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Strategic Capacity Planning for Efficient Operations Management

Learn about chapter 6 - Capacity Planning strategies: measurement, long-term and short-term strategies, break-even analysis, economies of scale, design, effective capacity, utilization, efficiency, demand management, complementary patterns, expansion approaches.

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Strategic Capacity Planning for Efficient Operations Management

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  1. Operations Management I Dirección de Operaciones I- English teaching Departamento de Organización de Empresas y Marketing Área de Organización de Empresas SECTION 2STRATEGIC DESIGN 3º GADI- 5º DG-ADI-DER 2013-2014 Slide presentation Chapter 6

  2. CHAPTER 6 CAPACITY PLANNING 6.1. Capacity Measurement 6.2. Long-Term Capacity Strategies 6.3. Short-Term Capacity Strategies 6.4. Break-Even Analysis: Comparison of Alternatives

  3. 6.1 Capacity • The throughput, or the number of units a facility can hold, receive, store, or produce in a period of time • Determines a large proportion of fixed costs • Determines if demand will be satisfied or facilities idle • Three time horizons

  4. * Long-range planning Add facilities Add long lead time equipment Intermediate-range planning Subcontract Add personnel Add equipment Build or use inventory Add shifts Schedule jobs Schedule personnel Allocate machinery * Short-range planning Modify capacity Use capacity Planning Over a Time Horizon *Limited options exist

  5. 6.1 Capacity • Capacity decisions are often influenced by economies and diseconomies of scale: • Economies of scale are achieved when the average unit cost of a good or service decreases as the capacity and/or volume of throughput increases • Diseconomies of scale occur when the average unit cost of the good or service begins to increase as the capacity and/or volume of throughput increases.

  6. 75 - Room Roadside Motel 25 - Room Roadside Motel 50 - Room Roadside Motel Average unit cost (dollars per room per night) Economies of scale Diseconomies of scale 25 50 75 Number of Rooms Economies and Diseconomies of Scale

  7. Design and Effective Capacity • Design capacity is the maximum theoretical output of a system in a given period under ideal conditions • Normally expressed as a rate • Effective capacity is the capacity a firm expects to achieve given current operating constraints • Often lower than design capacity • Safety capacity (or capacity cushion) is defined as an amount of capacity reserved for unanticipated events such as demand surges, materials shortages, and equipment breakdowns

  8. Utilization and Efficiency Utilization is the percent of design capacity achieved Utilization = Actual Output/Design Capacity Efficiency is the percent of effective capacity achieved Efficiency = Actual Output/Effective Capacity

  9. Bakery Example Actual production last week = 148,000 rolls Effective capacity = 175,000 rolls Design capacity = 1,200 rolls per hour Bakery operates 7 days/week, 3 -8 hour shifts Design capacity = (7 x 3 x 8) x (1,200) = 201,600 rolls Utilization = 148,000/201,600 = 73.4% Efficiency = 148,000/175,000 = 84.6%

  10. Capacity Considerations • Forecast demand accurately • Understanding the technology and capacity increments • Find the optimal operating level (volume) • Build for change

  11. Managing Demand • Demand exceeds capacity • Curtail demand by raising prices, scheduling longer lead time • Long term solution is to increase capacity • Capacity exceeds demand • Stimulate market • Product changes • Adjusting to seasonal demands • Produce products with complimentary demand patterns

  12. By combining both, the variation is reduced 4,000 – 3,000 – 2,000 – 1,000 – Snowmobile sales Sales in units Jet ski sales J F M A M J J A S O N D J F M A M J J A S O N D J Time (months) Complementary Demand Patterns

  13. 6.2 Long-Term Capacity Strategies • Firms must anticipate growth or decline in demand and plan capital investments • Complementary goods and services: goods and services that can be produced or delivered using the same resources available to the firm, but whose seasonal demand patterns are out of phase with each other • Design higher levels of self-service (customer labor) into operations

  14. (a) Leading demand with incremental expansion (b) Leading demand with one-step expansion New capacity New capacity Expected demand Expected demand Demand Demand (c) Capacity lags demand with incremental expansion (d) Attempts to have an average capacity with incremental expansion New capacity New capacity Expected demand Expected demand Demand Demand Approaches to Capacity Expansion

  15. 6.3 Short-Term Capacity Strategies • Managing Capacity by Adjusting Short-Term Capacity Levels • Add or share equipment • Sell unused capacity • Change labor capacity and schedules • Change labor skill mix • Shift work to slack periods

  16. 6.3 Short-Term Capacity Strategies • Managing Capacity by Shifting and Stimulating Demand • Vary the price of goods or services • Provide customers information • Advertising and promotion • Add peripheral goods and/or services • Provide reservations (a promise to provide a good or service at some future time and place)

  17. 6.4. Break-Even Analysis: Comparison of Alternatives • A means of finding the point at which costs equal revenues • Assumptions: • Only one product • Everything produced is sold • Cost and revenue are linear functions • Constant price sale and variable cost. Clear differentiation between fixed and variable costs • Fixed costs: costs that continue even if no units are produced • Variable costs: costs that vary with the volume of units produced • Contribution: difference between selling price and variable costs

