decisions.


Second, many decisions are based on limited knowledge of the possible alternatives; even when information is available, it is usually less than perfect.

Third, there is always a temptation to manipulate or ignore the gathered information and choose a favoured (but not necessarily the best) alternative.

Due to limitations of the optimising approach, most decisions still involve some judg­ment. Thus, in making decision, the manager generally uses a combination of intuitive and rational approaches.

b. The Satisfying (Administrative) Approach Restated:

Believing the assumptions of the optimising approach to be generally unrealistic, Herbert Si­mon, in attempting to understand how managerial decisions are actually made, formulated his principle of bounded rationality. This principle states, “The capacity of the human mind for formulating and solving complex problems is very small compared with the size of the prob­lems whose solutions is required for objectively rational behaviour — or even for a reasonable approximation to such objective rationality”. Basically, the principle of bounded rationality states that human rationality has definite limits.

Based on this principle, Simon proposed a decision model of the administrative man, which is based on following assumptions:


i. A person’s knowledge of alternatives and criteria is limited.

ii. In general people act on the basis of a simplified, ill-structured, mental abstraction of the real world; this abstraction is influenced by personal perceptions, biases, and so forth.

iii. People do not attempt to optimise but will take the first alternative that satisfies their current level of aspiration. This is called satisficing.

iv. An individual’s level of aspiration concerning a decision fluctuates upward and down­ward, depending on the values of the most recently identified alternatives.

Optimising means selecting the best possible alternative; satisficing means selecting the first alternative that meets the decision maker’s minimum standard of satisfaction. Assumption four is based on the belief that the criteria for a satisfactory alternative are determined by the person’s current level of aspiration. Level of aspiration refers to the level of performance a person expects to attain, and it is impacted (influenced) by the person’s prior successes and failures.

Fig. 2 represents the satisficing approach to decision making. If the decision maker is satisfied that an acceptable alternative has been found, she or he selects that alternative. Otherwise the decision maker searches for an additional alternative. In Fig. 2 the double arrows indicate a two-way relationship – The value of the new alternative is influenced by the value of the best previous alternative.


The value of the best previous alternative is, in turn, influenced by the value of the new alternative. As is indicated by the arrows, a similar two-way relationship exists between the value of the new alternative and the current level of aspiration. The end result of this evaluation determines whether or not the decision maker is satisfied with the alternative. Thus the decision maker (called the administrative man) selects the first alternative which meets the minimum satisfaction criteria and makes no real attempt to optimise.

2. Quantitative Techniques:

Armed with information managers can make better decisions. Frontline managers, for ex­ample, who are supplied with direct activity cost information, can better manage revenue mar­gins (profits) and costs. Organisations can achieve more consistency between upper manage­ment and lower-level managers by providing more information throughout the organisation.

The quantitative decision-making techniques are:

i. Management Information System (MIS),

ii. Decision Support System (DSS),


iii. Decision tree and

iv. Delphi technique.

i. Management Information Systems (MIS):

Management information systems (MIS) are reporting systems which summarise, collate and present information on a certain activity such as processing a transaction. An MIS is a procedure which is concerned with getting appropriate information to managers as and when they need it.

It is a comprehensive computer system for providing financial and qualitative information to all levels of management. Access to data is by the need to know and is restricted to areas regarded as useful for particular managers; confidential information is restricted to top management.

Management information systems (MIS) provide support to an organisation’s managers by providing daily reports, schedules, plans and budgets. A basic MIS is presented in Fig. 3. In­formation activities of each functional manager vary depending on whether he is in accounting department or marketing department as also the management level.

In general middle-level managers focus mainly on internal activities and information, higher- and top-level managers also remain engaged in external activities. However, middle-managers are the largest MIS user group. Since they use this technique extensively and frequently they need networked information to plan such emerging activities as employee training, materials handling and cash flows.

MIS produce reports which fall into three main categories.

First are periodic, scheduled reports. For example, an MIS may produce weekly reports regarding sales activity broken down by region.

Second, MIS produce demand reports, which are generated on request by the managers.

Finally, some MIS produce exception reports, which are generated as warn­ings based on certain business conditions. For example, an inventory system may produce an exception report to warn managers of low stock levels for a particular product line. MIS are normally highly structured since they involve highly repetitive, simple calculations with little variability in their presentation.

ii. Decision Support System (DSS):

With Internet-hosted databases and user-friendly query tools becoming more common, corporations are turning to decision support system (DSS) software to analyse the firm’s databases and turn them into information useful for decision making. DSS typically includes analytical and report-writing features, thus enabling users to translate new data into a form useful for decision support.

