The future of supply chains - Australian Industry Standards · The future of supply chains Simon...

The future of supply chains

Simon Rowe

au.linkedin.com/in/simon-rowe-58b28516https://www.forbes.com/kpmg/the-great-rewrite/#/0

—

27 September 2017

https://www.forbes.com/kpmg/the-great-rewrite/#/0

https://www.forbes.com/kpmg/the-great-rewrite/#/0

2© 2017 KPMG, an Australian partnership and a member firm of the KPMG network of independent member firms affiliated with KPMG International Cooperative (“KPMG International”), a Swiss entity. All rights reserved. The KPMG name and logo are registered trademarks or trademarks of KPMG International. Liability limited by a scheme approved under Professional Standards Legislation.

As the pace of change continues to accelerate the supply chain and logistics sector is at the center of disruption and is being transformed.

5 key mega trends

Big Data &

Big Analytics

Big Data and Big Analytics

1

Block Chain


2

Supply Chain Led Business

Models


3

Automation &

Supply Chain Technologies


4

Capabilities &

Skill Sets


5

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Enhancing supply chains through big data analytics

Big Data &

Big Analytics


1


The proliferation in technology and data within supply chains

Deliver step changes in efficiency, responsiveness, risk management or service levels for supply chains in Australia and New Zealand

“We have a terabyte of data but no information”- Vice President, Supply Chains at a Leading US Chemical Corp

56% of supply chain executives do not have access to real-time reporting

“These advanced analytics capabilities are now being used to take a cross functional view of an organisation where commercial, finance and supply chain operations are able to combine the vast data pools and make customer centric decisions whilst balancing cost, revenue and profit drivers.”- Andrew Underwood, Advisory Lead Partner, European Tax Efficient Supply Chain Management

80% of all cyber breaches occur in the supply chain

50% have a limited knowledge of risk and compliance issues

13% do not have complete end-to-end visibility of supply chains


Volume & Velocity

Variety

More

Less

Less More

Core Transactional Data (Laggards) Internal Systems Data (Majority) Other Data (Early Adopters)

• Origination and Destination

• ERP Transaction Data

• Demand Forecasts

• CRM Transactional Data

• Transportation Costs

• Delivery Times and Terms

• Barcode Systems

• On-Shelf Availability

• RFID

• Mobile Location

• Claims Data

• Delivery Expedite Instances

• EDI Invoices/ Purchase Orders

• Competitor Pricing

• Machine-generated Data

• Web Logs

• Weather Data

• Customer Surveys

• Traffic Data

• Call Centre Logs

• Customer Location and Channel

• Internet of Things

• GPS-Enabled Big Data Telematics

• Intelligent Transport Systems

• Call Logs Voice Audio

• E-mail Records

More complex, more added value, more

investment required

Less complex, Less added value, Less

investment required

Veracity

‘Other’ sources available that are ‘Big’ in Volume, Velocity & Variety


Value Accessible

Analytical sophistication

DescriptiveWhat happened?

DiagnosticWhy did it happen?

PredictiveWhat will happen?

PrescriptiveHow can we optimise?

AdaptiveHow do we learn?

Describe the ecosystem under consideration using data to identify trends

Understand why we get the performance we get and what caused it

Model the ecosystem and simulate scenarios to predict likely future outcomes

Prescribe actions to take for optimising performance outcomes

Learn from user behaviour to increasingly focus skilled people on exceptions

Learning from the past to chase future performance

Most organisations

Maturing organisations

Leading organisations

AI / Machine Learning

Analysing these ‘Big’ sources of structured and unstructured data

Such would be obscured to uncover hidden patterns & insights and is evolving from ‘Descriptive’ to ‘Adaptive’ techniques


More accurate estimation of demand by accessing data of sales,

market trends, competitors’ data, and relevant local and global

economic factors

Increased visibility of inventory levels, demand, and

manufacturing capacity; hence more accurate production and

distribution scheduling

Real-time conducting of big data analysis within the warehouse ERP system and

identifying inventory levels, delivery miss-matches, and incoming deliveries

Full transparency at the SKU level and fully automated replenishment systems combined with demand forecast data that eliminate under-/overstocking and optimise inventory ranging

Monitoring of delivery routes, traffic data, weather in real-time and rerouting if necessary for capacity and asset sharing

Real-time optimisation of complex webs of distribution hubs, plants, and warehouses based on the material flow data

Supply Chain Operations

DHL “Smart Truck” re-sequencing delivery routes in real time

KPMG Delivers ‘Retail Forecasting’

Tesco E-labeling ‘Surge/Dynamic Pricing’

Leveraging Big Data analytics

in supply chains' provides rapid scenario development, faster decision making and ultimately enables supply chains to become more demand driven.

