Showing posts with label Decision Management. Show all posts
Showing posts with label Decision Management. Show all posts

Monday, 13 June 2022

Decision Management

Management Decision Making

Management decision-making is a critical part of the management planning function. Understanding the unique nature of managerial decisions requires understanding the types of decisions and the context for making those decisions.

Types or Categories of Management Decisions

Decision-making can be defined as selecting between alternative courses of action. Management decision-making concerns the choices faced by managers within their duties in the organization. Making decisions is an important aspect of planning. Decision-making can also be classified into three categories based on the level at which they occur.

Strategic Decisions

These decisions establish the strategies and objectives of the organization. These types of decisions generally occur at the highest levels of organizational management.

Tactical Decisions

Tactical decisions concern the tactics used to accomplish the organizational objectives. Tactical decisions are primarily made by middle and front-line managers.

Operational Decisions

Operational decisions concern the methods for carrying out the organization's delivery of value to customers. Operational decisions are primarily made by middle and front-line managers.

Decisions can be categorized based on the capacity of those making the decision.

Organizational Decisions 

An organizational decision is one that relates or affects the organization. It is generally made by a manager or employee within their official capacity. These decisions are often delegated to others.

Personal Decisions

Personal decisions are those primarily affecting the individual - though the decision may ultimately have an effect on the organization as a result of its effect on the individual. These types of decisions are not made within a professional capacity. These decisions are generally not delegated to others.

Areas of Decision Management

The goal of decision management is to enhance business operations intelligence by ensuring quick, consistent, and accurate fact-based decisions. The quality of structured operational decisions, no matter how complex, should be constantly improving. There are five areas that affect decision management:

Data and analytics: Data is accessed and processed with the help of descriptive, diagnostic, and predictive techniques. You need strong data quality as a basis for accurate decision-making, and the outcomes of those decisions affect the data as well.

Business Management Process: Managing human tasks and the sequence of business process automation and task management. The information from staff helps to make better decisions, and their roles are enhanced as a result.

Operations research: Optimizing and managing various goals based on standards and priorities that can be modeled. Decision management analyzes operations and suggests improvements that can be made.

Business rules management: Automating business rules and managing them based on inputs provided by subject matter experts.

Robotics: Using software to imitate human behavior in the automation of actions and related interactions with software systems.

Decision management results in efficiency and productivity, two critical factors for successful business operations. As a concept, decision management can be used in a wide number of industries, functions, and areas of business. There are so many businesses that make scores of operational decisions on a daily basis. The quality of these decisions has a direct impact on the effectiveness of the company. All decisions are impacted by data, regulations, market dynamics, and decision management—and therefore becomes a necessity.

Benefits of Decision Management

Better Utilization of Time

Regardless of the model of the decision management support system, research shows that it reduces the decision time cycle. Employee productivity is the immediate benefit from the time saved.

Better Efficacy

The effectiveness of decisions made with decision management is still debated because the quality of these decisions is hard to measure. Research has largely taken up the approach of examining soft measures like a perceived decision quality instead of objective measures. Those who advocate the creation of data warehouses are of the strong opinion that better and larger-scale analyses can definitely enhance decision-making.

Better Interpersonal Communication

Decision management systems open the door for better communication and collaboration among all decision-makers. Set rules ensure that all decision-makers are on a single platform, sharing facts and any assumptions made. Data-driven rule sets analyze and provide decision-makers with the best version of the possible outcome, encouraging fact-based decision-making. Better access to data always enhances the quality and clarity of decisions.

Cost Reduction

An outcome of good decision management rule sets is saving costs in labor (which comes from good decision-making, lowered infrastructure, and technological costs).

Better Learnings

In the long term, a by-product of decision management is that it encourages learning. There is more openness to new concepts, and a fact-based understanding of businesses, and the overall decision-making environment. Decision management can also come in handy to train new employees—an advantage yet explored in full.

Increased Organizational Control

With decision-making rule sets, a lot of transactional data is made available for constant performance checks and ad hoc inquiries by business heads. This gives management a better look at how business operations work. Managers find this to be a useful aspect of decision-making. There is a financial benefit to highly-detailed data, and this gradually becomes evident.

Disadvantages of Decision Management

As with any system, decision management systems can have a few disadvantages.

Information Overload

Considering the amount of data that goes through the system (and the fact that a problem is analyzed from multiple aspects), there are chances of information overload. With too many variables available on hand, the decision maker may be faced with a dilemma. Streamlined rule sets can help.

Over-Dependence

When decision-making is completely computer-based, it can lead to over-dependence. While it does free up man hours for better use of skills, it also increases dependency on computer-based decision-making. Individuals can be less inclined to think independently and come to rely on computers to think for them.

Subjectivity

One of the important aspects of decision-making is the number of alternatives that are offered based on objectivity. Subjectivity then tends to take a backseat, and this can affect decision-making and impact businesses. Things that cannot be measured cannot be factored in.

Overemphasis on Decision Making

Not all issues an organization is faced with need the power of decision management. An emphasis has to be placed on utilizing decision-making capabilities for relevant issues.

Types of Decision Support Systems for Decision Making

Decision support systems are classified into two types

Model-Based Decision Support Systems: These stand independent of any corporate information system. They work on the basis of strong theory or models and come with an excellent interface for easy interactivity

Data-Based Decision Support Systems: These set-ups collect large amounts of data from a variety of sources, store it in warehouses, and analyze it. The warehouse stores historical data and also comes with some reporting and query tools.

In data-based decision support systems there are two main techniques that are employed:

Online Analytical Processing (OLAP): Based on queries, this provides quick answers to some complex business needs. Managers and analysts can actively interact and examine data from multiple viewpoints.

Data Mining: By finding patterns and rules in existing data, useful decision-making information can be extracted to help in trend and consumer behavior patterns.






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