Chapter 1

1. Chapter 1 Creative operations management A Decision- Making Approach

2. What is Operations Management? • Operations management is concerned with managing the resources that directly produce the organisations service or product. • The resources will usually consist of people, materials, technology and information, but they may go wider than this. • These resources are brought together by a series of processes so that they are utilized to deliver the primary service or product.

3. What is Operations Management? Operations management is an area of business that is concerned with the production of goods and services, and involves the responsibility of ensuring that business operations are efficient and effective. It is also the management of resources, and the distribution of goods and services to customers.

4. What is Operations Management? Operations management is also defined as a system. In such a system, material, machines, labor, management, and capital, are transformed into outputs, like products, goods, and services. Requirements and feedback from customers are used to adjust factors in the transformation process, which may also alter the inputs.

5. OPERATIONS MANAGEMENT

6. Then, Operation Management has the following objectives to be achieved: • Improving efficiency and quality • Solving business problems using model-based approaches • Increasing profitability by managing the operations of a firm - producing and delivering products and services • When the operations are managed well then: • Productivity is high • Quality is high • Costs are low • Profitability is high

7. Managerial Decision Making The work of operations managers consists largely in making decisions and solving problems that arise in the production of goods and services. It involves: • Choosing issues that require attention. • Setting goals. • Finding or designing suitable course of action. • Evaluating and choosing among alternative actions.

8. Creativity Tools for Operations Management • The problems and processes of operations management require creative solutions, which involve qualitative and quantitative analysis of the business operations. • So proactive quantitative and qualitative techniques are needed to provide a dynamic analysis not a static analysis

9. The aim of this course is to use one of the powerful computational tool, MS Excel to analyze operations management problems in order to improve and facilitate managerial decision making. • Excel is not just a powerful computational tool, it is a creative technique to develop better and more competitive Operational Management Systems.

10. Managerial Decision MakingDefinition A multi-step process through which problems are recognized (identified), diagnosed, and defined;

11. Managerial Decision MakingTypes • Programmed Decision: • A highly routine decision made according to pre-established organizational policies and procedures. • Non-Programmed Decision: • A decision made about a highly novel problem for which there is no pre-specified course of action.

12. Managerial Decision MakingProcess Systematic Decision Making Process (Nobel laureate Herbert A. Simon, 1997) classified decision making into three phases that reflect and idealized notion of the flow of decision making: • Intelligence • Design • Choice

13. Intelligence Phase (primarily qualitative process) Cluster chart Problem identification Model flowchart Design Phase (primarily quantitative process) Model – mathematical or worksheet Option generator Optimizer Choice Phase Decision

14. In general Intelligence Phase consists of four steps • Problem Detection (Identification) • Problem Definition • Problem Classification • Structural Modeling

15. The Three Phases of Decision Making The Intelligence Phase • Data are raw material (facts) • Data need to be filtered/refined and then treated in some way (i.e.;sorting, classifying and aggregating and averaging) to become useful information. • Information is data that are or may be useful to manager in their job. It is the processed data or the meaning that human beings assign or extract from data. • Intelligence does not refer to raw data or plain, unanalyzed information, but includes both evaluations and conclusions. It is the outcome of the meshing and reconciliation of a set of information. Information is the raw material for intelligence.

16. The Three Phases of Decision Making The Intelligence Phase • Problem occurs because of dissatisfaction with organization system. Dissatisfaction is the result of difference between what it expected and what it has been occurred.

17. The Three Phases of Decision Making The Intelligence Phase • The intelligence phase begins with extensive searching and gathering of information. • The mangers need to spend a significant part of their time in intelligence- related activities because they need to have some knowledge to solve a problem or make a decision. These includes knowledge of the relevant facts of situation and the problem, managerial preferences, priorities, goals, and the alternatives available to management.

18. The Three Phases of Decision Making The Intelligence Phase Systems and Environments • The world in which managers operate can be divided into two main parts - their system and its environment. • The distinction between the system and the environment is clear • The system consists of those things over which the manager has control • The environment being all else of relevance. The environment can be further subdivided into local and remote environments.

