Decision Science is the application that uses scientific approach and solves the management problems. It also helps managers to make best decisions. Decision science includes a large number of mathematically oriented techniques. These techniques can be either developed within field of decision science or taken from other disciplines. Decision science is a recognized and established discipline in business. Decision science is a technique which is mainly used within business for increasing their efficiency and productivity.

In various surveys of businesses, many indicate that they use decision science techniques, and most rate the results to be very good.
Decision science is also known as operations research, quantitative techniques, quantitative analysis and management sciences. It is largely used in daily routine of most programs of business organization.

Contents :
  1. Meaning & Definition of Quantitative Techniques.
  2. Role of Quantitative Techniques in Decision Making.
  3. Characteristics of Quantitative Techniques.
  4. Scope of Quantitative Techniques.
  5. Nature of Quantitative Techniques.
  6. Importance of Decision Science / Quantitative Techniques.
  7. Limitations of Quantitative Techniques in Business Decision Making.
  8. Applications of Quantitative Techniques.

Meaning and Definition of Quantitative Techniques :

The term Decision Science / Quantitative Techniques (QT) /Operations Research (OR) describes the discipline that is focused on the application of Information Technology (IT) for well-versed decision-making.

Quantitative techniques are those statistical and programming techniques: which support the decision making process especially related to industry and business. QT takes into consideration the elements of qualities such as use of numbers, symbols and other mathematical expressions. QT is basically helpful enhancement to judgment and intuition. Quantitative techniques assess planning factors and alternatives as and when they arise rather than suggest courses of action.

Quantitative, techniques may be defined as those techniques which provide the decision maker with a systematic and powerful means of analysis and help, based on quantifiable data, in exploring policies for achieving pre-determined goals. ''Quantitative techniques are mainly appropriate to problems of complex business enterprises".

QT can be considered as the scientific approach to managerial decision making. This approach starts from raw data and after manipulation or processing, information is produced which is valuable for making decision.
The main aim of quantitative analysis is the processing and manipulating of raw data into meaningful information. For increasing the use of quantitative analysis, computer can be used as an instrument.

According to C.R. Kothari :
"Quantitative Techniques may be defined as those technique which provide the decision maker with a systematic and powerful means of analysis and help, based on quantitative in exploring policies for achieving per-determined goals”.
Quantitative Techniques are the devices developed on the basis of mathematical and statistical models.

Role of Quantitative Techniques in Decision Making :

The major roles of quantitative technique are as follows :
  1. It provides a tool for scientific analysis.
  2. It offers solutions for various business problems.
  3. It enables proper deployment of resources.
  4. It supports in minimizing waiting and servicing costs.
  5. It helps the management to decide when to buy and what is the procedure of buying.
  6. It helps in reducing the total processing time necessary for performing a set of jobs.

Characteristics of Quantitative Techniques :

1) Decision-Making : 
Decision-making or problem solving constitutes the major working of operations research: Managerial decision-making is considered to be a general systematic process of operations research (OR).

2) Scientific Approach : 
Like any other research,  operations research also emphasizes on the overall approach and takes into account all the significant effects of the system. It understands and evaluates them as a whole. It takes a scientific approach towards reasoning. It involves the methods defining the problem, its formulation, testing and analyzing of the results obtained.

3) Objective-Oriented Approach :
Operations Research not only takes the overall view of the problem, but also endeavor's to arrive at the best possible (say optimal) solution to the problem in hand. It takes an objective-oriented approach. To achieve this, it is necessary to have a defined measure of effectiveness which is based on the goals of the organization. This measure is then used to make a comparison between alternative solutions to the problem and adopt the best one.

4) Inter-Disciplinary Approach : 
No approach can be effective, if taken singly. OR is also inter-disciplinary in nature. Problems are multi-dimensional and approach needs a team work. For example, managerial problems are affected by economic, sociological, biological, psychological, physical and engineering aspect. A team that plans to arrive at a solution, to such a problem, needs people who are specialists in areas such as mathematics, engineering, economics, statistics, management, etc.