DSS is a computer information system which performs complex data analysis that helps users make informed decisions. It is a procedure which is concerned with getting appropriate information to managers as and when they need it and which aids two managers in making decisions.

A DSS is generally based upon interactive computer networks which can help the managers to solve problems and to gauge the effects of alternative outcomes of a decision. While some DSSs are developed to solve specific problems others serve more general purpose. This allows management to analyse different types of problems.

A DSS involves sophisticated analytical modelling to support semi-structured and unstructured decision making, mainly at the managerial level. DSSs implement mathematical and/or heuristic models to process data. They go much further than the type of information presentation done by MIS systems. They also give recommendations to the user, identify advantages and disadvantages of decision alternatives. Sometimes, these systems employ artificial intelligence techniques.

Decision support technology is a comparatively new development in software. However, DSS offers highly flexible programming paradigms. It slices and dices data that may be novel and complex into understandable chunks to facilitate shared consideration of multiple criteria. The DSS can assist in decisions for which predetermined solutions are unknown by using sophisticated models and data analysis.


(a) A DSS can result in much time savings as well as an improved decision making.

(b) DSS can speed collaboration when there are several decision makers and all of them have to be satisfied. By providing multiple users with access to the firm’s data, DSS can clarify the decision-making process and enhance consistency among multiple decision makers. With electronic commerce competitors respond to strategic decisions within days or even hours. The speed with which decisions are made becomes more critical. DSS helps decision makers consider a wider range of alternatives in a short period of time.

Now-a-days middle and top-level managers receive decision-making assistance from a Decision Support System (DSS). It is an interactive system which locates and present information needed to lend necessary support to the decision-making process.

DSS are now-a-days extensively used to support the marketing department. They use mathematical models to project the outcome of new decision, adding variables — such as -previous outcomes in similar contexts — to help marketers to make optimal decisions.

iii. Decision Tree:

Decision tree is an aid to decision-making in uncertain conditions that sets out alternative courses of action and the financial consequences of each alternative, and assigns subjective probabilities to the likelihood of future events occurring. For example, a firm or a business person thinking of opening a new factory the success of which will depend upon consumer spending (and thus the state of the economy) would have a decision tree like Fig. 4.

The business person has two options – to open a new factory to boost production capacity or not to open a new factory; and he has to consider two states of nature or events which can occur- economic boom or recession. The business person must assess the likelihood of each of these events occurring and, in the case, based on his knowledge and experience, he estimates that there is a one-in-two chance of a boom and a 0.5 probability of a recession. Finally, the business person estimates the financial consequences as a Rs. 80,000 profit for the new factory if there is a boom, and a Rs. 30,000 loss if there is a recession.

In order to make a decision, the manager needs a decision criterion to enable him to choose which he regards as the best of the alternatives and, since choices involve an element of risk, we therefore need to know something about his attitudes to risk. If the manager were neutral in his attitudes to risk then we could calculate the certainty equivalent of the ‘open factory’ alternative using the expected money value criterion, which takes the financial consequence of each outcome and weights it by the probability of its occurrence, thus –

which being greater than the Rs. 0 for certain of not opening the factory would justify going ahead with the factory project.

However, if the manager were averse to risk then he might not regard the expected money value criterion as being appropriate, for he might require a risk premium to induce him to take the risk. Application of a more cautious certainty equivalent of the ‘open factory’ branch might even tip the decision against going ahead on the grounds of the ‘downside risk’ of losing Rs. 30,000.

iv. The Delphi Technique:

The Delphi technique is an approach to generating new ideas or problem-solving amongst a group or team. Each member or interested party submits his or her recommendations or views on the issue under review to a central contact point. All ideas generated in this way are then circulated to all those participants in the process, who then have the opportunity to submit comments on them.

This process is repeated until a consensus emerges. Although time consuming, it can be an effective approach to the management of change. The reason it that it enables all interested parties to express their view, generates consensus and, by incorporating all in the decision-making process, tends to generate commitment to the final outcome.