19. Remote Environment Local Environment System

20. Local Environment That part of the environment where the manager can exert a significant influence or exercise indirect. Moreover, the performance of the managers and organizational performance and productivity has a significant effect on this environment. Example: retailer,competition, size of car park, supplier’s delivery schedules, warehousing Remote Environment That part of the environment over which the managers have no influence or control. However, this environment has a significant impact on the managers and their system and the whole organization. Example of direct effect: monetary exchange rates and government legislation, Legal opening hours, health regulation, VAT, Bank lending rules, Import Duty

21. Some useful qualitative techniques for identifying problem and creating or finding alternatives • Managerial scenario • Brainstorming

22. Scenario Management Scenario in general is a statement of assumptions about the operating environment of a particular system at a given time. It describes decision variable, uncontrollable (output) variables, and parameters for specific modeling situation. It may also provides the procedures and constraints for the modeling itself.

23. Scenario Management Managerial Scenario : is a managerial view of the world. It’s an outline of the world in which the managers are currently operating and in which they think they will be operating in the future. Local scenario is the portion of the managerial scenario brought into focus under pressure from an altering stimulus. It is the portion of the scenario used to define the issue (problem or opportunity) once it has been detected. A local scenario is likely to be wider than an initial consideration of the single in-focus issue might suggest, but narrower than the whole scenario.

24. Brainstorming Techniques Is designed to help people generate alternatives for problem solving without prematurely evaluating. The purpose of brainstorming is to enhance creativity through team discussion. Certain procedural rules are enforced to permit all team members to express their ideas and to reduce critical evaluations that might inhibit creativity.

25. Mind Map: A mind map is a diagram used to represent words, ideas, tasks or other items linked to and arranged around a central key word or idea. It is used to generate, visualize, structure and clarify ideas, and as an aid in study, organization, problem solving, decision making and writing.

28. Structural Modeling There are three main steps to structural modeling: 1- Identification of the managerial variables in the local scenario 2- Identification of the constraints on the values that variables can take 3- Formalization of the local scenario by expressing the broad relationships between managerial variables, including the associated constraints

29. 1- Identification of the managerial variables Decision variables (independent) : are factors whose values the manager can change and control. Output variables (dependent): are the dimensions along which managers would measure themselves and be measured by others. So they reflect the level of effectiveness of the system. They indicate how well the system attains its goals. Output variable may be quantitative and reasonably defined variables such as turnover and profit or more qualitative one such as morale and flexibility. Environmental variables (local or remote): its an important variables in the system environment which has a significant impact on it.

30. 2- Identification of the constraints on the values that variables can take Constraints are limitations on the values that variables can take. Constraints can be : 1- Self-imposed: a constraint arising within the system. this type of constraint can be either direct(limits on the decision variables) or indirect (limits on the output variables) 2- Environmental-imposed: an environmental imposition on the system from outside. It might be physical (tangible) or it might be more behavioral (intangible)

31. The Three Phases of Decision Making The Intelligence Phase At the end of this phase, the objectives, facts, data, variables and parameters of the situation are identified, classified and often than organized in a cluster chart or text-based cluster chart.

32. The Three Phases of Decision Making The Design Phase • The focus of the design phase is the development of the decision model describing the problem. • Decision models selectively describe the managerial situation • Decision models identify decision variables • Decision models identify performance measure that reflect objective • The decision models should be constructed, tested and validated for feasibility which means compared with and tested against objectives and goals.

33. The Three Phases of Decision Making The Design Phase • A major output of the design phase is a list of scenarios to evaluate. These scenarios are combinations of values for each parameter in the model or various options to evaluate. • Option Generation : is the process of generating number of scenarios for certain model in the design phase. • The option generation process is accomplished by reviewing the results of scenarios so that the manager can answer such question as “ What happens if prices go up?” or “ What happens if volume goes down?”

34. The Three Phases of Decision Making The Choice Phase • The option and scenario generating systems developed in the design phase allow the managers to survey many alternative scenarios and thus facilitate the choice. • Reality Checks: decision makers must perform a reality check to check if the model or system can generate solutions that conform to the actual situation. If the model is not adequate to make the choice, the design phase, and possibly the intelligence phase, must be repeated.

35. The Three Phases of Decision Making The Choice Phase • Optimization: • Finding the best or optimal solution. For example finding the highest profit or sale or stock price. Or the minimum environmental damage. • Optimal solutions is a feasible solution that gives the largest value of the objective function (in maximizing situation) or smallest value of the objective function (in a minimizing situation). • Optimum solutions can be found using a mathematical optimization techniques of operations research and management science.

