Is conducted to address a specific business decision for a specific firm or organization what is?

Unformatted text preview: Chapter 1 Role of BUSINESS RESEARCH 1–1 Business & Decision Making • The crux of decision making – is making a selection from among the available alternatives. [No Alternatives --- No Decision Making] • Big or small decisions are to be made, by human beings, in every walk of their lives – almost on daily basis – rather more frequently. • Decisions can be made on the basis of instincts, intuitions, gut-feel, likes / dislikes, whims and fancies or on the basis of some pragmatic thinking based on experience, information and knowledge – depending on what is at stake – what risk is involved – how to reduce uncertainty. Informed decision making - rather than shooting in the dark. • “Business” is a serious business, where, often decisions are made on pragmatic well thought of deliberations - based on experience. Collecting relevant information and knowledge for business decisions is what is called as business research . THE PURPOSE OF RESEARCH IS TO PROVIDE KNOWLEDGE 1–2 Nature of Business Research Research is ONE OF THE TOOLS of INTELLIGENT / INFORMED Decision Making Intuitive Information Processing Vs Systematic, Objective & Accurate Investigations Marketing Research is a sub-set of Business Research 1–3 Steps In Decision Making 1.Fixing the Objectives 2. Analyzing / Defining the Situation / Problem 3.Identifying Possible Alternative Solutions 4.Evaluating Alternative Courses of Action 5.[Implementing and]Validation of Results 1–4 Business Research Defined Every business issue ultimately boils down to an information problem. How to collect the required information?? • The application of the scientific method in searching for the truth [Finding the Facts] about business phenomena is Business Research. • The Research process includes: Setting the Objectives Idea and theory deployment / development Analyzing the situation / Defining the problem Searching for and collecting information (for possible alternatives) Analyzing data Communicating the findings and their implications Research Reduces Risk, but it is not a substitute for Managerial Decision Making 1–5 Business Research Defined • This definition suggests that business research information is: not intuitive or haphazardly gathered – should be systematic and planned accurate and objective (not subjective) relevant to all aspects of the business limited by one’s definition of business • Not-for-profit organizations and governmental agencies can use research in much the same way as managers in for-profit organizations. “ It ain’t the things we don’t know that gets us into trouble. It’s the things we know that ain’t so.” 1–6 Applied and Basic Business Research • Applied business research conducted to address a specific business decision for a specific firm or organization. Short term – Problem Identification / Solving Activity Example: Should McDonald’s add Shawarma to its menu? Which health insurance plan should a business provide for its employees? What should be the strategy of Zong to have a satisfied customer base in view of new level of knowledge and changed attitude and behavior of consumers? What should be the strategy of P&G, regarding distribution of shampoos, in view of new business environment? BUSINESSES OPERATE IN A DYNAMIC WORLD 1–7 Applied and Basic Business Research • Basic business research (also called pure research -- (Testing Assumptions & Forming Theories) conducted without a specific decision in mind that usually does not address the needs of a specific organization. Attempts to expand the frontiers of knowledge in general. Not aimed at solving a pragmatic problem. Example: Do consumers experience cognitive dissonance in lowinvolvement situations? Does employee tenure with a company influence productivity? Basic research provides the foundation (theories / approaches) for Applied research 1–8 The Scientific Method • Scientific Method [used in all types of Business Researches] The way researchers go about collecting information and using knowledge and evidence to reach objective conclusions about the real world The analysis and interpretation of empirical evidence (facts gathered from observation or experimentation or through communication) to confirm, prove or disprove prior conceptions Data -> Information -> Knowledge -> Wisdom 1–9 A Summary of the Scientific Method Empirical Evidence Ideas that can be TESTED General LAWS 1–10 Managerial Value of Business •Research There are only a few business orientations: Product-oriented; How should be the product like? [ for technical superiority in the product e.g., product design, taste test, package test, etc], Production-oriented: What should be process like? [ to improve efficiency and effectiveness e.g., manufacturing process, time and motion studies etc] Marketing-oriented: What should be the strategy like to enhance customer-value? [e.g., Needs, Price, Place, Promotion, Positioning etc, consumer - oriented] 1–11 Business Orientations 1–12 Managerial Value of Business Research • Managers very frequently draw out strategies, plans, tactical moves, interventions etc – which all involve decision making. • The decision-making process associated with the development and implementation of a business strategy involves four interrelated stages: 1. 2. 3. 4. Identifying existence of some problems / opportunities Clarifying the situation. Diagnosing (reasons?) and assessing (gravity of ?) the problems or opportunities Selecting (best alternative) and implementing a course of action Monitoring the implementation / course of action (and) Evaluating the (results) 1–13 1. Identifying Problems or Opportunities [WHETHER THERE ARE ANY PROBLEM OR OPPORTUNITIES] • Business Research may be used as a Scanning Activity to provide information about what is happening / occurring within an organization or in its environment. • Business Research can help Managers Plan Strategies by determining the nature of issues (situations) or by identifying the existence of problems or opportunities present in the organization or lurking in the environment. • Once the Business Research points out a problem or opportunity, managers may feel that the ALTERNATIVES are clear enough to make a decision based on their experience , knowledge or intuition …………………OR ……………they may decide that more Business Research is needed to generate additional information for a better understanding of the situation (reducing ambiguity and risk). 1–14 2. Diagnosing & Assessing Problems / Opportunities [WHAT ARE THE PROBLEMS / OPPORTUNITIES?] • Managers need to gain insights about the underlying FACTORS causing the situation. • If a problem – specify what happened,when and why? • If an opportunity – explore, refine, and quantify [& prioritize] 3. Selecting & Implementing a Course of Action [WHAT ARE THE POSSIBLE SOLUTIONS / ALTERNATES?] • Once the ALTERNATES have been identified, further Business Research is conducted to obtain information, that will aid in evaluating the alternatives and in selecting the best course of action. 1–15 4. Evaluating the Course of Actions [HOW BEST IS THE SOLUTION BEING ACHIEVED?] • Performance Monitoring Research (continuous) Research that regularly, sometimes routinely, provides feedback for evaluation and control of the implementation process / business activity. • Evaluation Research (one time) The formal, objective measurement and appraisal of the extent a given activity, project, or program has achieved its objectives. The secret of success is to know something nobody else knows1–16 . When is Business Research Needed? • The decision to conduct or not to conduct business research or the need for research centers on: 1. Time constraints / urgency 2. The availability / accessibility of data 3. The nature / importance of the decision to be made 4. Benefits versus costs (the value of the research information in relation to costs) Will the payoff or rate of return be worth the investment? Will the information improve the quality of the managerial decision enough to warrant the expenditure? Is the expenditure the best use of the available funds? 1–17 Determining When to Conduct Business Research 1–18 Business Research in the 21st Century • Communication Technologies [Age of Information Explosion] Always “connected”—time, place, and distance are irrelevant. Reduction in information acquisition, storage, access, and transmission costs. [Time is collapsing / Distance is Disappearing] • Global Business Research The environment is becoming, day by day, more complex, interconnected, with increasing ambiguity and uncertainty. Business research is increasingly global. Must understand the nature of particular markets. Cross-validation Verify that the empirical findings from one culture also exist, are relevant and behave similarly in another culture. Drowned in Information -> Devoid of Knowledge ASK RIGHT QUESTIONS 1–19 ...
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A decision-making process is a series of steps taken by an individual to determine the best option or course of action to meet their needs. In a business context, it is a set of steps taken by managers in an enterprise to determine the planned path for business initiatives and to set specific actions in motion. Ideally, business decisions are based on an analysis of objective facts, aided by the use of business intelligence (BI) and analytics tools.