Techniques of Decision Making – Qualitative, Quantitative and Other Techniques

Decision-making needs to be accurate and rational to be effective. Decision-making becomes a challenging exercise especially when decisions are complex and have implications on major stakeholders. Success of an organisation depends on corrective decision-making. Right decisions may bring success, whereas a wrong decision may ruin an organisation. For the purpose of carrying out decision-making procedure, a wide variety of decision-making techniques are adopted.

These techniques can be classified into two broad categories:

Technique # 1. Qualitative:

Qualitative techniques of decision-making are subjective in nature as it is based on factors other than numerical data. It is a more in-depth analysis of the factors. Qualitative decision-making is based not just on the numerical statistical data but other associated factors that may have influence on the collected data.

It is an in-depth analysis of all possible factors that can affect the decision-making process. While exercising qualitative decision-making, managers are required to have experiential knowledge of the various factors underlying a problem. Qualitative decision-making is also called group decision-making as decision is an outcome of mutual discussion.

Various qualitative decision-making techniques are:

(i) Delphi Technique:

Delphi method was developed way back in 1950s by Olaf Helmer and Norman Dalker at the RAND Corporation to forecast the impact of technology on warfare. It was incorporated to reduce the range of responses and arrive at a consensus. Since then, the Delphi method has been widely adopted by organisations as an important decision-making technique.

Delphi method aims at soliciting the views of experts through a series of strategically designed questionnaires interspersed with information and opinion feedback so as to converge their responses to a consensus.

A very comprehensive definition of Delphi method is given by Wechsler, who says, “Delphi is a survey which is steered by a monitor group, comprises several rounds of a group of experts who are anonymous among each other and for whose subjective-intuitive prognoses, a consensus is aimed at. After each survey round, a standard feedback about the statistical group judgment calculated from median and quartiles of single prognoses is given and if possible, the arguments and counter arguments of the extreme answers are fed back”.

Thus, a Delphi method is adopted in the following procedure:

(a) A panel of experts is selected for resolving a particular problem.

(b) These experts are kept separated and their anonymous judgment or opinion over the issue is sought through questionnaire or a survey. Maintaining their anonymity helps in getting the unbiased responses.

(c) After this, members are asked to share and discuss their assessment with each other.

(d) Replies are collected, summarised and is given back to all the experts.

(e) With this information of previous round assessment, the experts are required to make fresh decisions with the new inputs.

(f) This process goes on for numerous rounds until a satisfactory convergence of experts’ opinions is arrived at.

Delphi technique is a very useful technique for handling and resolving the complex problems which are subject to many interpretations and alternatives. Although, it is a time- consuming exercise and its success depends largely on the expertise, of the panelists and their communication skills.

(ii) Brainstorming:

Brainstorming is a powerful decision-making technique used to extract ideas from a group of people. For brainstorming, groups are formed and each individual is provided with a platform to explore and express their ideas to others. Brainstorming may be used by an organisation for multiple objectives such as solving a problem, generation of new ideas, team development, etc.

In order to be affective, brainstorming session needs to be structured so as to avoid chaos, individuals should be provided with a criticism-free environment and freedom to express their views. Unlike Delphi, brainstorming is done face- to-face so that each individual knows what is happening and may act and react.

Brainstorming is carried out in an organisation by adopting the following procedure:

(a) Create a group and make it familiar with the objective and purpose of discussion.

(b) Provide an environment in which each member of the group is able to interact clearly with every other member of the group.

(c) Provide adequate time and opportunity to every member to express their opinion.

(d) If possible, facilitator keeps on chalking down the ideas generated.

(e) Finally, the ideas generated or alternative solutions deciphered are assessed, analysed and prioritised.

For example, an organisation has witnessed a sharp decline in its sales in recent months. It is now looking for various means by which it can increase its sales.

In this case, a company wants to first develop a list of alternatives for increasing sales and then prioritise them. Thus, this issue can be best resolved through a brainstorming activity by inviting people from within the company or outside experts to discuss on the issue. They may sit together and develop a list of alternatives and rank them unanimously.

(iii) Nominal Group Technique (NGT):

Nominal Group Technique is a variation of brainstorming technique. It is a structured process of obtaining the group’s opinions, ideas, suggestions, etc. Unlike brainstorming, in Nominal Group technique, each member is acquainted with the problem or issue under consideration and is required to pen down his opinion and suggestion on a piece of paper.

