Capacity Planning For Products and Services

Learning Objectives Explain the importance of capacity planning. Discuss ways of defining and measuring capacity. Describe the determinants of effective capacity. Discuss the major considerations related to developing capacity alternatives. Briefly describe approaches that are useful for evaluating capacity alternatives

Capacity Planning Capacity is the upper limit or ceiling on the load that an operating unit can handle. Capacity also includes Equipment Space Employee skills The basic questions in capacity handling are: What kind of capacity is needed? How much is needed? When is it needed?

Importance of Capacity Decisions Impacts ability to meet future demands Affects operating costs Major determinant of initial costs Involves long-term commitment Affects competitiveness Affects ease of management Globalization adds complexity Impacts long range planning

Capacity Design capacity Effective capacity Actual output maximum output rate or service capacity an operation, process, or facility is designed for Effective capacity Design capacity minus allowances such as personal time, maintenance, and scrap Actual output Rate of output actually achieved--cannot exceed effective capacity.

Efficiency and Utilization Actual output Efficiency = Effective capacity Utilization = Design capacity Both measures expressed as percentages (%)

Efficiency/Utilization Example Design capacity = 50 trucks/day Effective capacity = 40 trucks/day Actual output = 36 units/day Actual output = 36 units/day Efficiency = = 90% Effective capacity 40 units/ day Utilization = Actual output = 36 units/day = 72% Design capacity 50 units/day

Determinants of Effective Capacity Facilities (design, location, layout, environment) Product and service factors (design, product mix) Process factors (quantity capacity, quality capacity) Human factors (job content, job design, training & experience, motivation, compensation, learning rate, absenteeism and turnover) Policy factors Operational factors (scheduling, materials management, QA, maintenance, breakdown) Supply chain factors External factors (standard, safety regulation, unions, pollution control standard)

Strategy Formulation Capacity strategy for long-term demand patterns involve; Growth rate and variability of demand Cost of building and operating facilities of various size Rate and direction of technology changes Behavior of competitors Availability of capital and other inputs

Key Decisions of Capacity Planning Amount of capacity needed Capacity cushion (100% - Utilization) Timing of changes Need to maintain balance of the system Extent of flexibility of facilities and workforce Capacity cushion – extra demand intended to offset uncertainty

Steps for Capacity Planning Forecast future capacity requirements Evaluate existing capacity Identify alternatives Conduct financial analysis Assess key qualitative issues Select one alternative Implement alternative chosen Monitor results

Forecasting Capacity Requirements Long-term vs. short-term capacity needs Long-term relates to overall level of capacity such as facility size, trends, and cycles Short-term relates to variations from seasonal, random, and irregular fluctuations in demand

Calculating Processing Requirements Working 8-hour shift, 250 day/year Annual capacity = 2000 hours Machine required to handle these job = 5,800 /2,000 = 2.90 Machine required to handle these job = 3 machines

Planning Service Capacity Need to be near customers Capacity and location are closely tied Inability to store services Capacity must be matched with timing of demand Degree of volatility of demand Peak demand periods

In-House or Outsourcing (Make or Buy) Available capacity Expertise Quality considerations Nature of demand Cost Risk

Developing Capacity Alternatives Design flexibility into systems Take stage of life cycle into account Take a “big picture” approach to capacity changes (to focus bottleneck) Prepare to deal with capacity “chunks” Attempt to smooth out capacity requirements Identify the optimal operating level (economy of scale)

Company Strategy/Issues Drive-through restaurants Product Life Cycle Introduction Growth Maturity Decline Company Strategy/Issues Best period to increase market share R&D engineering is critical Practical to change price or quality image Strengthen niche Poor time to change image, price, or quality Competitive costs become critical Defend market position Cost control critical Internet Flat-screen monitors Sales DVD CD-ROM Drive-through restaurants Fax machines 3 1/2” Floppy disks Color printers

Product Life Cycle Introduction Growth Maturity Decline OM Strategy/Issues Product design and development critical Frequent product and process design changes Short production runs High production costs Limited models Attention to quality Forecasting critical Product and process reliability Competitive product improvements and options Increase capacity Shift toward product focus Enhance distribution Standardization Less rapid product changes – more minor changes Optimum capacity Increasing stability of process Long production runs Product improvement and cost cutting Little product differentiation Cost minimization Overcapacity in the industry Prune line to eliminate items not returning good margin Reduce capacity

Bottleneck Operation Machine #1 Machine #2 Bottleneck Operation Bottleneck operation: An operation in a sequence of operations whose capacity is lower than that of the other operations Bottleneck Operation Machine #1 Machine #3 Machine #4 10/hr 30/hr 30/hr Machine #2

Bottleneck Operation Bottleneck Operation 1 20/hr. Operation 2 10/hr. Maximum output rate limited by bottleneck

Production units have an optimal rate of output for minimal cost. Minimum cost Average cost per unit Rate of output Minimum average cost per unit

Economies of Scale Economies of scale Diseconomies of scale If the output rate is less than the optimal level, increasing output rate results in decreasing average unit costs Diseconomies of scale If the output rate is more than the optimal level, increasing the output rate results in increasing average unit costs

