The future of the future … belongs to intelligent ...

The future of the future … belongs to intelligent networked companies

Infor, August 2018

The power of networks

State of the market

Sellers FinancialInstitutions

LogisticsProviders

Buyers

State of the market: From Source to Delivery

OUTBOUNDINBOUND

E N T E R P R I S E

80% of the data needed to effectively runa global supply chain resides with partners

Suppliers Manufacturing Distribution Channels / Customers

Plant 1

Near Source

ContractManufacturer

Plant 1

Supplier 1

Supplier 2

Transport 1

3rd partydistributor

Transport 2

Retail 1

Retail 2

Retail 3

Information model for the Supply Chain Network

Many versions of truth

Traditional supply chain data flows Infor’s commerce networkSingle source of truth

Shipment InfoSupplier

Finance Provider

Customs Broker

Ocean Carrier

Inland Carrier

Control Tower

Enterprise

Shipment

Orders, Shipment and

Inventory

T R A D I T I O N A L S U P P LY C H A I N S

Are not able to compete

Traditional Networked

Manual

Spreadsheets

Support Business

In-side out thinking

Point-to-point connections

Firefighting

Enterprise thinking

Out-side In thinking

Collaborative

Digital supply network

Big Data • Machine learning • IoT

End-to-end

Automated

Proactive

Flexible

Drive Business

…... and wont survive

Suppliers

ShippersCarriers

Brokers

Forwarders

Warehouses

Dealers

Forecasts

Orders

Invoices

ShipmentsPayments

Products

Inventory

Supplier

Finance Provider

Customs Broker

Logistics ProviderCarriers

Enterprise

Invoice

Inspection Certificate

Invoice

Customs

Invoice

Change

Invoice

Accounts

Payable

Information Model for Network Orchestration

• All parties operating on a

shared platform

• Every party represented

• Single shared view

• Digital automation of supply

chain processes

• Multiple ways to connect

Single version of the truth

Digital Supply Chain Collaboration: Manufacturers/Distributors

MANUFACTURER

FINANCIAL INSTITUTIONS

LOGISTICS PROVIDERS

WMSTMS

RAW MATERIALS

SUPPLIERS

ERP ERPERP

FINFIN

COMPONENT SUPPLIERS

ERP ERP ERP

Global

Commerce

Book Carriers & Track Shipments

Confirmation & Collaboration

Customer Orders

Orders to Suppliers

Order Collaboration

Book & Tender

Transportation Sourcing

Supply Chain Visibility

Book Carriers

Respond to Tenders & Take Bookings

Track Shipments

Invoices

Financing

Payments & Invoices

Payments

Freight Invoices & Audit

Order Collaboration

Forecast

Collaboration

RETAILERS

Order Collaboration

Payments & Invoices

Track Shipments

Next Generation Supply Chains

Network

Single source of truth

Multi-tier

Network insights &

benchmarking

Digital

Real time information

More accurate

Process automation

Insights

Collaborative

Real time data sharing

and collaboration

Faster decisions

Ensures better

alignment

Transparent

Visibly to all parties

Better insights

Increased

responsiveness

E2E visibility: origin to

final delivery

Intelligent

More predictive &

prescriptive

Machine learning

Self-actuating

Resilient

Financially healthy

Secure

Compliant

Early notice of supply

chain disruptions

Value for all parties

Func t ion as In te rconnec ted Networks : More ag i le , respons ive and e f f i c ien t

IOT & MHE Extensibility

Document

ManagementWork flow

Alerts & Event

management

Integration

Social

Collaboration

Next Gen WMS + Advanced Technology Platform

Infor Next Generation Networked WMS and MHE

Infor Open Network

Transmits instructions from SCE to WCS

Modern Digital Technologies Enhance Visibility

Where it was, is and will be.

Real time

Granular

End-to-end

Where it was

and will be

Network IoT Machine

LearningIn-Memory

Live: Real Time Visibility with IoT

• 400+ GPS device types• + EDI 856, 210, 214

News Feeds

Social Media

Weather

Disasters

GPS / AIS

• Largest Ocean network• + EDI 301, 310, 314

• All 100,000+ daily flights• + EDI 856, 210, 214

• Rule-based filers• Location-based services

GPS / Telematics Flight Status

R E A L T I M E V I S I B I LT Y R E Q U I R E S M O R E T H A N J U S T I O T

Continuous Visibility: Example

Carrier / 3PL DCCarrier / 3PL

Augmented logistics processes combining EDI messages with real-time GPS

IoT vendor data lacks

supply chain context

Execution data doesn’t

provide full visibilityMilestone-only approach

limited by speed and scope

W E L C O M E T O

Katherine Coleman JohnsonNASA research mathematician

A . I . T H AT M A X I M I Z E S H U M A N P O T E N T I A L

EvolvingAI Toolset

EmbeddedIntelligence

SeamlessInfor OS

Connectivity

Levels of AIExperience

Enterprise Intelligence Platform

Artificial intelligence components

Voice UX

Voice assistant for the

enterprise

Relationships

Connected and referenceable data

patterns across applications

Data Science

Machine learning and deep learning

models for business

Big Data

Single cost effective, unrestrictive,

enterprise-wide data repository

Extensibility

Flexibility over customization

Predictive Analytics

Proactive KPIs to better

manage the enterprise

Intelligence Foundation

Augmentation AutomationAdvisory

Coleman Digital Assistant Coleman AI PaaS

Embedded Intelligence = Enterprise Whitespace

Coleman amplifies work

• Provides information

• Executes tasks

• Is available everywhere

Augments

Automates

Coleman frees you up to focus on high value work

• More intelligently

• More quickly

• More efficiently

Advises

Coleman helps you seize the moment by making the best decision every time

• Provides recommendations

• Makes expert decisions

Augments Automates AdvisesConversational

Chat Voice Image

recognition

Conversational UX

Amazon Lex Example

Submit Hours

API Gateway

Submit my hours for today.