Thus, initially no discussion is permitted amongst members. After all participants have given their ideas, then each one’s proposition and suggestion is discussed in an interactive manner within the group. Participants, as an outcome of this technique, develop a mathematical aggregation of each participant’s preferences so as to give the group ranking.

Thus, NGT technique is widely used in qualitative decision-making due to its following benefits:

(a) Involving personnel for decision-making process helps in wider acceptability of the final decision.

(b) Silent generation of ideas initially minimises the possibility of biases and undue influences. It allows an individual to be creative.

(c) Subsequent discussions and interactions allow the group to take the advantage of diversity of minds.

(iv) Multi-Voting:

Another group decision-making tool is multi-voting. In this method, repeated rounds of voting are carried out until a consensus is arrived at. In this method, each participant presents his opinion or proposition in front of the panel and each member casts a vote. When voting for every participant’s suggestion is completed, the strategies or suggestions with highest voting qualify for the next round. This process is continued until a clear unanimous strategy is voted.

(v) Didactic Interaction:

This is a very useful decision-making technique when decisions to be taken are dichotomous in nature. The solution to such decisions is in terms of either “yes” or “no” decision. For example, to purchase machinery or not to purchase, to import or not to import, to sell or not to sell, etc. These decisions are mutually exclusive, i.e., acceptance of one decision automatically results in rejection of another.

For this method, instead of one group of experts, two group of experts are created, one favouring a “yes” decision and other favouring a “no” decision. Each group then generates the list of justifications for their decisions and then interact and discuss with their findings. With mutual interactions and discussions, both the groups arrive at a consensus and a decision is taken.

Technique # 2. Quantitative Decision-Making:

Quantitative decision-making is the one which is based on numerical and quantifiable data. The quantitative approach to decision-making aims at solution finding through mathematical models. Such decision-making techniques are applicable in case of structured decisions. According to Good pasture, “Quantitative decision-making is most useful when there is a rational policy for obtaining the outcomes.” There are numerous methods of making decisions with the help of quantifiable data.

The most common ones are as follows:

(i) Decision Matrix:

Decision matrix method was invented by Professor Stuart Pugh and is also called as Pugh method. Decision matrix method is a quantitative technique used to rank the multi-dimensional options available for an underlying problem. This technique is primarily used when various alternatives are available and many different parameters are to be considered for making a selection.

Various areas of applicability of decision matrix are investment options, vendor options, product options, etc. The Decision Matrix is used by exercising a series of pair-wise comparisons between alternatives against a number of criteria or requirements. One of its key advantages over other decision-making tools is that Decision Matrix is able to handle a large number of decision criterion simultaneously.

(ii) Cost Benefit Analysis:

Cost benefit analysis is a systematic process for evaluating the feasibility of projects or proposals under consideration. As the name indicates, this method aims at comparing total benefits derived from a project with the total costs incurred for the same.

Cost benefit analysis, as a decision-making technique, is useful in situations where:

(a) Benefits and costs from a project can be numerically identified.

(b) Evaluating and selection of a project among many alternatives.

(c) Determining the feasibility of a capital purchase.

Being a numeric decision-making technique, cost benefit analysis should normally be undertaken for any project which involves policy development, capital expenditure, use of assets or setting of standards.

(iii) Payback Analysis:

Payback analysis is a financial tool in the hands of a decision-maker to determine the viability of the project by calculating payback period for the projects. Payback period may be defined as the period within which initial investment of a project is recovered. In other words, it tells how long a project will take to recover its initial investment. As a decision-making tool, on the basis of payback period, a manager may decide which project to accept and which to reject. A project with less payback period is preferred over others as it is fastest in recovering its investment.

Payback period is calculated using the following formula:

(iv) Decision Tree Analysis:

Decision tree analysis may be defined as a decision support tool which makes use of a tree-like graph, i.e., branching and depicting all possible decision alternatives for a particular problem. A decision tree is a pictorial method which starts with a root, i.e., underlying problem or decision to be made.

This root is then spread to branches and nodes depicting various alternatives and solutions available before the decision-makers for the underlying problem along with the state of nature and respective probability of occurrence of alternatives.

Decision trees, besides being pictorial, are also helpful in effective decision-making as they involve a systematic and formalized process leading to the presentation of holistic view of various alternatives to a particular problem and their respective consequences or outcomes.

