1. Operations Management (2) Topic 2 Prof. Upendra Kachru Aggregate Planning

2. Operations Management Prof. Upendra Kachru Planning Hierarchy LevelCustomerBusiness Activity StrategicCorporate/Senior OM Executives Competitive Strategy Product Innovation Supply Chain Structuring Capital Budget Process FunctionalRegional/Plant LevelMarketing Strategy Plant Utilization Strategy Capacity Budgeting Aggregate Planning Organizational Control OperationalOperations LevelCRM Procurement Logistics MPS and MRP Managing Workforce

3. Operations Management Prof. Upendra Kachru Planning Hierarchy Time horizon in years Current Plans Aggregate Plans Strategies & Facilities Types of Decision Short term Long term Planning Medium term

4. Operations Management Prof. Upendra Kachru The aggregate plan links strategic goals and objectives of the organization with the plans for individual products, services and their various components. WHAT IS AGRREGATE PLANNING?

5. Operations Management Prof. Upendra Kachru It determines the course the organization takes in the medium term, with the following in mind:  Market Inputs (demand forecasts and/or actual orders);  Capability Specifications and Performance Metrics; and  Resource Availability Aggregate Planning has to firstly link strategic goals and objectives with the plans for individual products by transforming its understanding of the market into a set of capability specifications. i.e. what business processes must do to meet the needs and expectations of customers. Nature of Aggregate Planning

6. Operations Management Prof. Upendra Kachru The business processes that are involved are as follows:

7. Operations Management Prof. Upendra Kachru Maximize  profits  customer service  utilization of plant and equipment Minimize  inventory investment  changes in production rates  changes in workforce levels Objectives of Aggregate Planning

8. Operations Management Prof. Upendra Kachru The Aggregate Planning Process Aggregate plan Materials Supplier capabilities Storage capability Materials availability Engineering New Products Product design changes Machine standards Human Resources Labor-market conditions Training capacity Accounting and Finance Cost data Financial condition of firm Operations Current machine capacities Plans for future capacities Workforce capacities Current staffing level Distribution and marketing Customers needs Demand forecasts Competition behavior

9. Operations Management Prof. Upendra Kachru Aggregate Planning System - Inputs Planning for production External capacity Competitors’ behavior Raw material availability Market demand Economic conditions Current physical capacity Current workforce Inventory levels Activities required for production External to firm Internal to firm

10. Operations Management Prof. Upendra Kachru Business Environment  Market Orientation  Time Focused Environment  Product Flexibility Focused Environment

11. Operations Management Prof. Upendra Kachru Make-To-Stock (MTS): Produce to buildup inventory and then use that inventory later to meet demand. This makes the aggregate plan critical to the business. Make-To-Order (MTO): Service organizations and job shops provide such Products. Assemble-to-Order (ATO), Engineer-to-Order (ETO): Aggregate planning has to use actual or projected orders to plan production activities. Market Orientation

12. Operations Management Prof. Upendra Kachru  Right inventory stocking decisions  Efficient, timely feedback  Excellence in collecting and analyzing data  Sufficient resources  Sufficient resources at the right location Time Focused Environment

13. Operations Management Prof. Upendra Kachru  Sufficient Goods at convenient place  Good Forecast  Short change over times  Reduction in manufacturing lead time Product Flexibility Focused Environment

14. Operations Management Prof. Upendra Kachru 14 Aggregate Demand and Aggregate Capacity 0 2000 4000 6000 8000 10000 JanFebMarAprMayJun 4500 5500 7000 10000 8000 6000 0 2000 4000 6000 8000 10000 JanFebMarAprMayJun 4500 4000 9000 8000 4000 6000 Suppose the figure to the right represents forecast demand in units Now suppose this lower figure represents the aggregate capacity of the company to meet demand What we want to do is balance out the production rate, workforce levels, and inventory to make these figures match up

15. Operations Management Prof. Upendra Kachru A Chase Strategy is a strategy aimed at adjusting capacity in anticipation of demand. You are "chasing demand" by regulating capacity to the demand doing it as dynamically and quickly as you can. Chase Strategy

16. Operations Management Prof. Upendra Kachru  Using part-time employees  Varying production rates through overtime or idle time  Maximizing efficiency through training, work scheduling, cross-training, use of technology, etc.  Increasing involvement of consumer in delivery of service  Keeping Bottleneck Resources Busy  Sharing capacity with other divisions/firms  Outsourcing Chase Strategy

17. Operations Management Prof. Upendra Kachru Level Strategy Level Strategy is a strategy where you maintain a constant capacity over a period of time, irrespective of fluctuations in demand. This strategy is used when skill level, the training required, or the cost of hiring people and terminating them is high.

