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Data Based Decision Making in Manufacturing Supply Chains

N. ViswanadhamComputer Science and Automation

Indian Institute of Science, Bangalore

January 23-24, 2014

IGSTC workshop on

Strategies and Concepts

for Advanced Manufacturing

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ContentsContents

High Performance Supply Chains

Big Data

Ecosystem Framework

Governance

Conclusions

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High Performance Supply Chains

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Integrated Supply Chain Network

Supplier Distributor

Supplier Retailer

Manufacturer

Service Provider

Information Network

Enterprise System or Web-site

Logistics Network

Logistics Hub

Financial Network

Banks

Supply Network

Service Network

Demand Network

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sConsolidation and ConnectednessConsolidation and Connectedness

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Ten mega corporations control the output of almost everything you buy; from household products to pet food to jeans.

37 banks have merged to become just four — JPMorgan Chase, Bank of America, Wells Fargo and Citi Group.

High concentration Clusters and connected networks are highly vulnerable

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Triggers of Global Supply Chain Disruptions

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sThe Great Trade CollapseThe Great Trade Collapse

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• Globalization & Highly Connected Supply Chains amplified & transmitted market collapse across the globe.

• Organizations extraneous to Supply Chain (Governments, Traders, Energy, .. Social, Political factors) influence its performance

The Great Trade Collapse: Causes, Consequences and Prospects A VoxEU.org Publication Edited by Richard Baldwin page 3

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Big DataBig DataFireflies on each component

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Recent Advances:Internet of Things,..

IoT technologies can be categorized into Tagging things, Sensing

things and Embedded things .– The tagging things provide item identification, things can be connected to

the databases.

– The sensing things enable us to measure and detect changes in the physical status of our environment.

– The embedded things yield information about the status of the embedding object.

Cyber Physical Systems

Systems of Systems: comprise of multiple, autonomous, embedded diverse global complex systems.

Network of Networks

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sBig data Enables Cognitive Supply Chains

During the last decade ERP, CRP etc analyzed internal data – sales, shipments, inventory, etc .

Now companies analyze external data to gain insights into customer fancies, markets, partner ecosystem and possible risks & consequences, etc

– Many Devices gather and store data: mobile, TVs, cars, Web, social media, traffic & security cameras, etc

– Data is in several forms: Images, sensor outputs, GPS, Internet of Things, text from email, blogs and reviews.

– Data on political, social, economic, meteorological factors

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Big data Enabled Business Processes Big data Enabled Business Processes

Procurement: Supplier & logistics provider selection, manufacturing locations, Delivery scheduling & Inventory management, Cost & Risk Evaluation,.

Dispersed Cognitive Manufacturing: Smart Factories, Embedded Machines, Smart parts, Cognitive PLCs

Distribution & Retail: Warehousing, Packaging, Tagging B2C Logistics, Customer preferences from recommender systems, In store customer moving & buying patterns

Service Chains: Logistics networks, Repair & Maintenance of Machines, Fleet of Trucks, Aircrafts, etc

Risk Mitigation Processes: Mitigating Cascading of network failures, Self Adaptive Machines, etc

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sBig data should aid in Decision Making that

results in Desired Business Outcomes

In Global supply chains, "What is the most sought after customer value, and what marriage of data and algorithms gets us there?"

The Big Question is “what data from suppliers, customers, governments, and local & economic environment should one collect and process” to get desired business outcomes.

What data you analyze every day, every week, every month.

A framework is needed to answer this question

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Ecosystem FrameworkEcosystem Framework

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Eco

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ware

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Supply Chain

Deliv

ery

Serv

ices

Infra

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Reso

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Institutions

The Basic EcosystemThe Basic Ecosystem

Investment ClimateCo-Evolution, Risk Propagation

SUPPLYCHAIN

ECOSYSTEM

DE

LIVER

Y SE

RV

ICE

MEC

HA

NISM

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IOT and Cognitive control systems

