Managing Production across the Supply Chain

Alphabet Soup TLA (Three Letter Acronym) Definitions ATP: Available to Promise BOM: Bill of Materials DRP: Distribution Requirements Planning MPS: Master Production Schedule MRP: Materials Requirements Planning PAC: Production Activity Control S&OP: Sales and Operations Planning

The Big Picture

Master Scheduling I Controls the timing and quantity of production for products or product families Primary interface point for actual customer orders Coordinates forecasted demand and actual orders with production activity Serves as tool for agreement between marketing and operations (but at a different level than S&OP)

Master Scheduling II Feeds data to more detailed material planning Indicates the quantity and timing (i.e., delivery times) for a product or group of products More detailed than S&OP weekly versus monthly specific products versus “average”

Link between S&OP and MPS Month: January February March Output: 200 300 400 S&OP January (weeks) 1 2 3 4 Push Mowers 25 25 25 25 Self-propelled 35 40 Riding 12 13 MPS

Master Scheduling Criteria The Master Production Schedule must: Satisfy the needs of marketing Be feasible for operations Match with supply chain capability

MPS Formulas: Definitions ATPt = Available to promise in period t EIt = Ending Inventory for period t (same as projected on-hand inventory for next period) Ft = Forecasted demand for period t MPSt = MPS quantity available in period t OBt = orders booked for period t

MPS Formulas:

Detailed MPS for a Product On-hand inventory at end of October = 100 Month November December Week 45 46 47 48 49 50 51 52 Forecast Demand 150 125 Orders Booked 170 165 140 120 85 20 Master Schedule 300 250 Notes: Planning time fence  cumulative lead time for product What seems to be the lot-sizing rule here?

Projected On-Hand Inventory On-hand inventory at end of October = 100 Month November December Week 45 46 47 48 49 50 51 52 Forecast Demand 150 125 Orders Booked 170 165 140 120 85 20 Projected On-Hand Inventory 230 65 215 190 Master Schedule 300 250 e.g., Projected on-hand inventory for week 47: = 65 + 300 – 150 = 215

Available-to-Promise On-hand inventory at end of October = 100 Month November December Week 45 46 47 48 49 50 51 52 Forecast Demand 150 125 Orders Booked 170 165 140 120 85 20 Projected On-Hand Inventory 230 65 215 190 Master schedule 300 250 Available-to-Promise   40 ATP (Week 45) = 100 + 300 – (170 + 165) = 65 ATP (Week 47) = 300 – (140+120) = 40 ATP (Week 49) = 250 – (85 + 45) = 120

Change in Forecast Demand On-hand inventory at end of October = 100 Month November December Week 45 46 47 48 49 50 51 52 Forecast Demand 150 Orders Booked 170 165 140 120 85 20 Projected On-Hand Inventory 230 65 215 190 Master schedule 300 250 Available-to-Promise   40 Are we in trouble yet?

Change in Orders Booked On-hand inventory at end of October = 100 Month November December Week 45 46 47 48 49 50 51 52 Forecast Demand 150 125 Orders Booked 170 230 140 120 85 20 Projected On-Hand Inventory Master schedule 300 250 Available-to-Promise   40 70 Note impact on ATP ( Week 45) and on-hand inventory projections

Planning Horizon How far an MPS looks into the future depends on Variability in demand and market conditions Variability in supplier deliveries and lead times Length of the production process.

Key Points about MPS Provides more detail than S&OP Tracks the following information: Actual versus forecasted demand Available-to-Promise This gives sales information for accepting or not accepting new orders for delivery in a given week

A Final View of Master Scheduling S&OP Operations & Supply Chain Marketing MPS Rough-Cut Capacity Plan

Material Requirements Planning MRP in the planning cycle The logic of MRP an extended example Considerations of MRP

So Far ... But we haven’t ordered the materials! We have only considered labor, overall inventory levels, and equipment:  S&OP  Master scheduling  Rough-Cut Capacity Planning But we haven’t ordered the materials!

We’ve scheduled 500 chairs to be ready five weeks from now . . . what?

Material Needed for a Chair Back supports (3) Side rails (2) Front legs (2) Cross bars (2) Seat

Chair Structure Tree (aka “Bill of Materials” or BOM) Leg Assembly Seat Back Assembly Legs (2) Cross bar Side rails (2) Back Supports (3)

Lead-Time I If final assembly takes one week, then we must start the assembly at the beginning of Week 4 . . . Chair Assembly (1 week)

Lead-Time II Which means that the major subassemblies and seats Week 2 Week 3 Week 4 Week 5 Which means that the major subassemblies and seats must be done by the beginning of Week 4 ... Back Assembly (1 week) Chair Assembly Seats (2 weeks) (1 week) Leg Assembly (1 week)

Lead-Time III Week 1 Week 2 Week 3 Week 4 Week 5 Back Support (2 weeks) Side Rails (2 weeks) Back Assembly Cross Bar (2 weeks) (1 week) Chair Assembly Seats (2 weeks) (1 week) Leg Assembly Legs (2 weeks) Cross Bar (2 weeks) (1 week)

Lead-Time Key Points To have finished chairs at the beginning of Week 5 with no work in progress or finished inventory, we must begin production and order materials in Week 1. “Exploding” the bill of materials tells us when to order things. Not much we can do to adjust output of chairs for the next 4 weeks. Why?