18. Operations Management Prof. Upendra Kachru  Changing Product Mix  Increasing Machine Product Rate  Improving Quality  Increasing Product Yield  Increasing Motivation  Increasing Employee Involvement  Changing Inventory Levels  Planning for future expansion Level Strategy

19. Operations Management Prof. Upendra Kachru Mixed Strategy In a “mixed” strategy, the organization combines strategies, in view of its specific and unique requirements. Mixed Strategy

20. Operations Management Prof. Upendra Kachru 20 Chase and Level Strategy Costs Production CostRs. 350/unit Lost SalesRs. 1000/unit per mo. Inventory Carrying CostRs. 10/unit per mo. Subcontracting CostsRs. 600/unit Layoff costsRs. 7000/worker Hiring CostRs. 3500/worker Beginning Workforce Level20 workers Capacity per Worker50 units/mo. Beginning inventory700 units Closing Inventory100 units Suppose we have the following unit demand and cost information: Demand/moJanFebMarAprMayJun 100012001500190018001600

21. Operations Management Prof. Upendra Kachru Demand JanFebMarAprMayJun Production/mo100012001500190018001600 Inventory 700700700700700700 Hire/Fire0+4+6+8-2-4 Given is the demand information below: JanFebMarAprMayJun Production350420525665630560 Inventory777777 Hire/Fire01421281428 Total35779813512051270323297 1000x350=Rs. 350000 700x107000x2= 14000 Cumulative cost information is given in ‘000 below: 50x(20+4+6)= 1500 Chase Strategy

22. Operations Management Prof. Upendra Kachru Demand JanFebMarAprMayJun Production/mo140014001400140014001400 Inventory 110013001200700300100 Hire/Fire00000-0 Given is the demand information below: JanFebMarAprMayJun Production4909801470196024502940 Inventory1113127347 Hire/Fire000000 Total52910321534203125243015 Chase Strategy costs Rs.3,297,000 1100x10 Cumulative cost information is given in ‘000 below: 1300+1400- 1500=1200 Level Strategy

23. Operations Management Prof. Upendra Kachru Managing Demand There are at least five basic options that a firm has to manage demand:  Differential Pricing  Develop Complementary Services to address imbalance  Use Reservation System  Variable Hours Strategy  Coordination with other Organizations

24. Operations Management Prof. Upendra Kachru OPTIONADVANTAGESDISADVANTAGESCOMMENTS Changing inventory level Changes in human resources are gradual or none; no abrupt production changes. Inventory holding costs. Shortages, resulting in lost sales, may occur if demand increases. This applies mainly to production, not service, settings. Varying work-force size by hiring or layoffs Avoids the costs of other alternatives Hiring, layoff, and training costs may be significant Used where many unskilled people seek extra income. Varying production rates through over time or idle time Matches seasonal fluctuations without Hiring / training costs Overtime premiums; tired workers; may Not meet demand. Allows flexibility within the Aggregate plan. Subcontracting Permits flexibility and smoothing of the firm's output. Loss of quality control; reduced profits; loss of future business. Applies mainly in production settings. Using part-time workers Is less costly and more flexible than full-time workers. High turnover / training costs; quality suffers; scheduling difficult. Good for unskilled jobs in areas with large temporary labor pools. Influencing demand. Tries to use excess capacity. Discounts draw new customers. Uncertainty in demand. Hard to exactly match demand to supply. Creates marketing ideas. Overbooking used in some businesses. Back-ordering. May avoid overtime. Keeps capacity constant. Customer must be willing to wait, but goodwill is lost. Many companies backlog. Counter seasonal product and service mixing. Fully utilizes resources; allows stable work force. May require skills or equipment outside firm's areas of expertise. Risky finding products or services with opposite demand patterns.

25. Operations Management Prof. Upendra Kachru  Graphical and charting procedure.  Linear programming.  Mathematical modeling using Linear Decision Rules  Management Coefficient Models  Production Switching Heuristics  Simulation Methods for Aggregate Planning

26. Operations Management Prof. Upendra Kachru This is a trial-and-error method, assisted by spreadsheets. In general, the graphical and charting method follows five steps:  Determine the demand in each period.  Determine what the capacity is for regular time, overtime, and subcontracting each period.  Find the labor costs, hiring and layoff costs, and inventory holding costs.  Consider company policy that may apply to the workers or to stock levels.  Develop alternative plans and examine their total costs. Graphical & Charting Method

27. Operations Management Prof. Upendra Kachru Graphical & Charting Method The method requires the planner to specify a planning horizon and secure aggregate demand forecasts Second, the decision variable such as size of workforce, output rate, overtime or idle time, inventory level, sub- contracting, etc., have to be explicitly identified. Third, all models require the relevant costs, including costs of wages, hiring/layoff, overtime, inventory, etc., to be specified

28. Operations Management Prof. Upendra Kachru Problem: Ramson & Co. MonthExpected demand Production daysDemand per day January10002245 Feb8001844 March12002157 April12002157 May15002268 June11002055 Ramson & Company, a Delhi company, manufactures designer furniture for offices. Mr. Ram has developed monthly forecasts for executive chairs and presented the period January – June in the table below.