Organisational Strategy Identify Prioritise Deploy Repeat




Blockchain is the emerging technologies that will remove barriers to integration and enable a supply chain marketplace of participants

Block Chain


2


Blockchain is the emerging technologies that will remove barriers to integration and enable a supply chain marketplace of participants

Blockchain is a shared, programmable, cryptographically secure and therefore trusted ledger which no single user controls and which can be inspected by anyone along the Blockchain

Block Chain


2


Blockchain is the emerging technology that will remove barriers to integration

and enable a supply chain marketplace of participants

AI Match-making criteria for servicescapability

capacity

cost

quality of service

eco footprint

Production and transportation units authenticate their service offerings in the blockchain. Even Customers can register their surplus assets on the blockchain.

Exchange of units and formulation of service packages happen through short-term, self-orchestrating supply networks.

Smart contracts verify execution of each service match.

Blockchain is the underlying technology to decentralize supply chains and create full transparency.


• Fraud Prevention

• Transparent Distributed Database

• Smart Contracts

• Information Integrity

• Identity Verification

• Data Clearance

• Legal Bots

Blockchain technologies will enable buyers, operators and customers of supply chains to benefits from enhanced efficiency, connectivity and security


Organisations such as Amazon and Pet Circle are wildly successful business models led and enabled by supply chain and logistics…………

Amazon’s raid rise to global prominence has been powered by a supply chain and logistics engine enabled by technology unlike anything we have seen before.

The complexity of managing up to 500m SKU’s, 300m users and 35m transactions per day is orchestrated by a supply chain designed and enabled around effective use technology and automation

Locally Australian start ups are introducing disruptive models to provide consumers superior service and tailored solutions enabled through supply chain process innovation

Pet Circle has exploded onto the Australian pet retail scene introducing disruptive subscription supply chain models to predict and smooth demand and deliver to your door bulk items for less ($) than a major pet retail could

Supply Chain Led Business

Models


3

13© 2017 KPMG, an Australian partnership and a member firm of the KPMG network of independent member firms affiliated with KPMG International Cooperative (“KPMG International”), a Swiss entity. All rights reserved. The KPMG name and logo are registered trademarks or trademarks of KPMG International. Liability limited by a scheme approved under Professional Standards Legislation.13

Disruptive supply chain led and enabled business models and morphing to network based

models to speed up supply chain flows and remove waste across the supply chain

Emerging supply chain led organisations leverage network based models that allow all participants to work as one virtual organisations sharing data and demand signals allow the chain to respond quickly to customer changing demand signals

Traditional supply chains are reactive to demand changes and restricted by the linear planning and replenishment frameworks that increase the amounts of inventory and working capital deployed across the supply chain network


Automation and supply chain technologies are providing solutions that are scalable and

cost effective to met the ever increasing demands of consumers

Tote, split & case picking Mixed case pallet building Pick face replenishment High density buffer storage Multi order profile

4 -7 times Increasedthroughput Increased utilisation Precise footprint Flexibility Improved accuracy

Goo

ds to

Pe

rson

Considerations Benefits

Picking Transport utilisation Robotic process automation

ASRS - Multi shuttle

Rob

otic

s Eliminates 80% of manual handling Reduces WHS exposure Reduced operating costs Improved efficiency

Robotics Operations

Pick to Light/Voice

Pick

ing

Split case picking operations Multi zone picking with high ‘line intensity’ Consistent product flow is required

Increase throughput ‘line’ rates up to 110 lines per hour Increases zone picking efficiency through ‘skipping’

Automation &

Supply Chain Technologies


4




Leveraging emerging technologies throughout the supply chain is increasing in

prominence due to decreasing cost however don’t get carried away by the hypeWearable Technology

Uses:• Augmented reality devices enable asset

identification and pick instructions• Wearables monitor staff to prevent

fatigue and provide hazard alertsExample: Warehousing providers are experimenting with using augmented reality devices to increase pick rates. Considerations: IT asset intensive and potential social implications.

RFID/GPS

Uses:• Asset tracking and identification• Receive real-time data• Monitor damage and identify hazards Example: Healthcare providers use RFIDs to track assets, monitor patient temperature and ensure pharmaceutical product standards are maintained. Considerations: Capabilities and IT infrastructure required to utilise large volumes of data.

