Digital supply chain

• Introduction

The global marketplace is a dynamic organism, constantly

evolving and demanding agility from businesses. Traditional
supply chains, often siloed and lacking real-time data insights,
struggle to keep pace with this rapid change.
However, a revolutionary approach is emerging: the digital supply
chain. This interconnected network leverages technology and
data to transform logistics, offering enhanced efficiency,
responsiveness, and visibility. This project delves into the core
principles of digital supply chains, exploring their definition and
the transformative potential they hold for modern businesses.

• Definition

A digital supply chain is an intelligent ecosystem that integrates all

aspects of traditional logistics. It encompasses raw material
sourcing, production, warehousing, transportation, and delivery,
seamlessly connecting these processes through a network
powered by advanced technologies.
These technologies include:
Internet of Things (loT): Sensors embedded in physical
objects generate real-time data about location, condition, and
performance.
Artificial Intelligence (Al): Machine learning algorithms
analyze data to predict demand, optimize routes, and identify
potential disruptions.
Blockchain: This secure, distributed ledger technology
facilitates transparent and secure transactions throughout the
supply chain
•A Literature Review :
1-Supply Chain Management: Supply Chain Management is
management of material, money, men, and information within and
across the supply chain to maximize customer satisfaction and to get an
edge over competitors.

2-Review of Literature:
-Supply Chain Management is a network of facilities that produce raw
materials, transform them into intermediate goods and then final
products, and deliver the products to customers through a distribution
system.
-It spans procurement, manufacturing and distribution (Lee & Billington
1995) the basic objective of supply chain management is to “optimize
performance of the chain to add as much value as possible for the least
cost possible.
-In other words, it aims to link all the supply chain agents to jointly
cooperate within the firm as a way to maximize productivity in the
supply chain and deliver the most benefits to all related parties (Finch
2006).
-Adoption of Supply chain management practices in industries steadily
increased since the 1980s.
- A number of definitions are proposed and the concept is discussed
from many perspectives.
-However Cousins et al. (2006); Sachan and Datta (2005); Storey et al.
(2006) provided excellent review on supply chain management
literature.
-These papers define the concept, principals, nature, and development
of SCM and indicate that there is an intense research being conducted
around the world in this field they critically assessed developments in
the theory and practice of supply management.
-Gunasekaran and McGaughey (2003) extended the scope of SCM
beyond material management, partnership,information technology to
the Total Quality Management areas like management commitment,
organizational structure, training and behavioural issues.
-As firms' survival lies on integration, a good understanding of the
integration process is a key aspect in SCM. Mouritsen et al. (2003)
discussed that basic hypothesis “the more integration (wider the scope)
– the better the management of the chain" is not always true and
proved that it depends very much on the “environment" of the supply
chain and the power relations between the participants in the supply
chain.
- Authors proposed a set of management techniques and tools to
analyze successful SCM strategies.
-It is also observed that research is not limited to hypothesis testing and
data analysis, but more advanced techniques like simulation, Artificial
Neural Network, and Fuzzy logic are also used for optimization and
decision making in SCM. Koh and Tan (2006) used the principles of fuzzy
logic for analyzing and monitoring performance of suppliers based on
the criteria of product quality and delivery time where as Chiu and Lin
(2004) showed how the concepts of
collaborative agents and artificial neural networks (ANNs) can work
together to enable collaborative supply chain planning (SCP).
-It appears from literature review that researchers have studied supply
chain management from a system perspective, or the systemic natures
of interactions between the participants of supply chain are observed.
Although numerous studies views SCM from different perspectives, this
paper gives the better understanding of supply chain activities
•Phases
•Now if we talk about the benefits that companies can
get from these.

1-Streamlining the flow of information:At present, significant time is

spent on non-value added activities like gathering data from various
departments, verifying if production has commenced with suppliers,
checking the status of trucks, and other minor yet time-consuming
status checks. However, with an end-to-end connected system, this
information can be accessed with just a click of a button, or
alternatively, any exceptions can be promptly identified. This improves
visibility across the entire value chain and facilitates timely decision-
making.

2-Planning automation: The daily process of creating MIS reports to

obtain production and dispatch numbers is a tedious and heavily reliant
on human efforts. However, with a connected system in place, this
process could be easily automated to generate production and dispatch
plans, from the source to the point of sale. This would allow planners to
spend more time verifying and adjusting these plans, making the
system more fool proof and free from human errors and biases. As a
result, this automated planning process would be more logical and
signal-driven, enabling better planning and decision-making.

3-Lower Operational costs: By implementing the aforementioned

improvements, companies could achieve lower operational costs,
leading to a positive return on investment for the implementation of
such complex systems. A one-day reduction in inventory could result in
a significant reduction in working capital. Moreover, enhanced visibility
across the value chain would reduce sales losses and eliminate dead
inventory.
4-Increase productivity:Digitalize and automating the supply chain
enables companies to improve supply chain efficiency, speed up
processes, provide better insights, and cut down manual errors, which
all help to reduce total acquisition costs. Logistics teams are thus
relieved of low-value-added
tasks (such as filling in delivery notes, for example) and can focus their
resources on managing more strategic processes.

