Disruptive Innovation Through Digital Transformation

  Dr. Robert de Souza Established in November 1998 under The Global School House Program as a collaboration between

  

Disruptive Innovation Through

Digital Transformation

• - A Supply Chain Focus

  To be the premier institute in Asia Pacific nurturing logistics excellence through world- class research, education and industry outreach Mission TLI-ASIA PACIFIC

  Disruption &

Transformation Disruptive Forces

Review Plan THE COMPETITION PARADIGM

  

TRANSFORMATIONAL

STRATEGIES FOR SUPPLY

CHAIN AND LOGISTICS

MANAGEMENT

  1 Basis of Competition THE CHANGING WORLD

  2 Demographic Trends Industry 4.0 The Marketplace Sociological Trends

  external factors speed costs throughput organization realignment process realignment integrating systems logistics infrastructure

  Increase of lifespan ageing population increasing urbanization more multi-cultural more middle class brands are less important omni-channel buying well-informed & social buying sharing economy mergers & acquisitions outsourcing strategies disintermediation/ governance growth ecommerce automated vehicles lights-out warehouse

  3D printing

  3 TRANSFORMATION CHALLENGES

  4 Pressure on Supply Chain Distribution Manufacturing

  more postponement changing batch sizes manage customer ship-to locations later cut-off times in warehouse multiple shipping locations distributed order management pricing differentiation in delivery options supply chain/ costs & time capacity new technologies global focus on core business broad alignment guidance & direction resource allocation high dependency on IT data current state analysis what-if analysis

  Digital Twinning Executive Support Organization Structuring Supply Chain Transformation

IMPACT ON COMPANY & SUPPLY CHAIN (CASES)

  Transformation

Digital Twinning

  

Innovation

The Journey to Transformation Traditional Supply Chain Digital Supply Chain

  Supply Chain Revolution

Industry 3.0 Automated Mass Production Transition Phase Industry 4.0 Atomization and Digitalization

E-Commerce Logistics versus Conventional Logistics

  E-Commerce Logistics Characteristics

  7 The Digital Supply Chain

Challenges

Future Supply Chain: Digital Supply Chain

  Digital Supply Chain  Digital supply chain is n customer-centric ly Chai

   Digital supply chain is Supp shifted to a more tal gi connected network in Di es

   Digital supply chain is fast- eng ll changing, requiring automation & flexibility

  Cha

Macro Challenges in the Digital Supply Chain Journey

  3

Cross-border Domestic

  Import duties vary widely across countries

  4. Inefficient last mile time-consuming delivery custom processes

  Source: Singapore Department of Statistics,

  2016 Source: Duty Calculator; A.T. Kearney Analysis

  4

  order to ensure efficient last-mile delivery

  Source: Jones Lang LaSalle; A.T. Kearney Analysis

  Strategic Process & Solution Change More Collaborative More Transparent More Flexible

  Supply Chain Self-Orchestration Micro Challenges in the Digital Supply Chain Journey Digital Twinning Leveraging the Opportunities

  

Digital Twinning

• The Sandbox!

Supply Chain Self-Orchestration “A Supply-Chain Specific Integrated Platform”

  (1) It would reveal insights and

  (1) provide suitable forecasting

  Visualization mechanism to maximize revenue of business and reduce costs/losses/risks over the chain.

Key Strategies in

  (2) It selects the “best” solutions

Digital Supply

  (3) Optimization from a set of alternative

Chain

  solutions (usually using mathematical model) by (4) (2) considering several factors.

  (3) Network It is used to find the best

  Optimization configuration of a supply chain network structure as well as the flows based upon an objective function, which typically maximizes profits.

  Data (4)

  It generates a set of “what-if” Simulation scenarios for determining best

  If handled and managed properly, data can help generate smarter supply chain and strategies in a supply chain logistics solutions and improved decision making processes.

Supply Chain Self-Orchestration “A Supply-Chain Specific Integrated Platform”

  1. As-Is Dynamic Resource

  Policy Design Tool Allocation Tool Supply Chain Network and Scheduling and Design Tool

  Routing Tool

  2. To-Be Ideal

Problem Statements

  A complex distribution network with limited cost-time-risk Product availability is extremely

visibility reduces cost transparency across the supply chain. important. Increasing on-shelf-availability

  This results in localized cost optimization instead of entire increases sales and consumers' loyalty. value chain cost optimization; resulting in high total cost to serve.

Opportunities

  Asset substitution Leveraging on the available routes, networks and transport assets from other companies (including 3PLs) enables the company to change the cost structure from fixed cost to variable cost.

  Utilization in DCs New strategies (i.e. (re)scheduling, delivery tracking and postponement) improves manpower utilization in the DCs as well as optimized truckload.

Supply Chain Visibility

  Visibility and transparency in the supply chain helps the company to implement best strategies to increase on-shelf- availability.

  

Challenge: Maintaining Economies of Consolidation from First

to Last Mile ? The Last Mile!