(v) Simulation:

Simulation may be defined as an imitation of a real-life situation. As a decision-making technique, simulation is used by creating a replica of real-life situation so as to know what could be an outcome under real operating conditions. Donald G. Malcolm defines simulation as, “a model which depicts the working of a large-scale system of men, materials, machines and information operating over a period of time in a simulated environment of the actual real world conditions.” Simulation technique primarily aims at answering “what if’ questions about real-life situations.

The simulation method may be adopted in the following situations:

(a) In the study of projects involving huge investments before actual implementation.

(b) For foreseeing the difficulties or problems that may arise due to implementation of new machinery, process or system.

(c) For training employees without disturbing the actual operations.

(d) Situations where actual execution or performance is irreversible such as – medical operations, layout of a building, wars, etc.

(vi) Network Analysis:

Network analysis refers to use of network techniques for solving large, complex problems comprising of many interrelated activities to be performed in a particular order. For example in metro construction, bridge construction, etc., network analysis is applicable for successful completion of projects within time.

Network is a graphical presentation of these interrelated activities in the order of their occurrence connected through arrows and depicted by nodes. Network analysis aims at developing a network and then planning, scheduling and controlling of performance of activities of a large complex project.

There are primarily two network techniques which are widely applied. These are:

(a) Programme Evaluation Review Technique (PERT) – PERT is a technique applicable for projects with non-repetitive activities. PERT is a probabilistic approach where time of completion of each activity is not certainly known.

(b) Critical Path Method – CPM is a project evaluation technique which aims at identification of total duration for the project completion time along with the shortest path for its completion. CPM is a deterministic networking technique where activity completion time is known with certainty.

(vii) Operations Research:

Operations research may be defined as a scientific method making use of various tools and techniques to quantitatively provide solutions to the problems. As a quantitative decision-making technique, operations research is very widely used to solve a wide variety of problems.

With the help of applying operation research techniques, management is able to solve many complex problems through a systematic and objective methodology, which is subject to minimal biases. Operations research as a scientific approach comprises of various techniques which have their respective areas of applicability.

These techniques are:

(a) Linear programming – It is an optimization technique. It deals with the optimisation (maximisation and minimisation) of an objective function, i.e., problem under consideration subject to availability of constraints.

(b) Transportation model – This is a decision-making technique which aims at managing the movement of goods from V number of sources to ‘m’ number of destinations in the most cost-effective manner.

(c) Assignment model – This technique aims at assigning jobs to various task persons so as to minimise the cost of getting the work done.

(d) Inventory control – These techniques aims at taking decisions for economic order quantity, how much quantity to order, how frequently to order, what should be the safety stock level, etc.

(e) Queuing theory – This technique is applicable for resolving the long queue issues and problems of traffic congestion. For example, at petrol pumps, railway booking window, service windows in a college, etc., all face long queues. This technique primarily answers questions such as whether to open a new counter or not, what is the desired number of persons in a queue so as to maintain efficiency, etc.

(f) Sequencing theory – This technique involves determination of an optimal order or sequence of performing a series of jobs so as to optimise the total time or cost involved in the process.

Other Decision-Making Techniques:

i. Management Information System (MIS):

Management Information System or ‘MIS’ is a computer-based system of collecting, storing and disseminating data in the form of information needed to carry out the functions of management. MIS is a system to support the decision-making function in an organisation. It helps the managers to discharge their functions of management efficiently and effectively. With MIS, the quality of management enhances as it provides accurate, timely and relevant information necessary for planning, organisation and control.

According to Dickey, “Management Information System is an approach to information system design that conceives the business enterprise as an entity composed of interdependent system and sub-systems, which with the use of automated data processing systems attempt to provide timely and accurate management information which will permit optimum management decision-making.”

Objectives of MIS:

(a) Capturing Data – The very first purpose of MIS is to capture and collect data from diverse sources which will facilitate in organisational decision-making. Data may be specific, general, and contextual or may be an operational information.

(b) Processing Data – The data captured is in its original form is not apt for the purpose of making decision-making. Hence, it is processed to be converted into information. This processed data is utilised for various organisational functional decision areas such as planning, organising, coordinating, directing and controlling.

Data can be processed through:

(i) Making calculations

(ii) Sorting of data

(iii) Classifying data

(iv) Summarising data.

(c) Information Storage – MIS stores the processed or unprocessed data for future use. If any information is not immediately required, it is saved as an organisation record, for later use.