29. Operations Management Prof. Upendra Kachru Inventory carrying costRs. 10 unit/month Subcontracting cost (marginal cost per unit above in-house manufacturing cost) Rs. 100/unit Average pay rateRs. 20/hour (Rs. 160/day) Overtime pay rateRs. 40/hour (above 8 hours) Labor-hours to produce a unit6 hours/unit Cost of increasing production rate (hiring)Rs. 100/unit Cost of decreasing production rate (layoffs)Rs. 150/unit Cost Information for Manufacture of Executive Chairs

30. Operations Management Prof. Upendra Kachru Forecast vs. Demand 6800/124 = 54.838

31. Operations Management Prof. Upendra Kachru Plan 1: Level Strategy - Production is equal to Average Demand Month Production at 55 units/day Demand forecastEnding inventory January1,2101000210 February990800400 March1,1551200355 April1,1551,200310 May1,2101,50020 June1,100 20 Total6,82068001,315 COSTSCALCULATIONS Inventory carryingRs. 13,150 = 1,315 units carried x Rs. 10 / unit Regular time laborRs. 833,280 = 42 workers x Rs. 160 / day x 124 days Other costs0 Total costRs. 846,430

32. Operations Management Prof. Upendra Kachru Plan 2: Mixed Strategy- Constant Workforce at lowest demand level and meet additional demand through Outsourcing To produce 44 units/day in-house, 33 workers are needed. All other demand is met by subcontracting, which is thus required in every month. No inventory costs are incurred. In-house production = 44 units/day x 124 production days = 5,456 units Subcontract units = 6,800 - 5,456 = 1,344 units COSTSCALCULATIONS Regular-time labor Rs. 654,720 = 33 workers x Rs. 160 per day x 124 days SubcontractingRs. 134,400 = 1,344 units x Rs. 100 per unit Total costRs. 789,120

33. Operations Management Prof. Upendra Kachru Plan 3: Chase Strategy – Hire and layoff workers to meet the exact demand each month. Month Forecast (units) Prod Rate Production Cost) Hiring costLayoff costTotal Cost Jan100045Rs. 118,800 Feb80044Rs. 95,040Rs. 2,700Rs. 97,740 Mar120057Rs. 143,640Rs. 170,940 Apr1,20057Rs. 143,640Rs. 27,300Rs. 143,640 May1,50068Rs. 179,520Rs. 24,200Rs. 203,720 June1,10055Rs. 139,200Rs. 3,900Rs. 143,100 6800Rs. 819,840Rs. 51,500Rs. 6,600Rs. 877,940 44 x 6 x Rs.20 x 18 = Rs. 95,040 Rs. 150 x 13 x 20 = Rs. 3,900 Rs. 100 x 13 x 21= Rs. 27,300

34. Operations Management Prof. Upendra Kachru Comparison of Different Plans CostPlan 1Plan 2Plan 3 Inventory carryingRs. 13,15000 Regular laborRs. 833,280Rs. 654,720Rs. 819,840 Overtime labor000 Hiring00Rs. 51,500 Layoffs00Rs. 6,600 Subcontracting0Rs. 134,4000 Total costRs. 846,430Rs. 789,120Rs. 877,940 Plan 2 is the lowest cost option

35. Operations Management Prof. Upendra Kachru In large companies with several divisions or plants, HPP is used so decide which product groups to produce where. Planning is then carried out at the appropriate organizational level. HPP is the starting point for decisions about production quantities, inventory levels, and workforce levels for each plant. This planning process can continue plans for individual products being developed by departmental managers. Hierarchical Production Planning (HPP)

36. Operations Management Prof. Upendra Kachru The typical service operation is Make-To-Order rather than Make-To-Stock. The aggregate planning process, therefore, is different for services in the following ways:  Most services can not be inventoried.  Demand for services is difficult to predict.  Capacity is also difficult to predict.  Service capacity must be provided at the appropriate place and time.  Labor is usually the most constraining resource for service. Aggregate Planning For Services

37. Operations Management Prof. Upendra Kachru Proactive Strategies  Fixed Service Schedules  Appointment for Service Times  Customer Involvement  Planning with order Backlogs

38. Operations Management Prof. Upendra Kachru Aggregate Planning For Services Where this is not the case, service organizations also use aggregate planning, some in exactly the same way with a manufacturing firm. Aggregate planning in the case of a high-volume-product output business is very similar to manufacturing. In such high-volume tangible services, traditional aggregate planning methods may be applied.