  18. Alt. B Alt. A BEP_A X1 FA BEP_B FB 6.4 Break-Even Analysis: Comparison of Alternatives Total revenue: TR = P x P = price per unit Total cost: TC = V x + F x = number of units produced (or demand) Benefits: B = P x - (V x + F) V= variable cost per unit BEP = F / (p - V) F= fixed costs Graphic approach B (u.m) D < BEP_A Do nothing BEP_A  D < X1 Alt. A D = X1 Indifferent D > X1 Alt. B X (units)

  19. 6.4 Break-Even Analysis: Comparison of Alternatives • RANDOM DEMAND: • Discrete probability • Demand Expected • levels Probability Benefit demand and benefit • Xo Po Bo • X1 P1 B1 • .... ..... ..... • Xm Pm Bm • ..... ..... ..... • Xn Pn Bn DE = BE =

  20. 6.4 Break-Even Analysis: Comparison of Alternatives • Continuous probability: • B = P x - (V x + F)= P x - V x - F = (P - V) x - F • P (B > Bmín) = P[(P-V) x - F > (P-V) xmín - F = • Since P, V and F are constant • = P(x > xmín) = 1 - P(x  xmín) • Standarizing the variable xmín x ~ N(µ, ) • P (B > Bmín) = 1 - P (Z  Zmín= (xmín - µ )/)

  21. Size Annual Capacity Fixed Costs Unit Variable Costs Selling Price Big 7.000 1.800.000 1.500 2.000 Medium 5.000 1.200.000 1.600 2.000 Small 2.500 740.000 1.700 2.000 6.4 Break-Even Analysis: Comparison of Alternatives EXAMPLE: NORTEL Inc. is opening a new plant in Malaga. They have to decide regarding the capacity of the new plant between the following alternatives: With the information provided we want to determine which is the best option in the following cases: 1º) Using the graphic approach of the break-even analysis.

  22. Demand (Di) Probability (Pi) 1.000 0,05 2.000 0,15 3.000 0,25 4.000 0,25 5.000 0,15 6.000 0,1 7.000 0,05 6.4 Break-Even Analysis: Comparison of Alternatives EXAMPLE (cont.): 2º) Knowing different demand levels and their probability: 3º) Assuming demand is normally distributed with mean 4.000 and standard deviation 1.000, we will choose the alternative with the highest probability of achieving, at least, an expected benefit of 100.000 €

  23. 6.4 Break-Even Analysis: Comparison of Alternatives PROBLEM 1 MISOL, S.L. (LTD.) produces and installs prefabricated solar systems (domestic solar equipments), whose objective is to produce warm water for domestic purposes. Currently, there are several points still to decide in the enterprise, one of them related to the capacity of a new production plant located in Seville. Therefore, there are two options: Installing a new production plant in Mairena del Aljarafe, with a capacity of 3,000 upy (units per year). Installing a new production plant in Osuna, with a capacity of 2,300 upy. The sale price of an equipment is known to be of € 4,000 and the main costs are as follows:

  24. 6.4 Break-Even Analysis: Comparison of Alternatives PROBLEM 1 (cont.) We would like to find out: Using the break-even point graphic, which of the plants would be more appropriate for each demand volume? Assuming that the demand acts like a continuous variable, following a normal distribution of average 2500 and standard deviation 400, what is the probability that this enterprise reaches a maximum profit of € 400,000 in the Mairena del Aljarafe production plant?

  25. 6.4 Break-Even Analysis: Comparison of Alternatives PROBLEM 2 At A SU GUSTO, S.A., a factory of jet planes for celebrities, their facilities aren’t enough for their purposes. That’s why a specialised consultant has been asked to produce a report on the best option for the board: A factory in Seville, smaller but modern, with a maximum production capacity of 50 units per year, though with relatively small fixed costs: 500 million € per year. Each unit cost would raise to 75 million €. A factory in Huelva, with a production capacity of 100 units per year, but 2 billion (2,000 million) € as yearly fixed costs and 50 million € as variable costs.

  26. 6.4 Break-Even Analysis: Comparison of Alternatives PROBLEM 2 (cont.) Knowing that, in both cases, the sales price for each jet plane is 100 million €, you have to propose to A SU GUSTO, S.A. the best option according to the expected demand volume. For this purpose, the technique of the break-even point graphic is to be used. The marketing department reports to A SU GUSTO, S.A. that the expected demand of jet planes acts like a continuous variable following a normal distribution of average 26 and standard deviation 20. What is the probability of not being able to fulfill all the demands of the clients if they choose the option of Seville?

  27. 6.4 Break-Even Analysis: Comparison of Alternatives PROBLEM 3 Café 1492, Inc. (S.A.) is thinking on increasing its capacity due to the extraordinary outcomes. Therefore, there are two options: Option 1: setting up a new café in a different location with a capacity of 13,600 customers per year. Its estimations are € 60,000 per annum for fixed costs and € 7 as unitary variable cost. This option would lead to the shutdown of the current café. Option 2: increasing the current capacity in the same location, enabling a night shift. This means assisting 13,900 customers per year more than option 1. The night-shift work would increase fixed costs €40,000 more. In the café business, there are different sorts of products. For the sake of this case, a representative equivalent value would be € 12 per product. We would like to find out: Using the break-even point graphic, which option would be more appropriate for each demand value?

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