Material Requirements Planning (MRP) Requires: Bill-of-Materials (BOM) Inventory record Master schedule to determine what should be ordered when, and how much to order.

The MRP Process Starts with the MPS End items are also known as “Level 0” items

The “Parent / Child” Relationship Refer back to bill of materials on slide 24, or insert duplicate after this slide for ready reference Where do the gross requirements come from? Do you understand the MRP logic?

Going Deeper…

Moving from “Level 1” items to “Level 2” items . . . Where do the gross requirements for LEGS come from?

Combining Requirements: “Cross Bars” Note effect of differences in lead times and order sizes on the gross requirements for each component

Impact of Longer Lead Times We cannot do this since the planned order would be in the past…. Thus the 250 crossbars will be delivered late one week to back assembly. What does this do to our chair schedule?

Do You Understand ... Why it is important to have an accurate BOM and accurate inventory information? Why we need to “freeze” production schedules? Where gross requirements come from? The difference between planned and scheduled receipts?

Other Considerations I MRP Feedback Feedback Planned Orders Production Suppliers

Other Considerations II When do we update the system? Capacity requirements planning using MRP output MRP ‘nervousness’ Increasing order chaos, the lower in the BOM structure of materials Lot sizing issues

Recall ... Look at the “lumpiness” of demand for legs

If we order “lot-for-lot” Much smoother demand for legs, lower average inventory

Job Sequencing Rules: Performance measure: FCFS — first come, first served EDD — earliest due date Critical ratio — work time remaining divided by days left before due date Performance measure: Average lateness — sum of days late for each job divided by total number of jobs

Example Data Job Estimated Time Days Until Due Critical Ratio Weldco 8 32 0.250 MetroArt 10 20 0.500 MMCC 9 1.000 Jones 6 15 0.400

Example FCFS Job Estimated Time Days Until Due Start End Days Late Weldco 8 32 MetroArt 10 20 18 MMCC 9 27 Jones 6 15 33 Average lateness = 36/4 = 9 days

Example EDD Job Estimated Time Days Until Due Start End Days Late MMCC 9 Jones 6 15 MetroArt 10 20 25 5 Weldco 8 32 33 1 Average lateness = 6/4 = 1.5 days

Example Critical Ratio (largest ratio first) Job Estimated Time Days Until Due Start End Days Late MMCC 9 MetroArt 10 20 19 Jones 6 15 25 Weldco 8 32 33 1 Average lateness = 11/4 = 2.75 days

Interpretation Here the EDD rule gives better average lateness. Compare with FCFS results. Note that the critical ratio does not do as well as EDD compared to the text example for Carlos Restoration. Why?

Distribution Requirements Planning (DRP) Anticipates downstream demand Uses this information, not predetermined reorder points or periodic reviews, to determine when to order Computer-based software systems needed to deal with the added complexity The key difference between DRP and the other methods is that DRP uses demand forecasts and knowledge about the supply chain partner’s inventory policies to determine when to place an order. DRP is more complex and usually requires a computer-based system, but is far better when demand levels are unpredictable.

DRP Example I Suppose we forecast demand for Wholesaler A for the next 8 days (the best time horizon to use will depend on many factors) Based on this, we anticipate that Wholesaler A will order on Day 3 As before, Wholesaler A has a reorder point of 50, and orders in quantities of 200. The DRP record shows the forecasted demand for the next 8 days, the expected ending inventory level, and when Wholesaler A will expect to receive an order. For example, the wholesaler starts Day 1 with 85 units and expects to sell 20, leaving it with 65 at the end of the day. Wholesaler A falls below its order point some time on Day 2. As a result, Wholesaler A places an order which it expects to receive on Day 3. Based on the expected demand rate of 20 per day, Wholesaler A shouldn’t expect to receive another order over the remaining days showing in the record.

DRP Example II Combined, we expect to see orders on Days 3 and 4 Here, we have completed a similar DRP record for Wholesaler B, and added its expected orders to those of Wholesaler A to get a line titled “Total expected orders” for the next 8 days. We extend the analysis to include Wholesaler B Combined, we expect to see orders on Days 3 and 4

DRP Example III Special notes: Even though the orders cause the demand to look “lumpy”, DRP allows the distributor to anticipate when the orders are required, and to plan accordingly. In this case, the distributor will need to plan on receiving 400 units in Day 3 (Q = 400 for the distributor). If it takes 2 days to get units to the distributor from the factory, this means the distributor should plan on releasing the order on Day 1. The distributor then uses this information to plan its own orders. In this case, suppose it takes two days for the supplier to replenish; based on the information, the distributor would order on Day 1

DRP Benefits Helps improve customer service Provides a better and faster understanding of the impact of shortages and/or promotions Helps reduce costs Inventory Freight Production Provides integration between the stages in the supply chain “Reduced costs” deserves some more explanation. To the extent that the distributor could “see” when the wholesalers would require more product, the distributor could use that information to combine orders, plan production, or even combine freight shipments. The point is, with better information, the Distributor will have more choices on how to run its business.

DRP Constraints Accurate forecasts and inventory levels Necessary to anticipate correctly when orders will be placed Consistent and reliable lead times To ensure that orders can be placed and arrive by the time they are needed “Nervousness” Even light changes in demand for downstream partners can have a significant impact on order volumes, especially when order sizes are relatively high

Case Study in Managing Production The Realco Breadmaster