39. Operations Management Prof. Upendra Kachru In a restaurant, for example, inventory is perishable. In addition, in fast-food restaurants, peak and slack periods may be measured in hours. The ’product’ may be inventoried for only as long as 10 minutes. This brings in complexity in aggregate planning.

40. Operations Management Prof. Upendra Kachru Aggregate Planning for Services Most service organizations have limited capacity. Their product is perishable e.g. airlines, and hotels, etc. In yield management, pricing relates to addressing specific capacity problems. The objective is to sell as much of the service at full price as possible, but to offer discounts if necessary to avoid the service to elapse. Yield Management

41. Operations Management Prof. Upendra Kachru From an operational perspective, yield management is most effective when  Demand can be segmented by customer.  Fixed costs are high and variable costs are low.  Inventory is perishable.  Product can be sold in advance.  Demand is highly variable. Yield Management

42. Operations Management Prof. Upendra Kachru Yield Management Formula Where: n= number of no-shows x= number of rooms or seats overbooked C u = cost of under-booking; i.e., lost sale C o = cost of overbooking; i.e., replacement cost P= probability The probability of ‘no-shows’ is given by the formula: P(n < x)  C u / ( C u + C o ) In yield management, service providers seek to minimize the cost of overbooking.

43. Operations Management Prof. Upendra Kachru Problem – Great Eastern Hotel The Great Eastern Hotel at Jaipur had on the basis of historical data calculated the probability of ‘no- shows’ in a particular season. The cost of under booking was estimated at Rs. 1750; and the cost of overbooking at Rs. 1200. The statistical data is shown below: No-ShowsProbabilityP(N < X) 0.150.00 1.250.15 2.300.40 3.300.70

44. Operations Management Prof. Upendra Kachru Solution Expected number of no shows = 1.75 Optimal probability of no-shows = 0.593 As you expect 1.75 ‘no shows’ and rooms have to be integer numbers, you overbook 2 rooms. The cost of overbooking the rooms is as follows: Cost of Refusing Rooms = Rs. 660.00 Lost revenue from no-shows = Rs. 525.00 Total cost of overbooking by 2 rooms = Rs. 1185.00 Expected savings = Rs. 1877.50 a night Therefore, it is worth overbooking 2 rooms to maximize profits and capacity utilization. 0*(.15) + 1*(.25) + 2*(.30) + 3*(.30) = 1.75 [2(.15) + 1(.25)]*Rs. 1200 = Rs. 660.00 [(Rs. 1750* 1.75) - Rs. 1185.00] = Rs. 1877.50 1750 / (1750 + 1200) = 0.593 (.30)* Rs. 1750 = Rs. 525

45. Operations Management Prof. Upendra Kachru & Solution The hotel sells its first 30 rooms at Rs. 2000.00 and the next 30 rooms at Rs. 4200.00. The variable cost per room is Rs. 1500.00. By selling rooms at differential prices, the hotel expects to improve its operations. Does it do so? Graphical Problem

46. Operations Management Prof. Upendra Kachru Solution The result is that it sells an additional 30 per cent of its rooms and improves profitability to Rs. 96,000 per day.

47. Operations Management Prof. Upendra Kachru In the real world, a manufacturing system with only a fair degree of complexity might process components through seven or eight manufacturing stages. The process would probably be integrated with parts purchased from outside vendors. The final-assembly plan would combine numerous internally manufactured components, purchased components, and subassemblies into end products for the customers. Desegregating the Aggregate Plan

48. Operations Management Prof. Upendra Kachru The operations manager would like to know:  How should aggregate output be subdivided among each of the products that are to be produced?  What mix of these products should comprise the aggregate inventories? This process of translating aggregate plans into plans for individual products is called desegregation. Desegregating the Aggregate Plan

49. Operations Management Prof. Upendra Kachru Rough-cut Capacity Plan The upper portion of shows that the aggregate production plan anticipates making 1,200, 800, and 600 2-liter bottles of soda over the 3-month planning horizon. The production schedule shown in the bottom half of the figure above provides a week-by-week schedule.

50. Operations Management Prof. Upendra Kachru The rough-cut capacity plan is necessary to generate the necessary detail, for planners to transform them into the Master Production Schedule (MPS). Planners use this to determine the firm’s resource needs over the planning horizon. In our next session, we will discuss MPS and MRP. Rough-cut Capacity Plan

51. Operations Management Prof. Upendra Kachru Forecast control  What is a Master Production Schedule (MPS) and what is its purpose?  What is Material Requirement Planning and what is its purpose? These are given on page 323 of your text book. Read at Home

52. Operations Management (2) Click to edit company slogan.