Analyzing Business Decision Making Process
Continuous analysis of organizational decision-making process is essential to high quality and transparent decisions; otherwise a business runs with a prejudice: the notion that it is good at making decision, even if in reality it is not. And probably this is why both, decision makers and decision support system analysts try to get a profound understanding of organization-wide decision-making, in order to build highly customized DSS software.
This means a lot goes into planning, designing and implementing a decision support system. Decision making is important as well as complex. But its scope is broad. It‚Äôs not restricted to a certain level of hierarchy; rather employees at all levels across all departments make decisions, depending upon the roles they play and situations they get face-to-face with.
Some decisions are related to evaluating investments, allocating resources or assessing mergers and acquisition proposals while some are about introducing new products, studying their shelf life or enhancing manufacturing efficiency. There are also day-to-day decisions that are valid for a point of time.
Typically, more objective decisions are made at lower levels of hierarchy, which can be quantified. Higher levels of hierarchy deal with unstructured or ill-structured decisions, which are subjective in nature. While objective decisions may not require creativity, subjective decisions do.
Like decisions made in each department at each level are different, similarly a decision support system analyst must take into consideration the type of decisions and distinguished factors influencing decision-making before going to the drawing board and designing the architecture.
Understanding the context in which decisions are made is an important consideration in building a decision support system. Let us take a closer look at the factors that a DSS analyst should take into account:
Types of Managerial Decisions
As said earlier, decisions are made at all levels of hierarchy. Therefore, it‚Äôs important to understand what type of decisions a decision support system is going to support.
- Strategic decisions: As strategic decisions are not related to general functioning of an organization, these are non-repetitive in nature and require a lot of time to be arrived at. Generally taken by the highest level of hierarchy, strategic decisions involve careful analysis of the situation and consequences.
Some examples of strategic decisions: Evaluation of an investment proposal, Decisions related to mergers and acquisitions, Resource allocations, Fund raising, etc.
- Operational decisions: These types of decisions fall under two categories. Decisions pertaining to plant location, production volume, distribution channel and policies are taken by top management. These are long term decisions that directly impact the functioning of a business. The second category of decisions is related to day-to-day functioning, which are taken by middle and lower level managers.
- Managerial decisions: These decisions pertain to resource allocation, talent management, research and development, new product introduction, withdraw or revamp old products. These are combined decisions taken by top and upper middle management.
Each type of decision requires different level of support. A decision support analyst needs to analyze ‚Äď what types of decisions need to be supported; who are involved in decision making process; and whether alternative courses of actions are required to be shown.
Nature of Problems
Decision making may be simple or complex depending upon the nature of the problem. It may be repetitive or non-repetitive, structured or unstructured. And each problem type requires different approach, problem-solving technique and subjectivity. Let‚Äôs understand this in detail:
- Recurring/ Repetitive problems: Recurring decisions are taken very frequently and do not require in-depth analysis and evaluation every time. Employees at the lower level of hierarchy are empowered to take these decisions on their own because a standard procedure is followed to tackle such problems.
- Non-repetitive problems: Non repetitive decisions are taken once in a while. Non-repetitive problems may or may not be difficult to tackle but they are not regular. Difficult problems are taken care of by the upper levels of management while the non-complex ones are solved by lower management.
- Structured problems: Structured problems can be quantified and therefore, can be solved using computational techniques. Structured problems may occur frequently as these are generic in nature.
- Non-structured problems: Non-structured problems are hard to quantify, making it difficult to decide the tangible objectives that a solution should achieve. These do not occur frequently. Although the decisions can be automated, but a thorough involvement of decision makers is also required. These decisions typically require creativity and human cognizance along with automated solution.
The architecture of a decision support system is developed once a DSS analyst understands what kinds of problems are likely to be solved. A decision support system is generally used when a problem is ill-structured, complex and vague and the amount of information to be considered is huge.
Involvement of People
A decision support system analyst must take into account the people involved in a decision making process. There is a set of decisions that are taken by a group of individuals. In such a case, a DSS must enable the people involved to connect, communicate and share files, data and views with each other. A simple DSS would do, if the decision maker is an individual.
Numerous factors have a direct impact on decision-making. Managers can help decision support system analysts in understanding these internal and external factors that impact decision-making.
External factors may include: technology, political environment, suppliers, distributors, competitors and customers.
Internal factors include people (their perceptions, capabilities, frequency of decision making, type of decisions they take), department (where a DSS is to be implemented) and organizational factors (procedures and processes, budget, change management).
A decision-making context defines the circumstances in which a problem is rooted. It also defines the assumptions around the problem, associated risks, level of uncertainty and expected return.
