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Transcript of Lecture 04: Forecasting and Demand Planningoran/classes/LSCM_resources/handout/LSCM... · Lecture...
Demands101 Forecasting Planning Aggre. planning S&OP
Lecture 04:Forecasting and Demand Planning
Oran Kittithreerapronchai1
1Department of Industrial Engineering, Chulalongkorn UniversityBangkok 10330 THAILAND
last updated: May 4, 2017
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Demands101 Forecasting Planning Aggre. planning S&OP
Outline
1 Understanding your demands
2 Forecasting SCM Demand
3 Operational Planning Concepts
4 Aggregate Planning
5 Sales and Operations Planning
General Reference: [?] [?] [?] [?]
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Game Plan: From Forecasting to Shipping...
Guessing customer’s demands ⇐⇒ ForecastingSmoothing resources ⇐⇒ Aggregate planning & Demand managementSourcing R/M needed to produce ⇐⇒ Purchasing & Material requirementEstimating producing time ⇐⇒ Production planingManaging stocks ⇐⇒ Warehousing & Inventory controlDefining appropriated service level ⇐⇒ Channel & Distribution managementEnsuring commitment and delivery products ⇐⇒ Shipping
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What are demand?
Are these terms difference?demand =? sale =? order =? forecast
Thinking Points: Recall your last dinning experienceHow to estimate resources restaurants should have?Which channel do restaurants receive ‘demand’ information? how reliable?What happen if restaurants estimate incorrectly?
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How should we manage demands?
Understanding nature of demandPrioritizing independent easy to monitor demandForecasting ‘reasonable’ demandCommunicating and updating demand forecastInfluencing quantity and time of demand
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Understanding nature of demands:
Aggregate VS Market: Why do we think about demand of our brand?Stochastic VS Deterministic: Why do we think about constant demand?Dependent VS Independent: Why do we think about independent demand?
How do we manage/model inventory?
Demanddep = f(Demandindi ,Demandind
j , ·)
Demandindi = demandcertain + demandrandom
⇓ ⇓• steady • safety stock• trend• seasonal
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Postponement: delay differentiation
Motivation: HP CustomizationMotivation: Inventory, nature of demand, multiple marketsIdea: delay the differentiation of product/processRelated concept: localization, simple and modular designTrade-offs: economy of scale, production cost VS inventory, transportationImplementation: cross-organization coordination (manufacturing,purchasing, R&D, market)
Product design: reducing inventory & leadtime by std parts & manuf.Process design: delaying process differentiation by technologyAgile supply chain: time based competitive
Example: DeskJet, Paint mixture, Benetton shirt, HP hard drive test
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Prioritizing demand with parieto principle
Idea: few items affects majority of activity
You don’t get what you want in lifeYou get what you focus on and expect.
—Tony Rush
Therefore: focus on few that are importantApplication: ABC analysis
Class A important (15-20 percentile → for 55-75% of activity)Class B some-what important (20-50 percentile → 15-15% of activity)Class C not important (50-100 percentile → 5-15% of activity)
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Example of ABC analysis
Item No. Annual dollar % Total Value22 95,000 40.6968 75,000 32.1327 25,000 10.7103 15,000 6.4382 13,000 5.5754 7,500 3.2136 1,500 0.6419 800 0.3423 425 0.1841 225 0.10- $223,450 100%
source: Chase and Jacob. 2011.LSCM v2.0 9/ 24
Demands101 Forecasting Planning Aggre. planning S&OP
What we should know about forecasting
What: A process to understand systematic of demandsFacts: Inaccurateness, but all companies need it
Forecasting is, typically, incorrectForecasting is suitable for a group of productsForecasting is inaccurate as time horizon increases
Ideal: Valid for short time and need updatedAware Art & Science: roles of marketing & sale; common misconceptTypes: Qualitative, Time Series, Regression, Simulation
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What should we aware before forecast
Description: story, relationship with other dataTime Horizon: hour, day, week, year
Actual = Forecast + errorPattern of Data: seasonal, trend, cycleForecasting Model: assumption, data required, parameters, static VSdynamicAccuracy: measuring, how to improve
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Example: US Air Passengers 1949-1951
Month
AirP
asse
nger
s
Year 1949 Year 1950 Year 1951
6080
100
120
140
160
180
200
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
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Time Series Review: Workshop
Forecasting Accuracy: Actualt - Forecastt (i.e., MAPE, MSE)Naive Method: Forecast = actualSmoothing Tech: Forecast ≈ set of actual
Moving Average: Forecast = average of actualExponential Smoothing Forecast = combination of actual and last forecast
Trending: Forecast = expo smoothing + slope × periodSlope = gap of forecast
Seasonality: Forecastsea = rsea· Forecastde−sea
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Communicating and updating demand forecast
If you have to forecast, forecast often.
