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Professor of Supply Chain Engineering, ITS, Indonesia President, Indonesian Supply Chain & Logistics Institute (ISLI) E-mail: [email protected]

Professor of Supply Chain Engineering, ITS, Indonesia President, … · 2018-08-16 · Professor of Supply Chain Engineering, ITS, Indonesia President, Indonesian Supply Chain & Logistics

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Page 1: Professor of Supply Chain Engineering, ITS, Indonesia President, … · 2018-08-16 · Professor of Supply Chain Engineering, ITS, Indonesia President, Indonesian Supply Chain & Logistics

Professor of Supply Chain Engineering, ITS, IndonesiaPresident, Indonesian Supply Chain & Logistics Institute (ISLI)

E-mail: [email protected]

Page 2: Professor of Supply Chain Engineering, ITS, Indonesia President, … · 2018-08-16 · Professor of Supply Chain Engineering, ITS, Indonesia President, Indonesian Supply Chain & Logistics

25 Top SC, 2016

Sumber: Supply Chain Management Review, 2016

Page 3: Professor of Supply Chain Engineering, ITS, Indonesia President, … · 2018-08-16 · Professor of Supply Chain Engineering, ITS, Indonesia President, Indonesian Supply Chain & Logistics

Top Supply Chain Players 2016 (Gartner)

156 – 13.2% – (4)% - 36,9 – 10.8% – 3.6% - 108,4 – 0.5% – 20.4% - 0

3,5 – 25,3% – 16,3% - 94,3 – 11,4% – 1,1% - 9

3,9 – 16,7% – 11,2% - 9

TOR – ROA – Revenue Growth - CSR

Page 4: Professor of Supply Chain Engineering, ITS, Indonesia President, … · 2018-08-16 · Professor of Supply Chain Engineering, ITS, Indonesia President, Indonesian Supply Chain & Logistics

Network Value

Characteristics of Leaders

Product

Demand

Supply

Enterprise outcomes

Page 5: Professor of Supply Chain Engineering, ITS, Indonesia President, … · 2018-08-16 · Professor of Supply Chain Engineering, ITS, Indonesia President, Indonesian Supply Chain & Logistics

Important in Managing a Supply Chain

You can forecast the demand accurately

You have a reliable supply

You have Innovative products, services, and business models

You have information visibility

Page 6: Professor of Supply Chain Engineering, ITS, Indonesia President, … · 2018-08-16 · Professor of Supply Chain Engineering, ITS, Indonesia President, Indonesian Supply Chain & Logistics
Page 7: Professor of Supply Chain Engineering, ITS, Indonesia President, … · 2018-08-16 · Professor of Supply Chain Engineering, ITS, Indonesia President, Indonesian Supply Chain & Logistics

Low / very low information visibility

Silo-based, poor cross-functional team

Reactive, rather than strategic buying

Decision is not data-driven

Page 8: Professor of Supply Chain Engineering, ITS, Indonesia President, … · 2018-08-16 · Professor of Supply Chain Engineering, ITS, Indonesia President, Indonesian Supply Chain & Logistics

ANALYTICSEVERY DAY WE CREATE

2,500,000,000,000,000,000(2.5 QUINTILLION) BYTES OF DATA

Fill 10 million Blu-ray discs, the height of which stacked, would measure the height of 4 Eiffel Towerson top of one another

Data stored grows4X FASTER THAN THE WORLD ECONOMY

Increasing quantity of data allows forMORE QUALITATIVE APPROACH

Page 9: Professor of Supply Chain Engineering, ITS, Indonesia President, … · 2018-08-16 · Professor of Supply Chain Engineering, ITS, Indonesia President, Indonesian Supply Chain & Logistics

Collecting

Cleaning

Analyzing

Simulating

Page 10: Professor of Supply Chain Engineering, ITS, Indonesia President, … · 2018-08-16 · Professor of Supply Chain Engineering, ITS, Indonesia President, Indonesian Supply Chain & Logistics

Problems with Truck Productivity

Wait for assignment

Loading assignment

Loading process

Travelling forward

Travelling backward

Unloading process

Wait for unloading

Long cycle time due to:• Uncertain travelling time• Held in distributors• Queueing in Depo

Page 11: Professor of Supply Chain Engineering, ITS, Indonesia President, … · 2018-08-16 · Professor of Supply Chain Engineering, ITS, Indonesia President, Indonesian Supply Chain & Logistics

Uncertain delivery time

Short distance

Long distance

Page 12: Professor of Supply Chain Engineering, ITS, Indonesia President, … · 2018-08-16 · Professor of Supply Chain Engineering, ITS, Indonesia President, Indonesian Supply Chain & Logistics

The Problem of Long Waiting Time

• Destination varies substantially (could be as short as a few kilometers and as long as over 700 kilometers), but there was no attempt to segment the queue.

