planning demang and supply in supply chain

8/10/2019 Planning Demang and Supply in Supply Chain

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PLANNING DEMAND AND SUPPLYIN A SUPPLY CHAIN

Peran Forecast dalam Supply Chain

Peramalan permintaan adalah dasar dariseluruh perencanaan dalam supply chain Push proses:

Forecast, untuk merencanakan jumlah produksi,jumlah transportasi, atau jumlah aktivitas lainnya

Pull proses: Forecast, untuk merencanakan ketersediaan

kapasitas dan persediaan (bukan jumlah aktual yang

akan diekseskusi) Keduanya mengacu pada: CUSTOMER

DEMAND DI MASA AKAN DATANG

Memprediksi masa depan...

Hal yang sangat sulit!!!!!

Every woman is frightened of a mouse.MGM head Louts B. Mayer in 1926, to young cartoonist

named Walt Disney

640k ought to be enough for anybody.Bill Gates, Microsoft founder, 1981

The Internet will collapse within a year.Bob Metcalf, founder of 3Com Corporation, in December

1995

Sumber: Forecasting for the Pharmaceutical Industry (Cook, 2006)

Peramalan pada Supply Chain

Poor Forecast: Dilakukan terpisah oleh masing-masing bagian SC

Mismatch antara supply dan demand

Good Forecast: Collborative forecast (joint team)

Lebih responsif dan efisien dalam memenu hi permintaanpelanggan

Karakteristik produk akan mempengaruhi peranan Forecast: Mature Products, permintaan stabil, permintaan mudah

diramalkan, kesalahan peramalan tidak berdampak signifikan. Produk Fashion dan High-Tech, jangka waktu penjualan singkat,

peramalan permintaan sulit dilakukan, kesalahan peramalanberdampak signifikan.

Characteristic of Forecasts

Forecast involves error >>> they are usuallywrong

Family forecast are more accurate than itemforecast. Aggregate forecasts are moreaccurate.

Short-range forecasts are more accurate than

long-range forecasts

A good forecast is more than a single number.


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Faktor terkait peramalan permintaan

Permintaan sebelumnya

Lead time produk

Rencana promosi dan kegiatan pemasaran

Keadaan ekonomi

Rencana pemberian diskon

Aksi yang dilakukan oleh kompetitor

Klasifikasi Peramalan

Kualitatif Sales force composite Survey Pasar

Keputusan Manajemen (Jury of executive opinion) The Delphi Method

Kuantitatif Projective

Time series

Causal Linear regression

Simulasi

Tahapan untuk menerapkan peramalan

yang efektif1. Pahami tujuan dari peramalan

2. Integrasi perencanaan permintaan danperamalan pada seluruh supply chain

3. Pahami dan identifikasi segmentasi pelanggan

4. Identifikasi faktor yang paling berpengaruhpada peramalan permintaan (*)

5. Tentukan metode peramalan yang tepat6. Lakukan pengukuran performansi dan error

peramalan

DemandEstimates

SalesForecast

ProductionResourceForecast

Examples of Production Resource ForecastsForecast

HorizonTime Span Item Being Forecast

Units of

Measure

Long-Range Years

Product linesFac tory capacities

Planning for new products

Capital expenditures

Fac ility location or expansion

R&D

Dollars, tons,

etc.

Medium-

RangeMonths

Product groups

Department capacities

Sales planning

Production planning andbudgeting

Dollars, tons,

etc.

Short-Range Weeks

Specific product quantities

Machine capacities

Planning

Purchasing

Scheduling

W orkforce levels

Production levels

Job assignments

Physical units

of products

Information needed to produce forecasts:


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Time Series

Selalu menggunakan data historis (Navemethods)

Komponen time series:

Trend

Seasonality

Cycles

Randomness

Simple Time Series Models

Moving Average (Simple & Weighted)

Exponential Smoothing (Single)

Double Exponential Smoothing (Holts)

Winters Method for Seasonal Problems

Simple Moving Average Forecast Ft is average of nprevious observations or actualsDt:

Note that the npast observations are equally weighted.

Issues with moving average forecasts: All npast observations treated equally; Observations older than nare not included at all;

Requires that npast observations be retained;

Problem when 1000's of items are being forecast.

t

nti

it

ntttt

Dn

F

DDDn

F

1

1

111

1

)(1

Example of Simple Moving AverageWeek Demand 3-Week 6-Week

1 650

2 678

3 720

4 785 682.67

5 859 727.67

6 920 788.00

7 850 854.67 768.67

8 758 876.33 802.00

9 892 842.67 815.3310 920 833.33 844.00

11 789 856.67 866.50

12 844 867.00 854.83

Weighted Moving Average

)( 11111 ntntttttt DwDwDwF

Forecast is based on n past demand data, each

given a certain weight. The total weight must equal

to 1.