Mobile and Telemetrics

Uses: • Mobile field force enablement• Route optimisation • Predictive maintenance Examples: Telemetrics are used throughout the mining industry to monitor asset usage and maintenance requirements. Considerations: IT asset intensive and challenges with data quality.

Drones

3D/4D Printing

Uses: • Asset inspection • Delivery • Security monitoring

Example: A UK Rail provider uses drones to survey tracks condition and inspect potentially hazardous assets.

Considerations: Capabilities required to operate drones and challenges associated with visual inspection.

Smart labelsUses:• Asset tracking and identification• End to end product lifecycle management• Mange reverse logisticsExample: Smart labels are used to track products throughout the supply chain and reduce security risks. Considerations: Initial quality of master data and ongoing data management required.

Uses:• Manufacturing to demand• Reduced requirement for warehousing• Affordable low volume productionExample: Clinicians can place orders on the spot for 3D-printed models of patients' bones reducing lead times. Considerations: Applicable primarily for only certain product types and for low volume production needs

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The capabilities and skillsets required for professionals in the supply chain and logistics

sector is changing from the conventionally operationally savvy to commercially savvy

• Data and data analytics

• Supply chain statisticians

• Simulation and optimisation competent

• Some skills and capabilities will disappear sooner than you think through robotic process automation

Capabilities &

Skill Sets


5


Supply chain professionals who understand analytics tools and embrace unstructured

exponential real-time data is will drive the next phase of supply chain success

Key big data tools and platforms and techniques to enable supply chain data management

• Ability to provide dynamic dashboards that integrate with visualisation tools

• Secure access to periodically updated dashboards through Microsoft Azure. Example visualisations for proposals and presentations are also available

• Delivery of standard and custom developed visualisations

• Data exploration & modelling tools• Algorithm execution including predictive analytics, optimisation

and simulation• Development tools and support model covering a broad range of

industry use cases.• Analytic Insight Library (AIL) with pre-defined routines

• Secure data storage & authenticated access• Search engines for discovery & analysis• Mapping of complex data for multiple uses• Support for Big Data and other unstructured data including text,

social media, location, and sensor data

• Flexible Interfaces to extract data from sources• Standard connectors to all major platforms• Transformation to cleans and structure data• Data management, governance, and integration• Information Governance framework for architecture, data

ownership, and master data management


Attracting talent in supply chain has been a challenge for sometime and these emerging mega

trends will prove no different so we must think and structure our approach differently

18

Capability requirements

Challenges

Attraction

Retention

Motivation

Tactical Approaches

• Buy

• Build supply chain lead or Technology lead

Strategic Approaches

• Developing Innovation and Disruption Culture ‘Fail Fast’

Capability Application

Supply Chain Statistics

Supply Chain Forecasting

Supply Chain Optimisation

Supply Chain Stimulation

Capability Description

Awareness of methods of statistical estimation and sampling

Understanding of qualitative and quantitative methods of forecasting

Capability to adopt analytical and numerical methods of optimisation

Redesigning supply chain processes using simulation models, data visualisation, and data repositories


The accelerating application and implementation of these disruptors will reshape, resize and

recalibrate the workforce and the skill sets and capabilities required

• Increased awareness for people working in the supply chain and logistics industry of changing nature and scope of their roles (RPA will take over labor intensive simple tasks)

• Accelerating capability and skills realignment to meet these changes will be increasingly important as the pace of change accelerates the cycle times for aligning relevant training to jobs of the future will continue to compress

Visiting a clients customer experience centre to first hand experience the rising role of robotic process automation


Part 1: How big data is shaping the supply chains of tomorrow

Part 2: Key big data tools and platforms to enable supply chain data management

Part 3: Leveraging data analytics for supply chain process improvement and risk management

Part 4: Disruptive technologies, analytics and the future of supply chains

I explore the topic of Big Data and its emerging applications in supply chain management over a four part thought leadership series that is available for download…….

Simon Rowe

LinkedIn: au.linkedin.com/in/simon-rowe-58b28516


Thankyou

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© 2017 KPMG, an Australian partnership and a member firm of the KPMG network of independent member firms affiliated with KPMG International Cooperative (“KPMG International”), a Swiss entity. All rights reserved.

The KPMG name and logo are registered trademarks or trademarks of KPMG International.

Liability limited by a scheme approved under Professional Standards Legislation.

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