In any business situation there are multiple directions in which to take a strategy or an initiative. The variety of alternatives to weigh -- and the volume of decisions that must be made on an ongoing basis, especially in large organizations -- makes the implementation of an effective decision-making process a crucial element of managing successful business operations.

There are many different decision-making methodologies, but most share at least five steps in common:

1. Identify a business problem.
2. Seek information about different possible decisions and their likely effect.
3. Evaluate the alternatives and choose one of them.
4. Implement the decision in business operations.
5. Monitor the situation, gather data about the decision's impact and make changes if necessary.

Data-driven decision making

Traditionally, decisions were made by business managers or corporate executives using their intuitive understanding of the situation at hand. However, intuitive decision-making has several drawbacks. For example, a gut-feel approach makes it hard to justify decisions after the fact and bases enterprise decision-making on the experience and accumulated knowledge of individuals, who can be vulnerable to cognitive biases that lead them to make bad decisions. That's why businesses today typically take more systematic and data-driven approaches to the decision-making process. This allows managers and executives to use techniques such as cost-benefit analysis and predictive modeling to justify their decisions. It also enables lines of business to build process automation protocols that can be applied to new situations as they arise, removing the need for each one to be handled as a unique decision-making event.

If designed properly, a systematic decision-making process reduces the possibility that the biases and blind spots of individuals will result in sub-optimal decisions. On the other hand, data isn't infallible, which makes observing the business impact of decisions a crucial step in case things go in the wrong direction. The potential for humans to choose the wrong data also highlights the need for monitoring the analytics and decision-making stages, as opposed to blindly going where the data is pointing.