A decision support system analyst must take decision-making context into account because it will help him:
- Identify the potential for decision support: If a computerized or automated decision making system will work or not. If yes, what problems it will likely to solve.
- Determine the scope of decision support: At what level support is required. For generic problems, a DSS can offer complete support, but for an ill-structured problem, it can only show all possible alternative courses of actions with their pros and cons, leaving the end decision to the user.
Depending upon a decision-making context, a DSS analyst can must consider goals to be achieved, examine relevant alternatives, draw a process to rank alternatives, predict decision environment (internal and external factors affecting decisions) and identify the characteristics of decision-makers.
Decision Making Process
Previously, decision making was a purely cognitive process to select the most feasible course of action from among the available alternatives. However, this was when decision support systems didn‚Äôt exist.
Nowadays, a decision-making process is supported extensively by automated software systems. However, if we carefully look at the sequence or stages of decision making, we‚Äôll barely find any deviation.
Decision making certainly is more complex today, but it is supported by computerized systems. A decision making process involves following step:
- Defining the Problem
Defining a problem is important. It provides decision makers with a base, on which they can build assumptions, collect and analyze data and evaluate alternatives. Defining a problem begins with recognizing that a problem exists. A problem exists when:
- There‚Äôs a difference between expected and delivered
- There‚Äôs a divergence from the customary
- An action taken is not justifiable
A DSS defines the problem and complexities involved by comparing deliverables and delivered.
- Identifying Decision Maker
Depending upon the nature of the problem, it is sent to the right person. An ill-structured problem will go to top management; a complicated problem to the managers and recurring will be sent to the employee at a lower hierarchical level.
- Gathering Information
Once a problem is sent to the right person, the concerned person can begin with collecting data and identifying the factors influencing the situation. Without DSS, you will take too long a time to collect and analyze data. A DSS can process tons of data in just few seconds.
- Evaluating Alternatives and Deciding
This stage involves sifting through all possible courses of action and determining the most suitable from among them, by assessing the pros and cons of each alternative. A DSS helps in justifying a particular choice.
- Implementation and Follow-up
Once the decision is taken, it‚Äôs time to walk the walk. It‚Äôs time to implement. Again implementation needs whole lot of planning. Monitoring is also essential to determine if a particular decision is helpful in achieving the objectives. It may require some adjustments or may lead to a new problem. If latter is the case, you may have to repeat the entire process.
Good Decision Making
A good decision is the one that is free of biases and prejudices, and resolves the identified problem while capturing the maximum value. It is something that takes you towards your goal, given the ambiguities and intricacies of the real world.
Characteristics of a good decision:
- Longer shelf life
- Doesn‚Äôt raise a conflict of interest
- Takes into account internal and external factors
- Helps decision maker get what they‚Äôre seeking
A meticulously designed decision support system aids in good decision making. If a decision maker uses a standard DSS, the results obtained are distorted, which defeats the whole purpose of using it.
Redesigning Decision Making Process
A decision making process is a group of various interrelated activities. Its sole aim is to create value for the organization.
In today‚Äôs extremely complex business environment, it‚Äôs important to make faster, more flexible, transparent and high quality decisions.
Redesigning/reengineering a decision-making process may help organizations become agile and nimble and significantly reduce the time taken in making a decision.
A decision making process can be reengineered by:
- Envisaging new work strategies
- Dropping iterative processes
- Encouraging full-scale recreation
- Fostering more creativity in decision making rather than automating the whole process
A decision support system should be developed in such a way that it promotes creativity rather than automation. It must propel a decision maker to think and come up with an out-of-the-box idea. Instead of being efficient, it must be responsive.
Authorship/Referencing - About the Author(s)
The article is Written By ‚ÄúPrachi Juneja‚ÄĚ and Reviewed By Management Study Guide Content Team. MSG Content Team comprises experienced Faculty Member, Professionals and Subject Matter Experts. We are a ISO 2001:2015 Certified Education Provider. To Know more, click on About Us. The use of this material is free for learning and education purpose. Please reference authorship of content used, including link(s) to ManagementStudyGuide.com and the content page url.
- Decision Support Systems ‚Äď Introduction
- Gaining Competitive Advantage with DSS
- Limitations & Disadvantages of DSS
- Analyzing Business Decision Making Process
- Designing and Developing DSS
- Designing a DSS User Interface
- Building DSS User Interface
- DSS Architecture, Networking and Security Issues
- Communications Driven and Group Decision Support System
- Building Model-Driven Decision Support System
- Building Knowledge-Driven Decision Support System and Mining Data
- Building Web-Based and Inter-Organizational Decision Support Systems
- Evaluating Decision Support System Projects