IntentsAn intent performs

an action in

response to natural

language user input

D I G I TA L A S S I S TA N T

UtterancesSpoken or typed

phrases that invoke

your intent …

8am to 5pm

Sure, what were your hours?

SlotsSlots are input

data required to

fulfill the intent

FulfillmentFulfillment

mechanism for

your intent

Great, hours have been posted.

27Copyright © 2015 Infor. All rights reserved. This presentation is provided for informational purposes only and does not constitute a commitment in any way. The information, products and services described herein are subject to change at any time without notice.

A.I. ColemanHOW CAN INFOR HELP?

Coleman, do we have a 15 tablets ready to ship to customers?

11:51 AM

Coleman

No, would you like to manufacture them?11:51 AM

11:52 AM

Coleman, show me the production plan for this week?

11:52 AM

Coleman, show me the parts I will likely need for this week’s jobs and highlight ones

we will need to expedite in ordering.

11:53 AM

Coleman, can you alert the service desk delay maintenance. We need all production

capacity this week. Schedule the maintenance for next week. Assign this

maintenance job to John Johnson’s team.

Let them also check the SMT machine as extra check.

ChatVoice Automates

A.I. ColemanHOW CAN INFOR HELP?

8:51 AM

Coleman, email [customer] to let them know I will arrive at 10:15

08:50 AM

Coleman, how long will it take to get to my next customer?

10:28 AM

Coleman, show me the specification documents for this equipment

10:33 AM

Coleman, show me the condition based monitoring check list for this equipment.

08:50 AM

Who do I need to meet?

A.I. Supporting Service Technicians: ExecutionHOW CAN INFOR HELP?

10:56 AM

Coleman, I’ve finished the job now.

10:38 AM

Coleman, I’m starting the job now

10:56 AM

Coleman, record I have used parts A, B & C on this job

10:42 AM

Coleman, mark tasks 1 to 3 as completed

ColemanPlease confirm the following activities for job: SO0004512

10:56 AM

Yes?Confirm:

Part Expected Use

Quantity

Actual Use

Quantity

PART A 1 each 1 each

PART B 1 each 1 each

PART C 1 Litre 1 Litre

PART D 3 each 0 each

Time taken

Start time: 10:38 AM

End time: 10:56 AM

ChatVoice Automates Augments

Apache Hive

Apache Hadoop

Apache Pig

Apache Spark

Apache Hbase

Redshift

Python

Mathematica

Matlab

SQLAMPL

Simulation Models

Constraint Programming

Multivariate Regression

Graph Theory

Linear Algebra

Galois Theory

Number Theory

Optimization Algorithms

Optimization Solvers

Game Theory

Mixed Integer

Programming

Machine Learning

Linear Programming

Statistical Analysis

Dynamic Programming

Chaos Theory

Option Theory

Combinatory Theory

Probability Theory

Optics

Differential Geometry

Network Theory

Differential Equations

Real Analysis

Numerical Analysis

Bayesian Statistics

COIN-OR

Stochastic Processes

Topology

Predictive Analytics

Mathematical Modeling

Optimization

Forecasting

Shanghai Ning Bo Los Angeles Topeka

When will it arrive? A science approach…

Loadedon truck

ArrivedPOL

Loadedon vessel

Vesseldeparted

ArrivedPOD

Loadedon truck

Arrived

12 days1 day 2 days 1 day 2 days 2 days

2 3 4 5 61

More accurate ETAs based on data science and machine learning

Optimization designed for the cloud and big-data

Next-gen algorithms,self-learning and flexible

Multi-threaded and scalable to largest data sets

Massively parallel computing process made for the cloud

Ocean Community PerformanceKey Metrics:

• Volume of trade

• On-time arrival

• On-time departure

• Total time at port

(container velocity)

• Average lateness

• Volume of trade

• Average speed

• Transit time

– Vessel transit time

– Container transit time

I T S TA R T S W I T H A N E T W O R K V I E W O F V I S I B I L I T Y

An Unprecedented Level of Responsiveness

Beyond Supply

I N F O R C O L E M A N A I P L AT F O R M ( A I P a a S )

needs to be

ordered

Auto create

in EAM

Based on

type order

via ERP

Outbound

Notification

(customers)

Enterprise Intelligence Platform

Runs by itself, cheap compute, automates for all.

Delivered with design thinking

STRATEGY

The future of the future … belongs to intelligent networked companies

• The future of the future … belongs to intelligent networked companies

• Total network orchestration is the highest and most sophisticated state a global supply chain can attain. Networked companies

win because they’re agile, fast, and efficient. They’re the first to sense and the first to respond to events, the right way. That’s

operational excellence.

• The networked supply chain combines advanced and intelligent supply chain planning, execution, and finance capabilities with

the global commerce network so companies achieve the velocity and control needed to compete in today’s rapidly-evolving

markets. Intelligent supply chain applications automate key processes from planning, through execution, to final

settlement. Advanced algorithms, optimization engines, and machine learning turn data, from across the value chain, into

actionable insights and prescribe better decisions. Integrated execution allows users to easily turn plans into action.

• For anyone who enjoys being scared and excited at the same time, AI is shaping up to be the roller coaster of choice for some

years to come. Parsing what is real and what is not—what is cool for the sake of being cool versus what can offer genuine

business benefit—will take some time. However, executives will be wise to “watch this space” and look for partners equipped to

turn the AI vision into reality. As the saying goes, just because you can’t see it, doesn’t mean it’s not there.

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