Logistics & IT companies

Delivery Channels

Decision Making Tools, BPO, Control Towers

RESO

UR

CES

Industry Clusters,Social Media, Web Blogs, Recommender systems

Human, Financial & Natural Resources Location Factors

Infrastructure: Ports, Airports, Roads,

Cloud and other storage resources

Customs , Export & Trade Other Govt. Regulators

INSTITUTIONS

Quality Control & Environmental Issues

Social, Legal and Privacy issues,Labor Unions

SUPPLY CHAIN

Retail Chains Distribution Manufacturing Suppliers

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sSES Framework Can Help To Study

Governance

Risk

Innovation

Performance

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GovernanceGovernanceHierarchy , Market or Network Hierarchy , Market or Network

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sThree Types of Network Governance Three Types of Network Governance

Supply Chain networks are Globally dispersed, independent organizations, connected only through Service agreements, Internet, FIIs, etc

The Network Governance model

– Highly Centralized External Broker (Li & Fung, Olam Intl.)

– Participant Shared Governance by Elected Board (Healthcare , Dairies, Cooperatives)

– Participant Shared Governance with a Lead Player Producer-driven (Cisco, Nike)

Buyer-driven (Wal-Mart, Carrefour, Levi)

All three governance forms are in practice.

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Governance: Partner Selection, Coordination & Control

A separate chain is formed for each order

Partner selection based on Transaction Cost and the risks in the ecosystem

Coordination : Determining who does what and when and communicating to everyone

Execution: Monitor order status so that processes work as per plan & control exceptional events

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sData Based Governance: Data Based Governance:

Partner selection, Coordination & ExecutionPartner selection, Coordination & Execution

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OtherAgencies

Coordination

Partner Selection

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Risks in the EcosystemRisks in the Ecosystem

Sr. No Risk classification Risk Elements

R1

Supply Chain

Location risk

Outsourcing risk

Design, manufacturing defects, Inventory deficit

Delay or unavailability of materials from suppliers

Breakdown of machines, power failure

R2

R3

R4

R5

R6

Resources

Raw material, Human, Financial

Social unrest, War

Infrastructure deficit, talent shortage

Credit squeeze, Energy & water shortage

R7

R8

R9

R10

Institutional

Regulatory risk

Political

Labor issues

Trade agreements

R11

R12

R13

R14

Delivery infrastructure

Failure of IT infrastructure

SC visibility decreases

Inbound and outbound logistics failure

Failure of governance mechanism

R15

R16

R17

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Supplier Selection using Transaction Costs

Delivery

Institutions

Shipping, Inventory, Asset specific Hard & Soft

Infrastructure

Taxes, Tariffs, SEZs, FTAs,

Social groups

Transaction Cost

ResourceAsset Specific

Clusters, Human, Financial, Power

Supply Chain Production, Quality, Transport

Coordination Costs Broker fees

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CoordinationCoordination

Coordination is to bring different complex activities or organizations into a harmonious relationship.

The coordination includes– For every order, selection of suppliers; assigning functions to them

such as what to supply, how is it to be produced (e.g., product tolerances and process standards), the production and delivery schedules , etc

– Identifying key parameters such as the product specification, the technology and the quality systems, labor and environmental standards along with the targeted price and communicating to the chain partners.

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sSupply Chain Control Tower

A command centre for visibility, decision-making, and action, based on real-time data.

Concept that has been around for a while in logistics called 4PL

Make real time decisions (exceptions) based on data

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ConclusionsConclusions

New technology developments such as IOT, cloud computing, mobile devices; Internet, Cognitive control, Big data analytics have immense impact on performance & competitiveness.

Our framework identifies the data to collect and analyze to make the needed decisions

The same methodology can be used to analyze service value networks and public networks for infrastructure building and food security.

Talent is need of the hour.

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sMathematical Models for Design of Mathematical Models for Design of

Governance MechanismsGovernance Mechanisms

The partner selection problem can be formulated as Fuzzy AHP or MIP problem. One can rank order the suppliers for each component based on the ecosystem parameters based on TCE.

Coordination, scheduling problems can be solved using Optimization techniques

Expert systems, Decision support systems, Case based reasoning and Hybrid control systems are useful for Exception Management and Execution

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