  Opportunity: Container within Container

  Picking points

  Picking Points

  Source: Stumm, 'Urban Logistics and Sustainable Development', EEG2 / TBG3 Transport/Logistics UN/CEFACT meeting, 2010.

  Opportunity: Virtual Consolidation

Challenge: Coordinating Assets Urban Area Retailers Shopping Centers Factories Businesses End- Customers

VC ratio

Urban Area Retailers Shopping Centers Factories Services End Customers

Many Long-Distance Final Deliveries (trucks) Few Short-Distance Final Deliveries (multi-modal) Urban Freight Consolidation Center (UCC) Warehouses

  Supply Network Design & Planning

  Opportunity: New Transporters Opportunity: Multiple Use

  Facilities Opportunity: Asset & Capacity Substituition

  23

Network Optimization and Simulation Modelling:

  Opportunity: Orchestrator (Control Towers)

Network Design Framework

  Congestion Index Trasportation Cost Index

  NTB

  Score Sumatra Java, Bali, NTT,

  Area Location Criteria

  Potential Locations (nodes) Geographic

  Kalimantan Maluku Papua Sulawesi

  Criteria Weightage 0.1813 0.2155 0.2081 0.1666 0.0972 0.0476 0.0461 0.0376

  NDP Index - Relative Pekanbaru 1.000 1.000 1.000 0.707 1.000 0.252 0.717 1.000 0.919 Medan 0.769 0.294 0.899 1.000 1.000 0.095 0.996 1.000 0.756 Bengkulu 0.648 0.478 0.260 0.613 1.000 1.000 0.415 1.000 0.591 Palembang 0.216 0.319 1.000 0.427 1.000 0.244 0.360 0.719 0.550 Surabaya 0.809 1.000 1.000 0.920 1.000 0.220 0.872 1.000 0.927 Semarang 1.000 0.321 0.925 0.760 1.000 1.000 0.896 1.000 0.809 Denpasar 0.313 0.545 0.285 1.000 1.000 0.204 0.591 1.000 0.586 Jakarta 0.302 0.148 0.618 1.000 1.000 0.125 1.000 1.000 0.583 Banjarmasin 1.000 1.000 0.230 0.930 1.000 0.041 1.000 0.719 0.787 Balikpapan 0.715 0.938 0.155 1.000 1.000 0.020 0.298 0.579 0.677 Samarinda 0.712 0.635 0.165 0.448 1.000 1.000 0.246 0.719 0.570 Pontianak 0.017 0.226 1.000 0.793 1.000 0.075 0.092 1.000 0.546 Ambon 0.495 0.833 1.000 1.001 1.000 0.504 1.000 1.000 0.868 Ternate 1.000 1.000 0.788 0.730 0.000 1.000 0.001 0.842 0.773 Timika 1.000 1.000 1.000 0.457 1.000 0.572 0.177 0.719 0.854 Jayapura 0.502 0.431 0.767 1.001 1.000 0.236 1.000 0.842 0.712 Sorong 0.738 0.381 0.673 0.892 1.000 0.566 0.408 1.000 0.698 Manokwari 0.612 0.688 0.664 0.566 1.000 0.629 0.636 0.719 0.689 Palau Biak 0.641 1.089 0.623 0.566 0.000 1.000 0.050 0.298 0.646 Manado 1.000 1.000 0.639 0.680 1.000 1.000 0.530 1.000 0.866 Makassar 0.442 0.357 1.000 1.000 1.000 0.617 1.000 1.000 0.759

  Pre-filtering of candidate locations

  Data Visualization MCDM Dynamic Simulation Optimization

  Zones Index Risk Index Infrastructure Index

  Coverage Index Access to Affected

  Qualitative Inputs Demands (Historical and Projection) Expenses Potential Facilities Network Visualization Comparison of alternative network performances Fleet and Inventory Policies

  Structuring and optimizing the supply network Supply chain operational performances

  Value-added GIS Visualization Inventory & transportation policies Identification of site selection criteria and candidate locations

  Implementable Facility and Asset Management

  Optimum network configuration Facility and Asset Optimization

  Corridor Accessibility Index Airport

Delivery Fulfilment Framework

  Dynamic Scheduling and Routing

  Data Visualization Data Analytics Multimethod Modelling Optimization

  Delivery Consolidation Facility and Asset Optimization

  Implementable Facility and Asset Management

  Value-added GIS Visualization Fleet Optimization Dynamic Vehicle

  Routing Problem (VRP) Delivery Postponement

  Delivery Self- collection Other Data Sensor and Telematics

  Demands (Historical and Projection) Expenses

  

Serious Gaming

Solutioning

  Engine: Smart Analytics Routing Application

  

“… a Serious Game that gives you the firsthand

experience at being either an LSP Manager or a Mall

Serious Games

  In Conclusion

  TLI-Asia Pacific Whitepaper Series

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Contact

  tliap.fb Email: rdesouza@nus.edu.sg

  @tliap_nus

Web: www.tliap.nus.edu.sg

Address

  Tel: +65 6516 5179 @tliap_nus

  21 Heng Mui Keng Terrace, NUS, I-Cube, #04-01 Singapore 119613