Turn potential into performance How AI can transform your supply chain network

Introduction

AI is set to revolutionize supply chain networks. But while generative AI grabs most of the

headlines, it should be viewed in the broader context as part of a continuum of intelligent

technologies and automation capabilities that include traditional process automation, classical

machine learning (ML) models, Internet of Things (IoT), and digital twins as well as large language

models (LLMs).

Led by AI, these technologies have the potential to impact the entire supply chain and the

possibilities appear endless. But to turn this potential into tangible business value, AI requires firm

foundations: a modern and flexible technology infrastructure and effective management of the

data that fuels it.

In this paper, Coupa and Accenture provide a succinct overview of the opportunities for AI across

supply chain functions like sourcing and supply chain planning, and cross-functional outcomes

such as supply chain sustainability, resilience, and supply assurance.

We also offer recommendations on how to get started with this truly transformative technology

– including implementing AI responsibly, safely, and ethically – to help you reap the maximum

benefits for your business.

According to Accenture’s Technology Vision 2024,

95% of executives agree that generative AI will

compel their organization to modernize its

technology architecture.

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Power your supply chain with AI

The potential business value of AI is enormous.

Accenture analysis suggests that 43% of all

working hours across the entire supply chain

function will be positively impacted – with

generative AI either automating activities (29%)

or significantly augmenting the work of human

employees (14%). Multiply that by the huge

global supply chain workforce and you get

some idea of the cumulative value that could

be achieved in terms of time and cost savings,

and employee and customer satisfaction.

Generative AI excels in language-related

activities, and on its own will not be suited

to every supply chain task. However, while

activities involving numerical processing or

requiring greater levels of complex reasoning

will remain the domain of traditional process

automation and machine learning, generative

AI can still add significant value across different

aspects of the supply chain.

of the 122 supply chain processes analyzed – from design and engineering, planning, sourcing, and manufacturing to fulfillment and service – can be reimagined to deliver greater speed, accuracy, and efficiency using generative AI.1

58%

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https://www.accenture.com/content/dam/accenture/final/accenture-com/document-2/Accenture-Supply-Chain-Networks-In-The-Age-Of-Generative-AI.pdf#zoom=40

Understand supplier performance

Machine learning can accelerate supplier vetting and assessment, and predictive analytics using historical can predict

future performance. If a particular supplier was always 10 days late with delivery, for instance, machine learning can

help to identify the contributing factors behind the delays and predict the potential lateness of other suppliers based

on similar characteristics such as size, location, weather, and so on.

Generative AI can play an important role here by taking the machine learning results and translating the data (which

is often highly technical and complex) into plain and easily understandable language that delivers usable information

and insights on assessing supplier performance to guide decisions on any remedial actions required.

Accelerate purchase order and invoice processing

While these key financial processes are already highly automated, the related communications may still be largely

manual. By rapidly converting large volumes of unstructured data from e-mails and other sources, Generative AI can

provide important contextual understanding to improve processing and execution speed, efficiency, and accuracy. In

turn, this can help maximize payables outstanding while avoiding penalties to optimize working capital and cash flow.

Transform supply chain planning

The combination of comprehensive data models and powerful AI is transforming supply chain planning. When

demand rises, do you need a new warehouse or additional manufacturing capacity? Will you need new suppliers in

different locations to cut delivery lead-times or reduce costs?

To help you answer these and other questions, the latest integrated scenario planning solutions like Coupa leverage

digital twin functionality so you can visualize your current supply chain model and use advanced algorithms to

model various future scenarios. Generative AI can make complex machine learning outputs more explainable and

understandable to enable faster and smarter decision-making. Together the technologies can help build more

proactive and resilient supply chains that save time and money while delivering better customer service.

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https://logisticsviewpoints.com/2024/05/23/integrated-scenario-planning-as-a-margin-multiplier/

Leverage the cross-functional value of AI

Improve supply chain sustainability

Supply chain modeling is also a powerful tool for enhancing sustainability measurement, performance, and

compliance: a key challenge facing many organizations.

