Quantitative Approach to Management - Explained
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What is the Quantitative Approach to Management?
The quantitative approach applies statistics, optimization models, information models, computer simulations, and other quantitative techniques to the management process.
Central to the quantitative approach is the principle that organizations are decision-making units. These decision-making units can be made more efficiently using mathematical models that place relevant factors into numerical terms.
The primary branches of quantitative management include:
- Management Science
- Operations Management
- Management Information Systems
- Total Quality Management
Back to: Business Management
Quantitative Management Techniques
Some of the primary techniques applicable to Quantitative Management include:
- Theory of Probability,
- Sampling Analysis,
- Correlation / Regression Analysis,
- Time Series Analysis,
- Ratio Analysis,
- Variance Analysis,
- Statistical Quality Control,
- Linear Programming,
- Game Theory,
- Network Analysis,
- Break-Even Analysis,
- Waiting Line or Queuing Theory,
- Cash-Benefit Analysis, etc.
What is Management Science?
This branch of management theory focuses on the development of mathematical and statistical models as a simplified representation of a system, process, or relationship as models, formula, and equations. These techniques help managers make maximum use of organizational resources to produce goods and services. This field of management has grown significantly with the development of computer systems and computational abilities.
What is Operations Management?
Operations management is a field of management focusing on efficiency, effectiveness, and producing or organizational systems, process, and functions used in the manufacture of goods or provision of services. It focuses on the operation and control of the production process (such as the use of resources) that transform resources into finished goods and services. It also looks at the extent to which the functional processes satisfy the needs and wants of the consumer. Operations management is a derivative of the mathematical models in which specified measurement systems are applied to operational scenarios. These methods are used to achieve a higher level of efficiency in operational tasks, such as plant layout, plant location, inventory control, and product distribution. Major areas of study within operations management include a product or process design, capacity planning, facilities location, facilities layout, materials requirement planning, and handling, scheduling, purchasing and inventory control, quality control, maintenance management, computer integrated manufacturing, just-in-time inventory systems, and flexible manufacturing systems. Types of operations management techniques include queuing theory, breakeven analysis, and simulation. These techniques are routinely applied to areas outside of operations.
What is Total Quality Management?
Total Quality Management (TQM) is a management theory developed following WWII during the reconstruction of Japan. Perhaps the best-known proponent of this school of management was W. Edwards Deming. Total quality management (TQM) is a management approach that focuses on the following elements of operations:
- Customer Focus
- Value Improvement
- Employee Empowerment
- Synergy of Teams
- Final Product Quality
- Preventing rather than detecting defects
- Universal quality responsibility
- Continuous Improvement
- Statistical measurement
- Process Focused
- Constant refinement and learning
- Training and Learning
- Accurate Measurement
There are four phases of total quality management:
- Planning Phase: Employees discover the problems in regular operations and their root-causes. Employees conduct comprehensive research and collect relevant data. The objective is to identify potential solutions to their problems.
- Doing Phase: Employees develop and execute strategies and plan to address identified problems.
- Checking Phase: Data is collected to analyze performance to validate the effectiveness of the processes and measuring the outcome.
- Acting Phase: Outcomes are documents and employees begin addressing resulting challenges.
What is Lean Management?
Lean management is an approach to management focusing on maximizing customer value while reducing processes waste without compromising quality. This is done through incremental improvement. The principles of lean management include:
- Value Identification - Focus on the customers point of view.
- Value Mapping - Eliminate all of the unnecessary steps in the value delivery process.
- Operational Mapping - Focus on sequencing value-providing activities.
- Value Pull - Identify the point at which customers pull value from the process.
- Efficiency - Continue to seek increased efficiency with less waste.
Lean management seeks to achieve an ideal state of operations known as single-piece flow. In product production, this means eliminating the wastes associated with batch production. Instead, it focuses on single-production production. In any process, this principle seeks to eliminate wastes from unnecessary human motion, inventory inefficiency, labor inefficiencies, space inefficiencies, product defects, and overproduction. The benefits of lean management are that it reduces defects and manufacturing flexibility. The downside is that it can result in lower productivity and longer process cycles. Lean management was made popular by Toyota Corporation as part of its production process.
What is Management Information Systems?
Information systems allow for more efficient creation, management, and communication of information across the organization as well as in the outside environment. The information allows for more efficient management decision making by providing information in a more timely manner and in a more useful format. Notably, Decision Support Systems (DSS) integrate decision models and data to this end.
What are the Positive and Negative Aspects of Quantitative Management Theory?
- It establishes relationships amongst quantifiable variables of decision-making situations and facilitates disciplined thinking.
- Mathematical models help to derive precise and accurate results by analyzing complex statistical data.
- It is useful in areas of planning and control where data is available in quantitative terms. Decisions are based on data and logic rather than intuition and judgment.
- Computer-based Statistical packages are available which facilitate analysis of qualitative data also (dummy variables are used to analyze the non-quantifiable data).
- Mathematical models cannot fully account for individual behaviors and attitudes.
- The time needed to develop competence in quantitative techniques may delay the development of other managerial skills.
- Mathematical models typically require a set of assumptions that may not be realistic in an industrial setting.
- Among the different functions of management, its use is limited in organizing, staffing and directing. It applies more in planning and control functions.
- It does not eliminate risk but only attempts to reduce it.
- It assumes that all the variables affecting the problem can be quantified in numerical terms which is not always true.
- Decisions are often based on the availability of limited information.
Who are some of the primary contributors of various theories to the quantitative approach?
- Decision Theory - Determination of objectives of the firm, assessment of group conflicts and interaction, organization analysis. R.M. Thrall, C.I. Bernard, H.A. Simon, N. Weine. Decision theory looks at the various factor influences management decision making. It views decision making is a continuous process within the organization. The organizations success will depend upon the quality of the decisions made. This requires the use or quantitative methods in evaluating options. Communication plays an important role in efficient decision making. Decisions can be grouped into Programmed and Non-Programmed, Organizational and Personal, and Major and Minor Decisions.
- Inventory Theory - Economic lot size and inventory control. F.W. Harris, J.F. Magee
- Game Theory - Timing and pricing in a competitive market, military strategy. J. Von Newman, Shubik
- Queuing Theory - Inventory control, traffic control, radio communication, telephone trunking system. A.K. Erlang, L.C. Edie, P.M. Morse, M.G. Kendall.
- Linear Programming - Assignment of equipment and personnel scheduling, input-output analysis, product mix. W. Leontief, G.B. Dantzig, P.A. Samuelson
- Sampling Theory - Quality control, Simplified accounting and auditing, consumer surveys and product preferences in marketing research. E. Deming, H.F. Dodge
- Probability Theory - Almost all areas of application. R.A. Fisher, T.C. Fry, W. Feller
- Statistical Decision Theory - Estimation of model parameters in probabilistic models. A. Wald, E.D. Molina, W. Shewhart
- Symbolic Logic - Circuit design, legal inference. G. Boole, B. Russell, A.N. Whitehead.