Scope of Quantitative Techniques :

The following are the scope of quantitative techniques in different areas :

Scope of Quantitative Techniques

1) Industry :
Industrial management deals with a series of problems, starting right from the purchase of raw materials till the dispatch of final products. The management is ultimately interested in overall understanding of the methods, of optimizing profits. Therefore, to take decision on scientific basis, operations research team has to think about various alternative methods, to produce goods and obtaining returns in each case.
Not only this, the operations research study should also suggest possible changes in the overall structure like installation of a new machine or introduction to automation, etc., for optimizing the results. Many industries have gained immensely by applying operations research in various tasks. For example, operations research can be used in the fields of manufacturing and production, blending and product mix, inventory management, for forecasting demand, sale and purchase, for repair and maintenance jobs, for scheduling and sequencing planning, and also for scheduling and control of projects.

2) Developing Economies :
OR is applicable to both developing and developed economies. But a lot of scope exists in developing economies, for building up an operations research approach towards planning. The basic idea is to orient the planning, to achieve maximum growth per capital income in minimum time; considering the goals and restrictions of the country. Poverty and hunger are the core problems faced by many countries of Asia and Africa. Therefore, people like statisticians, economists, technicians, administrators, politicians and agriculture experts can work in conjunction, to solve this problem with an operations research approach.

3) Agriculture Industry :
Operations research approach has a huge scope in agriculture sector Population explosion has led to scarcity of food. Optimum allocation of land for various crops in accordance with climatic conditions is a challenge for many countries. Also, each developing country is facing the problem of optimal distribution of water from several water bodies. These areas of concern hold a great scope for scientific research.

4) Organization :
Organization, big or small, can adopt operations research approach effectively. Operational productivity of organizations have improved by using quantitative techniques. Techniques of operations research, can be applied to minimize cost, and maximize benefit for decisions. For example, a departmental store faces problem like, employing additional sales girls, or purchasing an additional van, etc.

5) Business and Society : 
Businesses and society can directly be benefited from operations research. For example, hospitals, clinics etc. Operations research methods can be applied directly to solve administrative problems such as minimizing the waiting time of outdoor patients.
Similarly, the business of transport can also be benefited by applying simulation methods. Such methods, can help to regulate train arrivals and their running timings. Queuing theory, can be applied to minimize congestion and passengers waiting time.
These methods are increasingly being applied in L.I.C. workplaces. It helps in deciding the premium rates of various policies. Industries such as petroleum, paper, chemical, metal processing, aircraft, rubber, mining and textile have been extremely benefited by its use.

Nature of Quantitative Techniques :

1) Quality of Solution : 
Quantitative techniques helps in improving the quality of solution but may not necessarily result in a perfect solution. It helps to find the best possible solution to the problem under consideration.

2) Goal-Oriented Optimum Solution : 
Quantitative techniques is sensitive about the optimization theory. It aims at identify the best possible course of action or solution under given constraints.

3) Use of Models : 
Quantitative techniques uses models built by quantitative measurement, It also derives a solution from the model using one or more of the diversified mathematical techniques. A decision can be arrived, either by conducting experiments on it or by mathematical analysis. The objective is to assess the organization to determine its policy, and actions scientifically and optimize its results.

4) Require Willing Executives : 
Quantitative techniques needs a group of individuals having diverse backgrounds and skills to evaluate and analyze the costs, pros and cons of the alternative solutions of the problem. Willingness to participate in such experimental process is must for the executives. This will empower the decision-makers, to be objective in selecting the best possible solution.

5) Reduces Complexity : 
Quantitative techniques attempts to minimize the complexity of business operation by helping managers to correct a difficult function or process. It also attempts to innovate easy solutions of costly and complicated functions, compared to actual experimental practice.

Importance of Decision Science / Quantitative Techniques :

1) Better Control : 
For large organizations, it is practically impossible to continuously supervise every routine work. A QT approach comes handy and gives an analytical and quantitative basis to identify the problem area. QT approach is most frequently adopted with production scheduling and inventory replenishment.

2) Better Systems : 
For example, Problems identifying the best location for factories or decision on whether to open a new warehouse, etc., are often been studied and analysed by QT approach. This approach helps to improve the existing system such as, selecting economical means of transportation, production scheduling, job sequencing, or replacing old machinery.