(d) Information Retrieval – The system should be able to retrieve this information from the storage as and when required by various users.

(e) Dissemination of Information – Information, which is an output or finished product of MIS, is disseminated to the users in the organisation.

Characteristics of MIS:

(a) Systems Approach – MIS follows a systems approach. It means considering a systematic and comprehensive outlook of various input and output sub-systems.

(b) Management-oriented – Management information system, being a very critical and integral part of decision-making, focuses on catering to the decision-making requirements of various managerial functions such as- planning, organising, staffing, etc.

(c) Need-based – Management information system is a means for effective decision-making. Thus, it is designed and implemented according to the need and requirement of an organisation or of specific level.

(d) Future Orientation – Being a tool for decision-making, MIS is essentially a future-oriented technique. Collecting data and providing information for taking decisions is done by MIS for future reference.

(e) Integrated approach – MIS, being a computer-based system aims at collection, processing and dissemination of information on a unanimous basis. It adopts an integrated approach so as to provide more meaningful information to the right person at the right time.

(f) Long-term Planning – MIS is a decision-making system which involves a complex set-up and expertise to implement it. To reap the benefits of MIS, it is implemented in an organisation for a long-term period.

Significance of MIS:

In the recent years, the need for management information system has increased manifold due to the following reasons:

(a) Fosters Effective Planning – MIS is very useful for efficient and effective planning function of an organisation. MIS by providing quick and timely information to the management will be instrumental in developing plans more accurately and swiftly.

(b) Faster Communication – Management information system, with the computer-based information system and usage of advanced techniques of information transfer, ensures that information reaches the right person at the right time. With MIS, the formal communication becomes fast and accurate.

(c) Globalisation and Reducing Cultural Gap – With the implementation of computer-based information system in organisations, one can scale down the problems arising from the linguistic, geographical and some cultural diversities. With MIS, sharing of information, knowledge, communicating and building relationships between different countries become much easier.

(d) Availability – Management information systems have made it possible for businesses to be open 24 x 7 across the globe. This means that a business can be open anytime and anywhere making trade between different countries easier and more convenient.

(e) Cost-Effectiveness and Productivity – MIS application promotes more efficient operation of the company and also improves the supply of information to decision-makers. Applying such systems can also play an important role in helping companies to put greater emphasis on information technology in order to gain a competitive advantage.

(f) Effective Means of Control – MIS is instrumental in generation of various kinds of reports indicating about the performance of men, materials, machinery, money and management. MIS is helpful in controlling costs by giving information about idle time, labour turnover, wastages and losses and surplus capacity. Furthermore, MIS makes comparison of actual performance with the standard and budgeted performance very promptly, enabling mangers to take remedial actions in no time.

Limitations of MIS:

MIS, although being a very sophisticated decision-making tool, has the following limitations:

(a) Only Quantitative Inputs:

MIS considers primarily quantitative components and thus, in this manner, it disregards the non-quantitative variables like assurance, motivation, dispositions of individuals from the association, etc., which have an essential impact and influence on the organisation’s decision-making process.

(b) Meant for Programmed Decisions:

MIS is less useful for making non-programmed decision-making. Such types of decisions are not of routine type and thus they require information, which may not be available from existing MIS to executives.

(c) Inflexibility:

With ever changing and dynamic environment, MIS may not be flexible enough to have imperative adaptability to rapidly redesign itself with the changing needs of time.

(d) No Substitute for Effective Management:

MIS, despite being an important element in decision-making, does not replace the role and function of managerial judgment in decision-making. It is simply a vital device in the hands of decision-makers which facilitate in decision-making and problem-solving.

(e) Expensive:

Implementation of management information system in an organisation requires huge investment in terms of installation of computers, appointment of specialised technical staff and providing training to existing employees for effectively utilising it.

ii. Decision Support System (DSS):

Decision Support Systems (DSS) are interactive computerised information systems planned in a manner so as to enable the decision-takers to make a selection of the most feasible alternative amongst various options available. As the name says, DSS is a software-based system which assists managers in taking decisions by providing access to voluminous information collected from various information systems in an organisation.

It need not necessarily take the decision itself. An appropriately composed DSS is an intelligent programming based framework expected to help the decision-makers to assemble valuable data from a mix of crude information, reports, individual learning, or plans of action to recognise and take care of issues and finally take decision.

