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Where Will ERP be in 10 Years

Steve Bassaw, SYSPRO Canada

ABOUT ME

20 years experience as ERP user, tech support, product manager, sales support, implementer

Specialize in supply chain, operations, MRP

APICS member 20 years

APICS Certified Supply Chain Professional (CSCP)

BCIT: Advisory Committee for Business/IT program (BITMAN)

BCIT: Academic liaison to Operations Management (OPMAN) using SYSPRO to teach ERP concepts

MAKING TECH REAL FOR MFG + DISTRIBUTION

Manufacturing / distribution professionals don’t follow technology just for the sake of technology

Too busy doing their hectic day jobs

TechnoBabble XYZ won’t get your attention

But these will:

Better supply chain management

Better ways to forecast demand

More efficient

Lower costs

Increased revenue, profits

WILL TECH DISRUPT YOUR INDUSTRY?

2016 Mint Jutras Enterprise Solution Study:

“How much risk do you face in your industry being disrupted?”

Majority (79%) say low to medium

That’s what the taxi industry said before Uber came along!

Game-changing disruptions can occur right out of the blue. Are you ready? Would you survive?

Manufacturers/Distributors lagging on tech

81% of manufacturers and distributors agree: embracing digital technologies = competitive advantage

But over 80-90% still rely at least partially on spreadsheets / manual

What are you waiting for?

AGENDA

Cloud

Mobile

Social

AI

Bots

IIOT (Industrial Internet of Things)

Blockchain

CLOUD

CLOUD

Hosted

No IT infrastructure

ERP as a subscription service

Single vs. multi tenant

CLOUD – DIFFERENT TYPES

Applications

Frameworks

Hardware

Software as a Service (SaaS)

Platform as a Service (PaaS)

Infrastructure as a Service (IaaS)

CLOUD – PROS AND CONS

Cost – short term vs. long term, capex vs. opex

Customizability

Complex/unique industry requirements

Ownership of data

Security of data

Upgrade frequency/control

Multi vs single tenant

Mobile access

Integration to legacy apps

Internet speeds

Planned/unplanned downtime

MOBILE

MOBILE

MOBILE

MOBILE – EXAMPLES OF ERP APPS

MOBILE – WEARABLES – RING SCANNERS

MOBILE – WEARABLES – GOOGLE GLASS

Scan serial number to view related manuals, videos

Use voice commands to leave notes for next shift worker

"It took a little getting used to. But once I got used to it, it's just been awesome”

"I don't have to leave my area to go look at the computer every time I need to look up something”

SOCIAL

SOCIAL - LINKEDIN

SOCIAL - ERP

AI – ARTIFICAL INTELLIGENCE

AI – WHAT IS IT

Doesn’t rely on fixed programming rules

1997 chess victory by IBM Deep Blue was programming, not AI

IBW Watson on Jeopardy was AI

System through which computers use a massive set of data and apply algorithms to "train" on—to teach themselves—and make predictions

More suitable for large volumes of data

IoT, call centers, etc.

Garbage in, garbage out still applies

AI – BENEFITS WITH ERP

Companies have lots of ERP data but struggle to transform into meaningful information for decision making

Reduce cost of a business process

E.g. Customer service

Recommend new revenue generating opportunities

If customer bought X, also recommend Y

Suggest the best NEXT interaction with customer

Phone company accurately predicted BEFORE customer left, get Customer Service to contact them

Augment people's capabilities and effectiveness of organization

Shift employee’s focus to creative, analytical, non-routine tasks

Liberate them from monotonous, manual interactions with ERP software

AI – WHAT IT IS NOT

Pulling an answer from a database in response to spoken/typed question

Not AI. Natural language processing combined with search

True AI must exhibit

Self-governance

Surprise

Novelty

Otherwise, it’s the 21st century version of The Clapper!

Businesses require AI that aligns with company goals

Learns

Anticipates

Makes good decisions

Adjusts existing processes or recommends new ones

AI – EXAMPLES IN SUPPLY CHAIN

Recognize point in supply chain that is slowing entire process

Recommend best options to fix issue within a company’s budget and resources

See that incoming shipment of parts is delayed

Immediately search for ways to get new parts through a more reliable, reasonably priced vendor

Present those options based on timeline and budget restrictions

AI – EXAMPLE: CORRECTIVE MAINTENANCE

Digital assistant (DA) helps service technician with root cause analysis for corrective maintenance issues

Service technician asks DA questions, gets evidence-based recommendations back

DA obtains knowledge from core ERP system and OEM sources

AI – EXAMPLE: PREDICTIVE MAINTENANCE

Predictive maintenance

Identify manufacturing equipment failures before they happen

Based on real-time information about actual performance of equipment

Sensors, Internet of Things (IoT)

May recommend to replace later based on actual condition

Reduces maintenance costs

AI – SOURCES OF DATA

Today

Each ERP/tech company’s AI only uses data from its own stack

Future

AI uses data from multiple sources (e.g. IBM Watson)

BOTS

BOTS – TURING TEST

BOT – ELIZA 1964

ELIZA: 1964 natural language processing computer program

Created by Joseph Weizenbaum, MIT Artificial Intelligence Laboratory

“I had not realized…that extremely short exposures to a relatively simple computer program could induce powerful delusional thinking in quite normal people.”