Re-do the above example, using 3 past data, each given

a weight of 0.5, 0.3, and 0.2 (larger for more recent data)

Exponential Smoothing

New Forecast = (current observation ofdemand) + (1-) (last forecast)

OrFt= (Dt) + (1-)Ft-1

And

Ft-1= (Dt-1) + (1-)Ft-2, dst

Sehingga pada model ini, semua data historisterwakili pada forecast terakhir dengan bobot

yang semakin kecil (untuk data yang semakinlama)


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Exponential Smoothing Include all past observations

Weight recent observations much more heavilythan very old observations:

weight

today

Decreasing weight givento older observations

0 1

( )

( )

( )

1

1

1

2

3

Notes:

Only 2 values (Dt andFt-1 ) are required, compared with nformoving average

Parameter determined empirically (whatever works best)

Rule of thumb: < 0.5

= 0.1to = 0.3

Forecast for kperiods into future is:

tkt FF



Example:

Exponential smoothing and a constant model arebeing used for forecasting. The smoothed averageat the end of period zero was 80. The actualdemand in period 1 was 104. The smoothingconstant is 0,1. What is the forecast for period 2made at the end of period 1?

Persamaan MA dan ES

Sama-sama mengasumsikan demand bersifatstationary

Keduanya tergantung pada 1 nilai parameter, N

pada MA dan pada ES.

Kalau ada trend, kedua-duanya terlambat dalammerespon

Keduanya akan menghasilkan distribusi erroryang sama apabila = 2 / (N+1)

Perbedaan MA dan ES

MA mengakomodasikan lebih banyak data

ES hanya menyimpan dua data: forecast terakhirdan actual demand terakhir, sedang MAmenyimpan N data demand terakhir

Peranan IT dalam Forecasting

Forecast merupakan salah satu modul dalamsoftware yang digunakan pada Supply Chain:

ERP

SAP

Oracle

i2 Technologies

SAS

CRM


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Manajemen Resiko pada Peramalan

Resiko harus selalu dipertimbangkan dalammelakukan peramalan

Resiko eror pada peramalan dapat disebabkan oleh:

Semakin banyak faktor yang dipertimbangkan

Semakin panjang lead time pada forecast

Adanya pengaruh musin dan trend

Semakin pendek life cycle produk

Jumlah pelanggan yang sangat kecil

Peramalan dilakukan oleh pihak yang tidakberhubungan langsung dengan konsumen akhir

Meminimasi Resiko Peramalan dalam

Supply Chain Meningkatkan responsiveness

Membutuhkan investasi pada kapasitas

Untuk produk dengan life cycleyang pendek

Melakukanpooling demand

Timbul biaya transportasi

Jika forecast error selalu tinggi

Definisi Perencanaan Agregat

Proses yang dilakukan oleh perusahaan untukmenentukan tingkat kapasitas, produksi,

subkontrak, persediaan, stockout, dan hargapada jangka waktu tertentu

Hakekat Aggregate Planning

Tujuannya adalah to determine aggregateproduction quantitiesand levels of resourcesrequired to achieve these production goals

Merupakan rencana jangka menengahyangmencakup: Jumlah produksi dalam unit aggregate (pada level

product family, bukan pada level SKU) Kapasitas yang diperlukan (reguler, lembur, sub-

kontrak) Rencana tenaga kerja

Planning horizon 3 18 bulan Tujuannya untuk memaksimumkan profit

The Aggregate Planning Problem

Giventhe demand forecast for each period inthe planning horizon

Determinethe production level, inventorylevel,and the capacity level for each periodthat maximizes the firms (supply chains) profitover the planning horizon

Specify the planning horizon (typically 3-18months)

Specify key information required to develop anaggregate plan


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Cost yang Terlibat

Inventory holding cost

Hiring cost

Layoff cost

Shortage cost

Regular cost

Overtime cost

Subcontracting cost

Biaya Penyimpanan

(inventory holding cost / carrying cost)Biaya simpan adalah semua pengeluaran yangtimbul akibat menyimpan barang. Meliputi:

a. Biaya memiliki persediaan (biaya modal): 10-15%

b. Biaya gudang: 2-5%

c. Biaya kerusakan dan penyusutan

d. Biaya kadaluwarsa (absolence)

e. Biaya asuransi: 2-5%

f. Biaya administrasi dan pemindahan

Biaya Kekurangan Persediaan

(inventory shortage cost) Bila perusahaan kehabisan barang pada saat ada permintaan,

maka akan terjadi keadaan kekurangan persediaan. Keadaan ini akan menimbulkan kerugian karena proses

produksi akan terganggu dan kehilangan kesempatanmendapat keuntungan atau kehilangan konsumen pelanggankarena kecewa sehingga beralih ke tempat lain.