A DSS requires three basic constituents:

(a) The database (or knowledge base)

(b) The model (i.e., the decision context and user criteria)

(c) The user interface

Objectives of DSS:

(a) Data handling – The very objective of a DSS is to handle and store large amounts of data. It is like database searches which can be accessed as and when need for extracting the information arises.

(b) Collection and processing of data – DSS aims at procurement of data from varied internal and external sources and then processing it to convert into relevant information and finally storing it on the system for access.

(c) Facilitate in report making – DSS not only provides information but also helps the decision-maker by generating reports and presentations suiting his needs. DSS also helps the user by making charts, graphs, tables, etc., according to the requirement of the user.

(d) Analytical support – DSS also provides support to the user by making complex analysis and developing comparative charts with the help of using advanced software packages.

(e) Performs “what-if” and goal-seeking analysis.

Characteristics of DSS:

(a) DSS provides modern systematic models and information investigation instruments to bolster decision-making activities which are primarily semi-organised and unstructured.

(b) DSS aims at concentrating on issues that are extraordinary and swiftly changing. It focuses on assisting in arriving at a solution and is not characterised with the system of arriving at a solution.

(c) DSS is a system comprising of user-friendly softwares enabling the users to have easy interface and work directly. It has supportive networks which help management to address vital issues and long-term trends, both in internal and external environment.

(d) Having a focus on unstructured and non-routine decisions, DSS relies upon judgment, assessment and knowledge of the manager rather than replacing it.

(e) DSS facilitates the decision-makers with an array of computing and communicating capacity so as to enable him to apply them in different situations and problems.

Significance of DSS:

(a) Speedy Decision-Making – Decision support system by facilitating the procurement, processing and storage of voluminous data enables the managers to extract and use information in no time. This reduces the decision cycle time and increases employee productivity. With the help of computerised support system, time savings are substantial which in turn speeds up the decision-making process.

(b) Improves Effectiveness of User – Another benefit derived from decision support system is that it enhances effectiveness of decision-makers. By providing ample information in no time, DSS helps in taking decisions after considering wider arena of information and alternatives.

(c) Cost Saving – Incorporation of a decision support system provides an environment where decision-making speeds up, information extraction and access is speedier, accurate and rapid. This brings a lot of operational benefits and thereby results in cost reduction.

(d) Improves Interpersonal Communication – DSS by improving the quantum of data accessibility and maintaining uniform access by the users aids in improving interpersonal relationships. DSS also provides a means for sharing facts and information about company operations which improves data availability.

(e) Increases Satisfaction of Decision-Maker – DSS by providing computerised information, sophisticated softwares for analysis and wider coverage of data develops a sense of confidence in decision-maker that better and accurate information is used for taking decisions. This in turn leads to a satisfied and contended decision-maker.

(f) Automation of Various Support Systems – Data-driven DSS makes business information available to all users promptly as and when required. With DSS, an organisation is capable of automating various support systems and integrating the flow of information in an organisation.

Limitations of DSS:

Decision Support System brings many advantages for organisations and can have positive benefits.

However, designing and developing of a decision support system may have following limitations:

(a) Huge Cost Involvement – The very essence of decision support system lies in collecting data from many sources and processes them to convert into information relevant for decision-making. Thus, it requires an investment into an effective information system. Moreover, for many purposes, DSS requires the development of advanced techniques, information insight and data framework, all employing a high cost.

(b) Information Overload – Providing of excess information may not necessarily be beneficial for the decision-maker. Instead, it may boomerang and reduce his efficiency in taking decisions. With information overload, decision-maker may feel overburdened, may filter important information and finally there may be a delay in decision-making.

(c) Shift of Responsibility – Through DSS, computerised information being at the helm of decision-makers, it becomes very convenient for them to avoid responsibility of any wrong decision by simply passing on the blame over to the computerised information.

(d) Reduces Creativity – Implementation of decision support system in an organisation may reduce the skills and creativity of the employees because of too much dependence on computers. Decision-maker may be reluctant in deciphering new methods and techniques of doing things and may opt for simply relying on what DSS provides.

(e) Status Reduction – Implementation of decision support system facilitates in collecting data, processing it, storing it and also provides various techniques and software to analyse it and make presentations. With this, many times, employees have a perception that their task is diminished to the clerical work.