3) Better Decisions : 
QT models help in improved decision-making and thereby reduce the risk of wrong decisions. QT approach gives the executive an improved insight into the problem and thereby improve decision-making.

4) Better Co-ordination : 
QT models help in co-ordination of different or various divisions of an organisation.

Limitations of Quantitative Techniques :

1) Dependence on an Electronic Computer : 
QT approach is mathematical in nature. QT techniques try to find out an optimal solution to a problem, by taking all the factors into consideration. The need of computers become unavoidable because these factors are enormous (huge), it requires huge calculations to express them in quantity and to establish relationships among them.

2) Non-Quantifiable Factors : 
One of the drawbacks of QT techniques is that they provide a solution only when all the elements related to a problem are quantified. Since all relevant variables may not be quantified, they do not find a place in QT models.

3) Wrong Estimation : 
Certain assumptions and estimates are made for assigning quantitative values to factors involved in QT, so that a quantitative analysis can be done. If such estimates are wrong. the result can be misleading.

4) Involves Time and Cost : 
Operations research is a costly affair. An organisation needs to invest time, money and effort into QT to make it effective. Professionals need to be hired to conduct constant research. For better research outcomes, these professionals must constantly review the rapidly changing business scenarios.

5) Implementation : 
The complexities of human relations and behavior must be taken into account while implementing QT decisions, as it is a very delicate task.

Applications of Quantitative Techniques :

Uses, scope and applications of quantitative techniques in managerial decision-making are as follows :

1) Finance, Budgeting and Investment :
  • Long range capital requirements, cash flow analysis, investment portfolios and dividend policies.
  • Credit policies, credit risks and procedures for delinquent account.
  • Procedures to deal with complaints and claim.

2) Marketing :
  • Selection of product, its timing and competitive actions.
  • Cost and time-based decision for advertising media.
  • Rate of calling an account and requirement of number of salesmen, etc.
  • Market research effectiveness.

3) Physical Distribution :
  • Size of warehouses, distribution centre, retail outlets, etc., and their location.
  • Policy for distribution.

4) Purchasing, Procurement and Exploration :
  • Buying rules.
  • Determining purchase timing and its quantity.
  • Policies for bidding and analysis of vendor.
  • Replacement policies of equipment.

5) Personnel :
  • Manpower requirement forecasting, recruitment policies and assignment of job.
  • Suitable personnel selection considering age and skills, etc.
  • For each service center determining the optimum number of persons.

6) Production :
  • Proper allocation of machines for scheduling and sequencing the production.
  • Optimum product mix calculation.
  • Selecting production plant sites along with its location and design.

7) Research and Development :
  • Alternative designs evaluation and its reliability.
  • Developed projects control.
  • Multiple research projects co-ordination.
  • Required determination of time and cost.

How Organizations might use Quantitative Techniques in Daily Business Activities?

Banks and other financial institutions often use quantitative techniques in their daily business activities to make informed decisions and manage risk. These techniques help banks to stay competitive and provide better services to their customers. Here are some examples:

1) Credit Scoring: 
Banks use quantitative techniques to assess the creditworthiness of loan applicants. They use statistical models to evaluate the credit risk of an applicant based on various factors such as credit history, income, debt-to-income ratio, and employment history.

2) Risk Management: 
Banks use quantitative techniques to manage their risk exposure. For example, they use quantitative models to measure market risk, credit risk, operational risk, and liquidity risk. These models help banks to identify and quantify potential risks and take appropriate measures to manage them.

3) Portfolio Management: 
Banks use quantitative techniques to manage their investment portfolios. They use models to analyze market trends, identify potential opportunities, and make informed investment decisions.

4) Fraud Detection: 
Banks use quantitative techniques to detect and prevent fraud. They use statistical models to identify suspicious patterns and anomalies in transaction data, which can help them identify potential fraud.

5) Customer Segmentation: 
Banks use quantitative techniques to segment their customers based on various characteristics such as demographics, spending patterns, and transaction history. This helps banks to target specific customer segments with personalized offers and services.