Biaya kekurangan persediaan dapat diukur dari: Kuantitas yang tidak dapat dipenuhi Waktu pemenuhan Biaya pengadaan darurat

Kadang-kadang biaya ini disebut juga biaya kesempatan(opportunity cost)

Outputs of Aggregate Plan

Strategies Chase Strategi (zero Inventory)


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Level Strategy Chase Strategy

Level Strategy Mixed Strategy

Contoh PermasalahanCoverting to Net Predicted and

Net Cumulative Demand


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Aggregate Plan for

Chase Strategy

Aggregate Plan with

Level Workforce

Aggregate Plan Optimized with

LP

Predictable variability

Definisi:

Perubahan demand yang dapat diramalkan

Terdapat dua strategi mengatasipredictablevariability:

Demand Management

Supply Management

DEMAND MANAGEMENT


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Often, Demand Patterns Lead to

Inefficient Supply Chain

0

5

10

15

20

25

1 2 3 4 5 6 7 8 9 1 0 1 1 12 13 14 15 16 17 18 19 20 2 1 0

5

10

15

20

25

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

D

F

Demand forecasting the process that an organization

takes to predict the level of demand. Demand forecastingtakes demand pattern as a given.

Problems with Volatile Demand

High forecast errors

High inventory investments

Low service levels (shortages often occurred)

High cost of adjusting the level of capacity

Fluctuated resource utilization

Demand Planning Vs Demand Management

Demand Planningthat process that anorganization takes to anticipate customerdemand and ensure sufficient product isavailable in the right place, in the right time, tothe required level of service and at the lowestpossible supply chain costs.

Included here are :Demand forecastingInventory management

Capacity planningProduction planning and schedulingMaterials requirement planning

Impetus to Demand Management

Demand is never truly exogenous, but oftenvery much dependent on internalprocesses. Sales and marketing usepromotion and other means to inflate sales.While this is good in terms of increasingsales volume, such an effort could result ina serious danger if not communicatedproperly to the related functions in thecompany as well as to other channels of thesupply chain.

Typical consequences: Serious out of stock Excessive inventory

Demand Management

Actively seeks to ensure that the customer demandprofile as an input to the demand-planning process

is as smooth as possible in order to make supplychain operations easier.

In other words, the company is not only passivelyprocess the given demand, but is trying to reducedemand volatility, or improving demand stability.

Thus, demand forecasting is REACTIVE, whiledemand management is PROACTIVE to customerdemand.


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Componen of Demand Management

Forecasting Demand

Communicating Demand

Influencing Demand

Demand Planning Vs Demand Management

ProductionPlanning

Production Delivery

Demand Management

DemandForecasting

Instruments of Demand Management

Pricing & Promotion: discounts, rebates, etc.

Assortment & Shelf management

Deal structure: terms and condition, priceprotection, return policies.

EVENT MANAGEMENT

Promotion

Special offers

Buy one get one

Happy hour scheme

End of season sale, etc

Coordinated Demand Management

Demand management should be wellcoordinated within the supply chain

Event potentially increase or decrease sales shouldbe visible to other (especially upstream) channels.

Market reaction to demand management shouldbe closely monitored.

Cross functional teamdifferent interestsamong functions

SUPPLY MANAGEMENT


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Supply Management

Controlling a combination of the following twofactors:

Production Capacity

Inventory

Managing Capacity

Time flexibility from workforce

Use of seasonal workforce

Use of subcontracting

Use of dual facilities specialized and flexible

Designing product flexibility into the production

processes

Managing Inventory

Using common components across multipleproducts

Build inventory of high-demand or predictable-

deman products

IMPLEMENTING SOLUTIONS TO

PREDICTABLE VARIABILITY IN PRACTICE Coordinate planning across enterprises in the

supply chain

Take predictable variability into account when

making startegic decisions

Preempt, do not just react to predictablevariability

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planning demang and supply in supply chain

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