Quantitative Analysis: Uses in Business Management

This presentation discusses the concept of quantitative analysis and its use in business management. It covers the different techniques involved in QA such as mathematical programming, cost analysis, linear programming, and more. The role of QA in decision making, resource allocation, and minimizing costs is also explained.

Quantitative Analysis
Uses of QA in Business Management

What is Quantitative Analysis
 It is a technique that seeks for understanding the behaviour through
using the means of statistical and mathematical modelling, research and
measurement (Ferrero & Sison, 2014).
 It aims at representing a given reality in terms of numerical value.

How it is used in Business
Management
 Many companies or organisations employ candidates who have
expertise in the science of quantitative management and operations
research in solving problems.
 One of its common use comprise of the various different approaches to
simulation, liner programming and forecasting, among others.
 It is also used in the process of Business Decision Making

Types of QA techniques
 Mathematical Programming
 Cost Analysis
 Cost Benefit Analysis
 Linear programming
 Capital Budgeting
 Inventory Management
 Expected Value
 Decision Tree
 Simulation

 Information theory
 Utility theory or preference theory
 Heuristic Programming
 Decision theory
 Cost Effective Analysis
 Queuing or Waiting line theory
 Game theory

Role of QA and QA methods
 It provide a tool for the scientific analysis
 It provide solutions for different business problems
 It helps in proper deployment of the resources
 It assists in minimising the servicing costs and waiting time
 It helps in allocation of optimum resource
 It enables management to determine when and how much to purchase
(McKee, 2015)
 It ease the decision making process
 By different quantitative methods, the management could know the
reactions of the integrated business systems

Analysis of the techniques
 Mathematical Programming- It is useful when different factors constrain
the choices of strategies .
 Cost Analysis- Its main objective is to decide the optimum break-even
point, i.e., where the profits would be the highest. It is also called the
Break-Even Analysis
 Cost-Benefit Analysis- It is one of the useful techniques for decision
making. It is used to evaluate the social benefits and the economic costs
that are associated with a particular course of action

 Linear Programming- It is used to determine optimal mix of the limited
resources for increasing the profits and minimising the costs. It is an
extension of the cost analysis which is very useful in analysing the
complex problems. It involves solutions of the liner equations and is apt
when the managers allocate scare resources to the competing projects
 Capital Budgeting- It provides a set of different techniques that a
manager could use for evaluating the relative attractiveness of different
projects in which a lump payment is made for generating a stream of
earnings over future period (Thompson et al., 2016).

 Inventory Management- It involves the determination and control of the
amount of raw materials that an organisation must keep in stock for
operating efficiently and effectively.
 Expected Value- In order to understand the value model, it is very
important to comprehend the concept of probability that means the
possibility of an even to take place. The expected value of an event
refers to the income that it would produce times its probability.
 Simulation- these techniques are basically applicable to the problems
that the technicians and the managers want to know. It is conducted by
manipulating the physical models. It is very useful for solving complex
problems which cannot be solved by any other techniques.

 Queuing or Waiting Line theory- It aids the managers in making the
decisions that involves the establishment of the services that facilitate
to meet the irregular demands. It is applied to any situation that
produce a need for balancing the cost of increasing the available
services against the cost of letting the units wait.
 Information theory- It is a rigorous mathematical effort for solving the
problems in the communication engineering. As the Information theory
deals with the communication networks and the flow of information, it
has many important implications for the organisation design and for the
man-machine relationships.

 Cost Effectiveness Analysis- It is a decision making methodology which
ultimately lead to a comparison of the alternatives in terms of their
effectiveness and costs in achieving some particular objective. It permits
the analysis of the alternatives with widely ranging operational and
physical characteristics (Runfola et al., 2017).
 Heuristic Programming- It is also called Heuristic problem solving and is
an approach to decision making which has gained significant wide usage
in the current years.

Why is QA important?
 It is a basis for the scientific analysis- With an increase in the
complexities of the modern business, it is impossible to depend on the
decisions that are unscientific depending on the intuitions. QA provides
scientific methods for coping up with various problems for the modern
business
 It helps in selection process of optimal strategy- Through using QA
techniques it is possible to decide the optimal strategy of an
organisation which is undergoing competition from its competitors.

 Decision tree

 It provides methods of decision making in face of the uncertainty. These
are based upon the decision making theory.
 It provides the managers with numerous tools from operational
research, mathematics, statistics and economics. These tools help the
managers to provide more accurate description as well as solution of the
problem.
 All the solutions that are gained by the quantitative techniques are
completely free from the bias of managers and the owners of the
business.

References:
 McKee, H. (2015). Development Process of an Instructional Delivery
System on Quantitative Analysis in Business. Journal of Applied Learning
Technology, 5(3).
 Thompson, M., Houbiers, M., McConnell, J., & Irving, D. (2016).
Quantitative 4D analysis using business analytics techniques. First
Break, 34(7), 33-38.
 Runfola, A., Perna, A., Baraldi, E., & Gregori, G. L. (2017). The use of
qualitative case studies in top business and management journals: A
quantitative analysis of recent patterns. European Management
Journal, 35(1), 116-127.
 Ferrero, I., & Sison, A. J. G. (2014). A quantitative analysis of authors,
schools and themes in virtue ethics articles in business ethics and
management journals (1980–2011). Business Ethics: A European
Review, 23(4), 375-400.

Thank You