Challenges in the decision-making process

Balancing data-driven and intuitive approaches to decision-making is a difficult proposition. Managers and executives may be skeptical about relying on data that goes against their intuition in making decisions or feel that their experience and knowledge is being discounted or ignored completely. As a result, they may push back against the findings of BI and analytics tools during the decision-making process.

Getting everyone on board with business decisions can also be a challenge, particularly if the decision-making process isn't transparent and decisions aren't explained well to affected parties in an organization. That calls for the development of a plan for communicating about decisions internally, plus a change management strategy to deal with the effects of decisions on business operations.

Decision-making models can also be used to avoid these various challenges by creating a structured, transparent process.

What is a decision-making model?

A decision-making model is a system or process which individuals can follow or imitate to ensure they make the best choice among various options. A model makes the decision-making process easier by providing guidelines to help businesses reach a beneficial conclusion.

Decision models also make the decision-making process visible and easily communicable for everyone involved, including all managers, stakeholders and employees. They can be used for a wide variety of purposes across departments, businesses and industries, but they are especially useful when selecting software vendors or new tools, choosing new courses of action or when implementing changes that effect large amounts of people.

Types of decision-making models

Common types of decision-making models include:

Rational models. Rational decision-making is the most popular type of model. It is logical and sequential and focuses on listing as many alternative courses of action as possible. Once all options have been laid out, they can be evaluated to determine which is best. These models often include pros and cons for each choice, with the options listed in the order of their importance.

A rational decision-making model typically includes the following steps:

1. Identify the problem or opportunity.
2. Establish and weigh decision criteria.
3. Collect and organize all related information.
4. Analyze the situation.
5. Develop a variety of options.
6. Assess all options and assign a value to each one.
7. Decide which option is best.
8. Implement the decision.
9. Evaluate the decision.

Intuitive models. These decision-making models focus on there being no real logic or reason to the decision-making process. Instead, the process is dictated by an inner knowledge -- or intuition -- about what the right option is. However, intuitive models are not solely based on gut feelings. They also look at pattern recognition, similarity recognition and the importance or prominence of the option.

Recognition primed models. These models are a combination of rational and intuitive decision-making. Its defining element is that the decision maker only considers one option instead of weighing all of them.

The recognition primed decision-making process involves:

1. Identifying the problem, including all its characteristics, problem cues, expectations and business goals.
2. Thinking through the plan and performing a mental simulation to see if it works and what modifications might be needed.
3. If the plan seems satisfactory, then the final decision is made, and the plan is implemented.

In recognition primed models, alternative courses of action are only considered if the original plan does not produce the intended results. The success rate of this model correlates to an individual's experience and expertise.

Creative models. In this decision-making model, users collect information and insights about the problem and create some initial ideas for solutions. Then, the decision maker enters an incubation period where they do not actively think about the options. Instead, they allow their unconscious to take over the process and eventually lead them to a realization and answer which they can then test and finalize.

When to use decision-making models

Even when rules and procedures are set up to make business decision-making more systematic, there can still be room for intuition on the part of decision-makers. For example, after gathering data about different alternatives, more than one might seem similarly advantageous, or management might find itself lacking certain information needed to make a decision with full confidence. This is a good use case for incorporating an intuitive decision-making model into the process.

On the other hand, decisions that happen frequently and have clear optimal outcomes benefit from a structured, rational decision-making models. This approach to business problem-solving uses clearly prescribed steps and, usually, data analytics software to evaluate the available options and arrive at a decision. 

Sometimes involving more people in the decision-making process can pay off. This is known as participatory decision-making; in the business world, it involves managers seeking input and feedback on decisions from the workers they oversee. The participatory approach has the potential advantage of generating many ideas for solving a business problem; it also helps to engage employees.

Decision management

Decision management -- also known as enterprise decision management (EDM) or business decision management (BDM) -- is a process or set of processes that aims to improve the decision-making process by using all available information to increase the precision, consistency and agility of decisions. The processes also focuses on making good choices by taking known risks and time constraints into consideration. 

Decision models and Decision support systems (DSS) are key elements of decision management. Decision management processes also use business rules, business intelligence (BI), continuous improvement, artificial intelligence (AI) and predictive analytics to access the capabilities of big data and meet the needs of modern day user expectations and operational requirements. 

Decision management systems treat decisions as reusable assets and introduce technology at decision points to automate the decision-making process.  Decisions may be fully automated, or they may be presented as possible choices for a human to select.  

Increasingly, organizations who deal with financial services, banking and insurance are integrating decision-making software into their business process systems as well as their customer-facing applications. This approach is especially useful for high-volume decision-making because automating such decisions can enable more efficient, information-based and consistent responses to events.