BOTS – SYSPRO

BOTS - SYSPRO

IIOT – WHAT IS IT

Connected “smart” machines and objects collect, share data with ERP and other systems

Not new concept, done on shop floor for decades

But data in silos, not connected

No “shop floor to top floor” communication

IIOT – “INDUSTRY 4.0”

1.0 rise of machines

2.0 mass production

3.0 computers and automation

4.0 “smart factories” built upon an “internet of things” that are interconnected and capable of intelligent self-management

IIOT – PREDICTED GROWTH

Today:

15 billion connected devices

2020:

50 billion (Cisco estimate)

200 billion (Intel estimate)

General Electric estimate:

"Industrial Internet" market will add $10 to $15 trillion to global GDP in 20 years

Current GDP of China = $10 trillion

Current GPD of US = $17 trillion

IIOT - BENEFITS

Improved flexibility on the factory floor

Reduced downtime for machines and labor

Downtime costs thousands $$/hr

Enhanced operational efficiency

Safety and security

Deeper visibility into value chain

Information can be used to drive greater insight

current state of the operation - what is going on

cause and effect - why it is going on

probability of outcomes to happen in future - what will be happening

Accenture:

84% of organizations believe they would benefit from enabling IIoT

But only 7% have developed a strategy

Opportunity to gain competitive advantage!

IIOT - EXAMPLES

Shop floor (MES Manufacturing Execution Systems)

Production rates, qty produced

Quality metrics

Caterpillar:

Wear and tear levels of customer’s equipment

“Repair before failure”

Replenish printer toner

Low toner > signal supplier > auto-create S/O > allocate stock > shipping > auto-invoice customer

IIOT – MES EXAMPLE: MACHINE AVAILABILITY

IIOT – MES EXAMPLE: MACHINE DOWNTIME

IIOT – PHASES OF ADOPTION

Phase 1: Pre-Software & Analysis

Assessment of your current IT systems and future requirements

Phase 2: Semi-Connected Framework

Some systems installed but not all connected

Phase 3: Connected Infrastructure

Manufacturing operations management (MOM) or manufacturing execution system (MES)

Phase 4: Securely Connected System

Back end software capabilities

Communication between machines

Accessibility

Security

IIOT - CHALLENGES

Challenges of getting real time data

data import

processing

security

storage

extraction

integration with analytics engines

Configuring hardware, infrastructure, software and networking in ways that rarely or never break

IIOT – SECURITY

Security firm ForeScout

Fewer than three minutes to hack many common Enterprise IoT devices

Entry point into company’s entire network

Stuxnet virus 2010

Physically sabotaged Iran’s nuclear centrifuges for enriching uranium

BLOCKCHAIN – WHAT IS IT

The infrastructure behind Bitcoin

Global, online ledger, or network of ledgers/transactions

Verified immediately by other people using the system

Protects people's privacy

Transparent enough to allow for oversight from anyone

No one group (no middle man) regulates it

BLOCKCHAIN - TRANSACTION

BLOCKCHAIN – LEGACY SILO LEDGERS

BLOCKCHAIN – SHARED LEDGER

BLOCKCHAIN – NETWORK OF TRANSACTIONS

BLOCKCHAIN – ALL NODES VERIFY TRANSACTION

BLOCKCHAIN – Fraudulent Transaction Fails

BLOCKCHAIN – SINGLE SOURCE OF TRUTH

BLOCKCHAIN – WITH INTERNET OF THINGS

BLOCKCHAIN – IOT VENDING MACHINE

BLOCKCHAIN IOT VENDING MACHINE

BLOCKCHAIN - BENEFITS

Fewer Intermediaries – e.g. banks, brokers

Faster Processes – multi-party scenarios

Security – difficult/impossible to hack

Transparency – less risk/fraud, more trust

Automation – programmable, trigger events, payments

BLOCKCHAIN - SUPPLY CHAIN ADOPTION

Chain Business Insights survey:

Most blockchain development activity to date in financial services

Other industries—notably supply chain management—now actively evaluating

Primary use case:

Improving supply chain transparency and traceability

80% of respondents envision tracking product through the supply chain

Supply chain benefits

Improves supply chain visibility/transparency

Reduces transaction costs

Enhances trust between supply chain partners

Still a long way to go before widespread acceptance

BLOCKCHAIN – EARLY ADOPTERS

U.S. Defense Advanced Research Projects Agency (DARPA)

create unhackable messaging system

Walmart / IBM / Tsinghua University (Beijing), to track movement of pork in China

Walmart / IBM pilot blockchain tracked mango supply chain

branch it came from

packing house it went through

cold storage facility was it kept

distribution center it passed through

much of the info came directly from Walmart's ERP system

Mining giant BHP Billiton: track mineral analysis done by outside vendors

Precision parts manufacturer Moog Inc

“How can the maintenance crew on a U.S. aircraft carrier have absolute confidence that the software file they downloaded to 3D print a new part for a fighter jet hasn’t been hacked by a foreign adversary?”

BLOCKCHAIN – CONSIDERATIONS, CONCERNS

How to ensure privacy of transparent shared transactions

Dr. Mark Staples: "You don't put plain-text data on a blockchain unless you're happy for your competitors to see what it reveals about your market position“

High through-put data - some scalability and performance limitations

Nature of blockchain as a distributed database with lots of nodes means not suited for big data

Potential split between evolution of global public blockchains vs. private

Interoperability, open standards

RECAP

Cloud

Mobile

Social

AI

Bots

IIOT (Industrial Internet of Things)

Blockchain

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Copyright © 2015 SYSPRO All rights reserved.