As mentioned above, logistics teams no longer have to fill in

administrative documents, (re)enter data or search for information. As
Julien Morin, Sales Director of the software
division (Easy WMS) at Mecalux, a leading company in the global
market for intralogistics systems and storage solutions, points out:
‘Digitalising the supply chain increases the company’s productivity
substantially, by around 40%.’

•Drawbacks:

Cybersecurity

Challenge: Digital supply chains are susceptible to cyberattacks, data

breaches, and ransomware threats.
Solution: Invest in robust cybersecurity measures, including encryption,
multi-factor authentication, and regular security audits to protect data
and maintain the integrity of the
supply chain.

The information system and data

Today, the main challenge of supply chain digitalisation is still on the

technical front. This mainly applies to companies’ current information
systems as well as the availability and
quality of data. It is vital for companies to implement a solid technical
foundation based on clear processes and governance to initiate this
digital shift.

• DIMENSIONS

The digital supply chain refers to the integration of digital technologies

into traditional supply chain processes to improve efficiency, visibility,
and agility. Here are some key dimensions of the digitalsupply chain:

1. Data Integration and Visibility: Integration of data from various

sources including suppliers, manufacturers, distributors, and customers
to provide real-time visibility into the entire supply chain network. This
includes leveraging technologies such as IoT sensors, RFID tags, and
advanced analytics to track goods and monitor inventory levels.

2. Predictive Analytics and Forecasting: Utilizing advanced analytics

techniques such as machine learning and predictive modeling to
forecast demand, optimize inventory levels, and anticipate disruptions
in the supply chain. This helps in reducing stockouts, minimizing excess
inventory, and improving overall responsiveness.

3. Automation and Robotics: Implementation of automation and

robotics technologies to streamline warehouse operations, improve
order fulfillment accuracy, and increase the speed of product delivery.
This includes automated material handling systems, robotic picking
systems, and
autonomous vehicles for transportation.

4. Digital Twins: Creating digital replicas of physical assets, processes,

and systems within the supply chain to simulate and optimize
operations. Digital twins enable scenario analysis, predictive
maintenance, and continuous improvement by providing a virtual
representation of the supply chain in real-time.

5. Blockchain Technology: Leveraging blockchain technology for secure

and transparent transactions across the supply chain. Blockchain
ensures immutability, traceability, and authenticity of data, which is
particularly valuable for tracking the provenance of goods, verifying
product authenticity, and enhancing trust among supply chain partners.

6. Supplier Collaboration Platforms: Deploying digital platforms for

seamless collaboration and communication with suppliers and other
partners. These platforms facilitate real-time information exchange,
collaboration on product design and development, and coordination of
production
schedules to improve supply chain efficiency and agility.

7. Demand-Driven Supply Chains: Shifting towards demand-driven

supply chain strategies that focus
on responding dynamically to customer demand signals. Digital
technologies enable closer alignment between supply and demand by
enabling real-time demand sensing, demand shaping, and flexible
manufacturing and distribution capabilities.

8. Sustainability and Environmental Impact: Incorporating digital

solutions to monitor and optimize the environmental impact of supply
chain operations. This includes using data analytics to identify
opportunities for reducing carbon emissions, optimizing transportation
routes, and minimizing waste throughout the supply chain network.

9. Supply Chain Resilience and Risk Management: Enhancing resilience

and risk management capabilities through the use of digital tools for
identifying, assessing, and mitigating supply chain risks. This involves
scenario planning, supplier diversification, and the implementation of
contingency plans to minimize the impact of disruptions such as natural
disasters, geopolitical events, or global pandemics.
10. Customer Experience and Personalization: Leveraging digital
technologies to enhance theoverall customer experience by providing
personalized products, services, and delivery options. This includes
using data analytics to understand customer preferences, offering
customizable products, and providing real-time shipment tracking and
delivery notifications.

•Implemention

A digital supply chain strategy encompasses the adoption and

integration of digital technologies throughout the supply chain
operations to enhance efficiency, improve
decision-making processes, and respond proactively to market
dynamics. This strategic approach leverages the power of data analytics,
artificial intelligence (AI), the Internet of Things (IoT), and blockchain
technology to create a responsive, transparent, and efficient supply
chain network. The ultimate goal is to transform traditional, linear
supply chain models into dynamic, interconnected systems capable of
predictive analytics, real-time visibility, and automated decision-making.