36. Spreadsheet Modeling For Business Decision Making Analysis

37. Type of Decision Operational Control Managerial Control Strategic Planning Structured Accounts receivable, order entry Budget analysis, short-term forecasting, personal reports, make-or-buy Financial management, warehouse location, distribution system Management information system, operations research models, transaction processing Semi-structured Production scheduling, inventory control Credit evaluation, budget preparation, plant layout, project scheduling, reward system design Building new plant, mergers and acquisitions, new product planning, quality assurance planning DSS, KMS Unstructured Selecting a cover for magazine, buying software, approving loans Negotiating, recruiting an executive, buying hardware New technology development, social responsibility planning IDSS, ES, Neural network Technology Support Needs Management information system, management science Management science, DSS, ES, EIS,SCM EIS, ES, neural networks, KMS Framework for IT support for Decision Making

38. Why Spreadsheet ? • Spreadsheet packages are one of the MSS. They are used specially as DSS or MIS. Some example of available spreadsheet packages are Excel, Lotus 123, and SPSS. • The spreadsheet packages provide a rapid, ad-hoc access to a set of pre-structured data to support a regular operational task. • It also provides straightforward analysis, reports and graphical output for predefined situations.

39. Spreadsheet Components • A spreadsheet model consists of logic model, data model and human-computer interface. • The logic model is composed of the selected factors and the • relationships (rules of calculation) according to which the data • are used to derive results. • The data model consists of the data needed to start the model off. • Human-computer interface: the display of results- in tables or • graphs- is through a ‘results interface’

40. The building blocks of logic models 1- Input Factors and Calculated Variables 1- Revenue = sales x price Calculated variableInput value ) model factors Output variable Decision variables } managerial variable Environmental variable is the price of the single competitor’s product 2- Revenue = sales x price sales = 50 x ( competitors price/price)^2 x adv. spend Input factor : their values would be input to the logic model (values derived outside the model) Calculated variables: its value would be calculated within the model

41. The building blocks of logic models 2- Parameters In logic modelling a parameter is a factor whose value is held constant over a given period of time or during the exploration of given relationships. Revenue = Sales x Price Sales = 50 x ( Competitors price/Price)^2 x Adv price Fixed (Parameter) changed Explore the influence of these changes on the calculated variable (Revenue)

42. The building blocks of logic models 3- Constants and Coefficients There are two types of Constants: 1- Constant whose values are fixed by definition Ex: 7 days in a week, 24 hours in a day

43. The building blocks of logic models 3- Constants and Coefficients (continued) 2- Constant whose values are known to vary, but where this variability is relatively trivial to the issue of concern and thus when it is appropriate to treat their values as unchanging. Example: cost of product1 = X1, cost of product 2 = 20 times of product1 X1 20*X1 Constant

44. The building blocks of logic models 3- Constants and Coefficients (continued) Coefficients : represent a relationship between two or more factors and are thus ratios. Their values may have been defined externally. An example is a govt decree on the minimum floor space per employee in commercial buildings Another example is used in universities to relate one part-time student to one-third of a full-time student.

45. The building blocks of logic models 4- Intermediate Variables Intermediate variables: are variables needed in order to simplify the development and maintenance of the model. Revenue = Sales x Price Price ratio = competitors price/ price Sales = 50 x price ratio ^2 x Adv Spend Intermediate variable

46. Summary of the building blocks used in logic models • Variable: A factor whose values are frequently changing. • Parameter: a factor whose value is held constant over a period of spreadsheet exploration • Constant: a) a factor whose value is unchanging and has been defined to be what it is. b) A factor where the variability in its value is insignificant or extremely small. • Coefficient: a factor representing a relationship between two or more factors.

47. Managerial Variables and Modeling Factors Managerial variables and modeling factors are often the same. However, sometimes they are different and its very difficult to find a direct link between them. The managerial variables are the decision, environmental and output variables. The model factors are the input factors, calculated factors, and any intermediate variables that model requires.

48. Managerial Variables and Modeling Factors What value will an output variable (Revenue) take if a specific value is given to a decision variable (Price)? Revenue = Sales * Price Output variable = Calculated variable Decision variable = Input factors What value should price (decision variable) take in order that Revenue (Output variable) has a specific value? Price = Revenue / Sale Decision variable = Calculated variable Output variable = Input factors

49. Modeling require the model factors ( input factor, calculated and intermediate variables) to be viewed in a way that different from that in scenarios ( managerial decision and output variable) and this may affect the way in which a model is constructed.

50. Types and relationships between the building blocks A relationship is a link between variables, parameters, coefficients and constants. It can be in three different forms: • Equality, (Equation) Revenue = sales * price • Inequality No of emp req.<> > < crew members * no of machines • Conditional relationship If profit > 0 then Tax = 40% of Profit else Tax = 30% of Profit