Economies of Scale Small Medium plant Large plant Output rate Minimum cost & optimal operating rate are functions of size of production unit. Small plant Average cost per unit Medium plant Large plant Output rate

Evaluating Alternatives Cost-volume analysis Break-even point Financial analysis Cash flow Present value Decision theory Waiting-line analysis

Cost-Volume Relationships Amount ($) Total cost = VC + FC Total variable cost (VC) Fixed cost (FC) Q (volume in units)

Cost-Volume Relationships Total revenue Amount ($) Q (volume in units)

Cost-Volume Relationships Profit Total revenue Amount ($) Total cost BEP units Q (volume in units) BEP = Break Even Point

Break-Even Problem with Step Fixed Costs Quantity FC + VC = TC Step fixed costs and variable costs. 1 machine 2 machines 3 machines

Break-Even Problem with Step Fixed Costs $ BEP 3 BEP 2 TC TC 3 TC 2 TR 1 Quantity Multiple break-even points

Assumptions of Cost-Volume Analysis One product is involved Everything produced can be sold Variable cost per unit is the same regardless of volume Fixed costs do not change with volume Revenue per unit constant with volume Revenue per unit exceeds variable cost per unit

Financial Analysis Cash Flow - the difference between cash received from sales and other sources, and cash outflow for labor, material, overhead, and taxes. Present Value - the sum, in current value, of all future cash flows of an investment proposal.

Decision Theory Helpful tool for financial comparison of alternatives under conditions of risk or uncertainty Suited to capacity decisions

Waiting-Line Analysis Useful for designing or modifying service systems Waiting-lines occur across a wide variety of service systems Waiting-lines are caused by bottlenecks in the process Helps managers plan capacity level that will be cost-effective by balancing the cost of having customers wait in line with the cost of additional capacity

Product and service design Decision Theory Decision Theory represents a general approach to decision making which is suitable for a wide range of operations management decisions, including: Capacity planning Product and service design Location planning Equipment selection

Decision Theory Elements A set of possible future conditions exists that will have a bearing on the results of the decision A list of alternatives for the manager to choose from A known payoff for each alternative under each possible future condition

Decision Theory Process Identify possible future conditions called states of nature Develop a list of possible alternatives, one of which may be to do nothing Determine the payoff associated with each alternative for every future condition If possible, determine the likelihood of each possible future condition Evaluate alternatives according to some decision criterion and select the best alternative

Causes of Poor Decisions Bounded Rationality The limitations on decision making caused by costs, human abilities, time, technology, and availability of information

Causes of Poor Decisions (Cont’d) Suboptimization The result of different departments each attempting to reach a solution that is optimum for that department

Decision Process Identify the problem Specify objectives and criteria for a solution Develop suitable alternatives Analyze and compare alternatives Select the best alternative Implement the solution Monitor to see that the desired result is achieved

Decision Environments Certainty - Environment in which relevant parameters have known values Risk - Environment in which certain future events have probable outcomes Uncertainty - Environment in which it is impossible to assess the likelihood of various future events

Decision Making under Uncertainty Maximin - Choose the alternative with the best of the worst possible payoffs Maximax - Choose the alternative with the best possible payoff Laplace - Choose the alternative with the best average payoff of any of the alternatives Minimax Regret - Choose the alternative that has the least of the worst regrets

Decision Making Under Risk Risk: The probability of occurrence for each state of nature is known Risk lies between the extremes of uncertainty and certainty Expected monetary value (EMV) criterion: The best expected value among alternatives Determine the expected payoff of each alternative, and choose the alternative with the best expected payoff

Decision Trees Decision tree: a Schematic representation of the available alternatives and their possible consequences. Useful for analyzing situations that involve sequential decisions

Format of a Decision Tree State of nature 1 B Payoff 1 State of nature 2 Payoff 2 Payoff 3 2 Choose A’1 Choose A’2 Payoff 6 Payoff 4 Payoff 5 Choose A’3 Choose A’4 Choose A’ 1 Decision Point Chance Event

Example of a Decision Tree Low demand (0.4) B 40M High demand (0.6) 55M 2 Do nothing Expand 70M 10M 50M Reduce price Build small Build large 1 Decision Point Chance Event Overtime 50M

Expected Value of Perfect Information Expected value of perfect information: the difference between the expected payoff under certainty and the expected payoff under risk Expected value of perfect information Expected payoff under certainty Expected payoff under risk - =

Sensitivity Analysis Sensitivity Analysis: Determining the range of probability for which an alternative has the best expected payoff Useful for decision makers to have some indication of how sensitive the choice of an alternative is to changes in one or more of these values

Example ตารางแสดง Payoff ของแต่ละทางเลือก State of nature #1 #2 #1 #2 Alternative A 4 12 B 16 2 C 12 8 จงเขียนภาพแสดง Sensitivity

Sensitivity Analysis A B C A best C best B best #1 Payoff #2 Payoff 16 14 12 10 8 6 4 2 16 14 12 10 8 6 4 2 Sensitivity analysis: determine the range of probability for which an alternative has the best expected payoff