The transition from traditional to digital supply chain models marks a

significant evolution in how businesses manage their operations.
Traditional models, often characterized by
manual processes and siloed operations, struggle to cope with the
challenges of today’s fast-paced market environment, such as demand
volatility, supply disruptions, and the increasing need for transparency
and sustainability. Digitalization addresses these challenges by
introducing agility and resilience into the supply chain, allowing
businesses to anticipate changes, respond to disruptions more
effectively, and meet customer expectations for speed and reliability.
This article aims to equip businesses with the knowledge and tools
necessary to successfully implement a digital supply chain strategy.
Through an exploration of actionable
strategies, insights, and best practices, readers will learn how to
navigate the digital transformation journey, from assessing current
capabilities and setting clear objectives to
selecting the right technologies and integrating them into their supply
chain operations

Table of Contents
• Building the Foundation for Digital Transformation
o Assessing Current Capabilities
o Setting Clear Objectives
• Key Strategies for Digital Supply Chain Implementation
o Data Management and Analytics
o Investing in the Right Technologies
o Integrating Systems and Processes
• Overcoming Common Challenges in Digital Supply Chain
Transformation
• Charting the Digital Supply Chain Transformation
• 5 Key Benefits of a Digital Supply Chain
o 1. Enhanced Visibility and Transparency
o 2. Increased Efficiency and Reduced Costs
o 3. Improved Customer Satisfaction
o 4. Agility and Flexibility in Operations
o 5. Data-Driven Decision Making and Innovation
• The Future of Digital Supply Chains
o Emerging Trends and Technologies
o Sustainable and Ethical Supply Chains
o Collaboration and Ecosystems
•Examples:

Take an e-commerce website, for example. Its digital supply chain

includes the website’s developers, its administrators, the cloud services
company that hosts the website’s data, the CMS provider, and the
devices that consumers use to access the website. In addition, every
third-party technology provider whose code provides functionality to
the website — e- commerce plugins, personalized recommendation
engines, advanced analytics services, inventory tracking solutions,
custom product builder, chatbots, etc. — should also be considered part
of the digital supply chain.

There are several examples of digital transformation in supply chain

management. Here are a few:

1-Internet of Things (IoT) sensors: IoT sensors can be used to track

inventory levels, monitor
equipment performance, and optimize logistics routes.

2-Blockchain: Blockchain technology can be used to create a secure and

transparent supply
chain, providing end-to-end visibility and traceability.

3-Artificial Intelligence (AI) and Machine Learning (ML): AI and ML can

be used to analyze data and optimize supply chain processes, such as
demand forecasting, inventory
management, and logistics planning.

4-Cloud computing: Cloud-based supply chain management systems

can provide real-time visibility into inventory levels, streamline
communication between suppliers and customers, and improve
collaboration across the supply chain.
5-Robotic Process Automation (RPA): RPA can be used to automate
repetitive tasks, such as data entry and order processing, freeing up
employees to focus on more strategic activities.

6-IoT-enabled sensors and devices: IoT (Internet of Things) devices

such as sensors, RFID tags, and GPS trackers can be used to track
inventory, monitor supply chain operations, and optimize logistics.
These devices can provide real-time data on the location, condition, and
status of goods, enabling businesses to make data-driven decisions and
improve supply chain efficiency.

7-AI-powered predictive analytics: AI (Artificial Intelligence) can be

used to analyze vast amounts of data and generate insights that can
help businesses optimize their supply chain operations.
-Predictive analytics can be used to forecast demand, optimize
inventory levels, and reduce lead times, improving supply chain
efficiency and reducing costs.

• Investment for Scalability: Research accentuates the

imperative for businesses aspiring to be supply chain leaders to invest in
digital technologies. Integrating AI and machine
learning into an organization’s strategic planning and
operations processes facilitates agile decision-making and
adaptability, which are paramount in navigating the complex
supply chain ecosystem.

• Supply Chain Digital Transformation ROI: A 2023

survey depicts a notable uptick in digital-related budgets
among manufacturing organizations, with 47% increasing their digital
budgets by up to 20% for the year. A significant 59% of respondents
described their digital ambitions as “ambitious,” reflecting a robust
drive to adopt new technologies and processes as part of their ongoing
plans.
• Defining the Scope: The ROI of digital transformation is
substantially tethered to defining the accurate scope of
transformation. Identifying specific pain points, setting clear
goals, and envisaging the expected outcomes are crucial steps in
avoiding an unfocused and wasteful digital endeavor.

• Technological Maturity: Various facets of the supply chain,

such as inventory management, transportation, and warehouse
equipment management, are at different stages of digital maturity. For
instance, while 91% of respondents are digitizing data and processes in
inventory management, only 31% are utilizing predictive analytics. This
indicates a significant room for advancing the use of sophisticated
technologies to harness actionable insights from data.

• Rapid Technological Adoption: The swift pace of digital

technology adoption over recent years has engendered
substantial shifts in the industrial sector, rendering digital
transformation not an option but a necessity to ensure
sustainable growth and resilience against uncertainties.

References