• Time window is not taken into account when departing trucks. Many trucks wait for the following day for unloading.

Queue time before loading, average around 4 hours

Queue time @ Plant travel Queue time @ destination Travel back 1 cycle

2,5 cycle

Page 13: Professor of Supply Chain Engineering, ITS, Indonesia President, … · 2018-08-16 · Professor of Supply Chain Engineering, ITS, Indonesia President, Indonesian Supply Chain & Logistics

00 06.00 18.0024.00

ONOFF OFF

00

Loading Travelling WaitingReady for

Unload

Maximize the probability of this event falling in the green area

N (7; 2)

0 wp. 0.5

U[0 – 8] wp. 0.5

24.00

00 06 18 30 42 54 66 78 90 102

OFF OFF OFF OFF OFFON ON ON ON

Departure U [ 03 – 10]

Page 14: Professor of Supply Chain Engineering, ITS, Indonesia President, … · 2018-08-16 · Professor of Supply Chain Engineering, ITS, Indonesia President, Indonesian Supply Chain & Logistics

Efficient Frontier Analysis

An Integrated Shipment Planning and Warehouse Capacity Decision: A Case Study of Bulk Item

00 0 00

33 3

33

2323 2323 23

393939 3939

150.00

160.00

170.00

180.00

190.00

200.00

210.00

220.00

230.00

240.00

85.0% 87.0% 89.0% 91.0% 93.0% 95.0% 97.0% 99.0%

Co

st P

er T

on

(T

ho

usa

nd

of

Ru

pia

h)

Service Level

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47

Page 15: Professor of Supply Chain Engineering, ITS, Indonesia President, … · 2018-08-16 · Professor of Supply Chain Engineering, ITS, Indonesia President, Indonesian Supply Chain & Logistics

An Integrated Shipment Planning and Warehouse Capacity Decision: A Case Study of Bulk Item

Cost per ton Service level

Running 30 replications, the distribution of cost per ton and service level looks...

(a)

(b)

(c)

0

2

4

6

8

10

0,85

5

0,86

0

0,86

5

0,87

0

0,87

5

0,88

0

0,88

5

0,89

0

0,89

5

0,90

0

0,90

5

0,91

0

0,91

5

0,92

0

0,92

5

0,93

0

0,93

5

0,94

0

0,94

5

0,95

0

0,95

5

0,96

0

0,96

5

0,97

0

0,97

5

0,98

0

0,98

5

0,99

0

0,99

5

1,00

0

Mor

e

Freq

uen

cy

Scenario 0

0

2

4

6

8

10

0,85

5

0,86

0

0,86

5

0,87

0

0,87

5

0,88

0

0,88

5

0,89

0

0,89

5

0,90

0

0,90

5

0,91

0

0,91

5

0,92

0

0,92

5

0,93

0

0,93

5

0,94

0

0,94

5

0,95

0

0,95

5

0,96

0

0,96

5

0,97

0

0,97

5

0,98

0

0,98

5

0,99

0

0,99

5

1,00

0

Mor

e

Freq

uen

cy

Scenario 3

0

2

4

6

8

10

0,85

5

0,86

0

0,86

5

0,87

0

0,87

5

0,88

0

0,88

5

0,89

0

0,89

5

0,90

0

0,90

5

0,91

0

0,91

5

0,92

0

0,92

5

0,93

0

0,93

5

0,94

0

0,94

5

0,95

0

0,95

5

0,96

0

0,96

5

0,97

0

0,97

5

0,98

0

0,98

5

0,99

0

0,99

5

1,00

0

Mor

e

Freq

uen

cy

Scenario 23

0

2

4

6

8

10

0,85

5

0,86

0

0,86

5

0,87

0

0,87

5

0,88

0

0,88

5

0,89

0

0,89

5

0,90

0

0,90

5

0,91

0

0,91

5

0,92

0

0,92

5

0,93

0

0,93

5

0,94

0

0,94

5

0,95

0

0,95

5

0,96

0

0,96

5

0,97

0

0,97

5

0,98

0

0,98

5

0,99

0

0,99

5

1,00

0

Mor

e

Freq

uen

cy

Scenario 39

(a)

(b)

(c)