Accurately mapping company spend to emissions, for example, is time-consuming and laborious work. Accenture

has developed a generative AI solution that can sift through millions of lines of spend data across multiple languages,

and automatically map each line item to relevant emissions factors. Once mapped, the information can be fed into a

supply chain modeling tool like Coupa.

of CEOs say a key reporting and compliance challenge is the lack of ESG data measurement across the value chain2 63%

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https://www.accenture.com/content/dam/accenture/final/a-com-migration/pdf/pdf-177/accenture-tech-sustainability-uniting-sustainability-and-technology.pdf

Build supply chain resilience by design

It’s estimated that supply chain disruption has cost businesses $1.6 trillion in missed revenue opportunities over

the last two years3. As a result, one of the key supply chain management challenges is having the ability to better

understand supplier networks and their co-dependencies to asset risk and vulnerabilities.

Coupa has a global community of over 10 million suppliers with authorized customer spend data anonymized

to deliver visibility and better decision-making at scale. Generative AI can augment existing AI-powered solutions

that analyze this and other structured data with analysis of much larger volumes of unstructured data to produce

deeper insights. Chatbot interfaces can also be used to make these insights more accessible and improve supplier

collaboration.

Resilience can also be built into supply chains themselves through the design and planning solutions referred to

above that can model potential disruptions, assess their effects, and inform mitigation strategies to reduce risk.

Increase supply assurance and improve revenue

Manufacturers need total confidence in their supply chain to deliver the right materials and parts in the right place,

at the right time, at the right quality, and in the right quantity. Although direct spend can be highly complex with

large networks of suppliers, many suppliers’ systems and processes are still manual – and therefore slow, inefficient,

and inaccurate. Telephone orders can go unrecorded, and e-mailed purchase orders missed or unacknowledged –

potentially resulting in manufacturing delays and late deliveries.

Generative AI can streamline and accelerate processes by turning unstructured data into structured data: parsing

e-mails, for example, and communicating back to the buyer for action. These improvements result in reduced plant

shutdowns, increased customer service and, ultimately, improved margins.

Optimize working capital

For companies dealing with large numbers of suppliers and high volumes of invoices, paying at exactly the right time

to maximize incentives and minimize penalties has become a business essential. Generative AI can simplify and speed

up this process by analyzing all outstanding invoices to ensure consistently prompt payment that builds supplier

loyalty while optimizing working capital.

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https://www.forbes.com/sites/jillstandish/2024/03/25/how-genai-can-help-retail-supply-chains-withstand-shocks/?sh=56ec2a754c05

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How to get started with AI

Learn more This unique combination of Coupa’s community-generated AI network and

market-leading source-to-pay platform delivers margin-multiplier capabilities to

help companies enhance growth, productivity, efficiency, resiliency, and sustainability.

To find out more about how Coupa is using AI to improve Total Spend Management,

please visit our website.

For the latest Accenture viewpoint on generative AI, read their 2024 report:

Supply chain networks in the age of generative AI.

Get your data AI-ready

Collaborate with your suppliers

AI relies on huge volumes of data, so an effective enterprise data strategy is an essential prerequisite. However, many

organizations are still struggling with managing data across their supply chain networks and will need to extend this

with large volumes of mixed-modality unstructured data. The good news is that generative AI itself can be applied to

this task by automatically analyzing and extracting knowledge from supply chain data to feed other AI use cases.

A note of caution here. Companies are understandably cautious about providing confidential business-critical

information to external generative AI solutions and strict data security and privacy policies are critical to ensure the

ethical and responsible use of AI.

AI can benefit buyers and suppliers. Collaborating with key suppliers on generative AI pilots will help build confidence

and trust while demonstrating the mutual benefits of the technology.

This collaboration can be extended across the ecosystem by leveraging community intelligence for scalable

insights. Coupa, for example, has a vast trove of $6 trillion of customer contributed spend data across its total spend

management platform to fuel AI models. Companies can use AI-powered insights to benchmark their businesses,

identify trends, and predict spend patterns to reduce risk, increase efficiencies and be more profitable.

© Coupa Software Inc. 2024. All Rights Reserved. © Accenture 2024. All Rights Reserved.

https://www.coupa.com/ https://www.accenture.com/content/dam/accenture/final/accenture-com/document-2/Accenture-Supply-Chain-Networks-In-The-Age-Of-Generative-AI.pdf#zoom=40

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