source: Edgar Fiedler
Sharing Points:Know data source: market goal =? operation cap, reliability VS urgencyKeep process simple/ comm. flat: verbal & constant, formal & informal,time frameRight communication channel: always confirm & name (scope), IT asenable (goldcity)
Believe the forecasting pattern, not absolute quantity or time
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Influencing demand
Cutting prices or putting things on sale is not sustainable businessstrategy.
source: Howard Schultz
Sharing Points:Other factors: service (physician schedule), experience (food), waiting time(BTS, bike), events (MOTOR SHOWS), quality (UBER)Marketing: focused social media (time spent)
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Planning Concept
Hierarchical: decision in upper-level → constraint in lower-levelFeedback: systematic correctionMan-Machine interface: ∃/ exceptions → including man’Single’ database & Integration: maintaining data integrity and accuracyTransparency: understanding logic and algorithm behind system
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Production Process
source: Chase & Jacabs. 2010. Operation and Supply Chain Management.
Project: product remains in a fixed locationWork center: similar equipment or functions are grouped togetherManufacturing Cell: dedicated area where similar products are producedAssemble line: processes are arranged according to the progressive stepsContinuous process: assembly line only the flow is continuous
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Closed-Looped Production Planning
MPSDemand Mgt.
PO
S. Forecasting
RCCP
Agg.Planning
L. Forecasting RRP
MRPBOM
InventoryCRP
Job Shop Purchasing
Long-Term Plan
Intermediate Plan
adopted from: Smith, S. 1989.
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Aggregate Planning
What: planning for family of productIdea: smoothing demands & key resources (workers, # machine)Occurred: beginning of fiscal year (unit: month of sale)Input: long-term forecasting + key resources, policy (overtime, subcontract,backlog, machine capacity)Output: production plan, capacity, inventory
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Red Tomato : Aggregate planningRed Tomato Tool, a US gardening tool manufacturer, usually faces with highly seasonaldemands and considers three distinguish strategies as follow:
Strategies Month Demand Month Demanda) adding seasonal worker Jan. 1600 Apr. 3800b) using subcontractor Feb. 3000 May 2200c) building inventory/backlog Mar. 3200 Jun 2200
The company sells each tool for $40 that requires 4 hour and has initial inventory andworkers in January of 1000 unit and 80 employees, respectively. A employee of RedTomato typically works 8 hours a day and earns $4 per hour during regular time.Because of labor law, no worker can work more than 20 days of regular time per monthand 10 hours of overtime per month.
Item Cost Item Cost Item CostMaterial cost $15/unit Hiring costs $300/worker RT cost $4/hourHolding cost $2/unit/month Layoff costs $500/worker OT cost $6/hourStockout cost $5/unit/month Labor required 4/unit Subcontract cost $30/unit
Determine the most suitable ’pure’ strategy and the optimal ’mixed’ strategy thatmaximizes profit if the company profile must have at least 500 units in June.
adopted from: Chopra, S. & Meindl 2016. pp. 227
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Red Tomato: Model and Excel
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Problems with aggregate planning
MethodsPrice taker: price can influence demand or negotiation (what if) → S&OPInventory of component: lack of components → MPS & MRPCapacity issues: simplified production constraints
ApplicationAggregate product: no information on exact product → communicationDelivery plan: frequency, product mixed, lot size → communication
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Sales and Operations Planning (S&OP)
What: manage supply or demand to smooth production given predictablevariabilityIdea: seasonal consumer demand, but fixed plant capacityManaging supply: capacity (flexible workforce & machine, subcontracting),investing (common component)Managing demand: shift or manipulate demand (using price) or promotion;may result to
Market growth:Forward buying:Stealing market share: depending on competitors
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Reference
[Bal07] Ronald H Ballou.The evolution and future of logistics and supply chain management.European Business Review, 19(4):332–348, 2007.
[CM07] Sunil Chopra and Peter Meindl.Supply chain management. Strategy, planning & operation.Springer, 2007.
[Goe11] Marc Goetschalckx.Supply chain engineering, volume 161.Springer, 2011.
[JC10] F Robert Jacobs and Richard B Chase.Operations and supply management: The core.McGraw-Hill Irwin New York, NY, 2010.
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