0

2

4

6

8

10

16

6

16

8

17

0

17

2

17

4

17

6

17

8

18

0

18

2

18

4

186

188

19

0

19

2

19

4

19

6

19

8

20

0

20

2

20

4

20

6

20

8

21

0

21

2

21

4

21

6

21

8

22

0

22

2

224

More

Fre

qu

ency

Scenario 0

0

2

4

6

8

10

16

6

168

17

0

17

2

17

4

17

6

17

8

18

0

18

2

18

4

186

18

8

19

0

19

2

19

4

19

6

19

8

20

0

20

2

204

20

6

20

8

21

0

21

2

21

4

21

6

21

8

22

0

222

22

4

Mo

re

Fre

qu

ency

Scenario 3

0

2

4

6

8

10

16

6

16

8

17

0

17

2

17

4

17

6

17

8

180

18

2

18

4

18

6

18

8

19

0

19

2

19

4

19

6

19

8

20

0

202

20

4

20

6

20

8

21

0

212

21

4

21

6

21

8

22

0

22

2

224

Mo

re

Fre

qu

ency

Scenario 23

0

2

4

6

8

10

16

6

16

8

17

0

17

2

17

4

17

6

17

8

18

0

182

18

4

18

6

18

8

19

0

19

2

19

4

19

6

19

8

200

20

2

20

4

20

6

20

8

21

0

21

2

21

4

21

6

218

22

0

22

2

22

4

Mo

re

Fre

qu

ency

Scenario 39

Page 16: Professor of Supply Chain Engineering, ITS, Indonesia President, … · 2018-08-16 · Professor of Supply Chain Engineering, ITS, Indonesia President, Indonesian Supply Chain & Logistics

On Demand Ride Services Demand-Supply Matching Research

Rider/DemandAnywhere and Anytime

(uncertain)

Driver/Supply

Anywhere and Anytime (uncertain)

Driver is not an employee

• Demand & Supply dalam jumlah besar

• Demand & Supply Matching in large area

• Memuaskan kebutuhan stakeholder (Driver, Rider, Provider)

EconomyGrowth

Population Growth

City SizeGrowth

The need of Transportation

Increase

❖ Low Idle time❖ Low Traveling time &

distance❖ High income &

bonus

➢ High Order fulfillment rate

➢ High Customer satisfaction

➢ Low Customer cancelation rate

Supply/Driver

Provider

o Good Serviceo Low Pick-up timeo Fast Order waiting

timeo Cheap

Demand/Rider

Stakeholder Needs

Enabler Factors:✓ Sharing Economy Phenomena ✓ Mobile Device Technology (cangggih, murah) ✓ Internet Technology (4G, 5G, murah, cepat)✓ Digital Economy (transaksi digital)

Page 17: Professor of Supply Chain Engineering, ITS, Indonesia President, … · 2018-08-16 · Professor of Supply Chain Engineering, ITS, Indonesia President, Indonesian Supply Chain & Logistics

The Study of Contract and Spot Carrier in Logistics and Transportation

Lala Ayu Kantari and Prof. I Nyoman Pujawan

Industrial Engineering Department

In general, a shipper is partnering with a long-term transportation contract

On the spot carrier can handle one-time shipment without a prior contract agreement

Research Methodology

Simulation and Experiment

α Contract & (1-α) Spot carrierOnline matching scenario

Supply chain configuration

+ Low risk+ Sustain delivery- Not flexible

Dedicated no. of truck

Unmet demand

+ Flexible+ Real-time agreement

- Higher price

- Higher risk- Low availability

Additional truckDemand

RetailersDemandLocation Time windows

ShipperRules and PolicyLocationCapacity Carriers

Mileage CostAvailabilityLocation

Result and Analysis

Product Fill RateReliability

Transportation Cost

Shipper

Contract carrier

On the spot carrier

Retailers

Supply Chain System

Online matchingscenario

Uncertain demand

Page 18: Professor of Supply Chain Engineering, ITS, Indonesia President, … · 2018-08-16 · Professor of Supply Chain Engineering, ITS, Indonesia President, Indonesian Supply Chain & Logistics

Inflexible push model

Demand pull, but costly

Adaptive and synchronized

• Flexible configuration• High visibility, continuous scanning and signaling• Intelligent capability (optimization, simulation)

Page 19: Professor of Supply Chain Engineering, ITS, Indonesia President, … · 2018-08-16 · Professor of Supply Chain Engineering, ITS, Indonesia President, Indonesian Supply Chain & Logistics

Statistics Decision Analysis

Finance Marketing HRM

Information Technology

Technology & Innovation

Project Management

Operations Planning and

Control

Transportation & warehouse

SC StrategyPurchasing &

SupplyRetail & Digital

SC

Thesis Proposal Thesis

Tools

Functional Management

Specific Management

SC Core

Research

https://intip.in/mmtitsjakarta