Effective Implementation of Digital transformation

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Executive Summary

This paper aims at producing a plan that will help facilitate the implementation of the digital

transformation strategy in PrüvIT Technologies and the Canadian Sheep Federation. It describes

steps required to create and apply efficient knowledge management system that meets the

company’s objectives as well as strategies that should be followed during the development of a

knowledge management framework.

The report starts with an outline of the organization’s business involving information on the

industry category, size, structural format, and main business functions that the organization

performs. Following this, it defines the key areas of KM requirements and issues in the

organization in order to introduce the KMS solution for the organization.

The proceeding section of the report is the heart of the document where the essential elements of

the KMS are discussed: knowledge capture, organization and storage, sharing and collaboration,

transfer, and maintenance and update. All of them are described in detail and provide the reader

with specific recommendations and operational tactics that may be applicable to the

organization’s specific context.

Moreover, it also examines the threats, risks, and obstacles that may likely occur in the course of

the implementation process. It outlines plans for overcoming challenges and recommendations

for managing change to implement the KMS effectively in the organization, given key factors

like culture, leadership, and employee participation, change management, and professional

development.

Such success also entails identifying potential benefits or outcomes the organization will achieve

if the KMS is implemented properly. The use of KPIs and metrics is brought forward to assess

the impact and performance of this system on organizations and knowledge sharing. Lastly, the

report reiterates the recommendations as well as the confines of the suggested solutions.

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Table of Contents
Executive Summary...................................................................................................................................2
Objectives of this Report...........................................................................................................................5
Problem Statement.................................................................................................................................... 7
Company Overview................................................................................................................................... 9
Organizational Goals and Objectives.....................................................................................................10
Knowledge Capture and Integration.....................................................................................................11
Knowledge Organization........................................................................................................................ 13
Knowledge Storage and Access..............................................................................................................15
Knowledge Sharing and Collaboration..................................................................................................16
Knowledge Transfer................................................................................................................................17
Knowledge Maintenance and Updates...................................................................................................18
Implementation Considerations.............................................................................................................19
Possible difficulties, threats, and limitations.....................................................................................19
Mitigation Strategies and Measures...................................................................................................20
Benefits and Measurement......................................................................................................................22
Key Performance Indicators...................................................................................................................23
Recommendations...................................................................................................................................24
Conclusion................................................................................................................................................ 25
References................................................................................................................................................ 26

Effective Implementation of Digital transformation

Objectives of this Report

1. Enhance Traceability and Supply Chain Transparency

Assess the AgroLedger project that has integrated the concept of traceability using

blockchain technology and propose solutions for increasing the system’s extendibility

and compatibility with the continuously developing livestock sector.

Discover other technologies and other ways by which the issues of supply chain

transparency, real-time sharing of information and keeping of records of such information

through the life cycle of the product can be enhanced.

2. Improve Animal Health Monitoring and Disease Control:

Evaluate the effectiveness of the existing biometric identification system; Face IT and

recommend some improvements or recommend an even better method for identification

of health status of the animals using facial recognition or other forms of biometrics.

Examine the possibilities of using AI and ML for the detection of possible diseases like

the foot melt disease and the subsequent prevention.

3. Address Connectivity and Technology Adoption Challenges:

Suggest solutions to help close the gap between conventional approaches and today’s

technology platforms, as well as to overcome organizational culture issues as they apply

to livestock businesses.

4. Enhance Data Privacy and Security:

Assess the current state of data governance and privacy and make changes to enhance the

protection of the stakeholders’ data to encourage their confidence in digital

transformation strategies.

5. Ensure Regulatory Compliance and Integration:

Evaluate the current approaches to legal requirements as applied to food safety and

welfare or the environment in conjunction with the use of new technologies.

6. Promote Stakeholder Adoption and Training:

To learn the tactics that should be employed, develop a comprehensive training and

education plan that can make all stakeholders proficient at the adoption of the new

technologies, managing resistance to change, and the implementation of new practices.

7. Establish Performance Monitoring and Continuous Improvement:

Examine the leaders and stakeholders’ goals to determine appropriate key performance

indicators (KPIs) to assess the success and output of the digital transformation

approaches for organizational productivity, supply chain performance, and knowledge

exchange.

Problem Statement

This research identifies several challenges facing PrüvIT Technologies and the Canadian

Sheep Federation in the livestock industry in which they are unable to optimally implement their

digital change management strategies. Despite their pioneering efforts in integrating blockchain,

AI, biometrics, and analytics to enhance disease control, food safety, and supply chain

transparency, the following key problems persist:

1. Limitations in Traceability and Supply Chain Visibility

While AgroLedger, the trace technology that was piloted to track sheep through the supply

chain, can track animals within the four corners of the supply chain you can barely begin to

contemplate the metric tonnage of the other demands that accompany the expansive equation of

the livestock equation. Coordinating the flow of information and its availability in an end-to-end

manner, in real time, is a major issue across the members of a supply chain ecosystem.

2. Animal Health Monitoring and Disease Prevention

Symptoms like the foot melt disease are fatal to the livestock industry, and once out it causes

major harm to animal health, production, and farm output. Thus, despite the current

advancements made by the FaceIT system proposed by researchers, it is still possible that some

improvements or other solutions would be necessary in order to achieve the level of precision in

tracking animals’ health state and early signs of their illnesses.

3. Connectivity Limitations in Remote Farming Locations

Stable internet connection is essential in utilization of digital technologies especially in areas

of farming which may be in the rural regions. Insufficient connectivity reduces the integration

capacity, slows down the exchange of information and the adaptation of innovative solutions,

which the organization needs to exploit the real-time analysis functions and related decision-

making powers.

4. Technology Accessibility and Adoption Barriers

The livestock industry has always used conventional practices; there is resistance when it

comes to adopting new technologies because the stakeholders are used to these practices.

Extending from traditional practices to the modern IT solutions and taking an account of user-

friendliness and stakeholder’s persuasion remain a very crucial challenge to meet.

5. Data Privacy and Security Concerns

Since both, PrüvIT Technologies and the Canadian Sheep Federation work with sensitive

information regarding the health and functioning of the livestock, the privacy of the

stakeholders’ information is crucial. Proper data management and protection yet facilitating data

exchange and cooperation is a fairly major challenge to deal with.

6. Regulatory Compliance and System Integration

Some of the policies that commonly apply to the livestock industry include those ones

concerning to food safety, animals’ treatment, and environmental impact. Adhering the above

regulations when embracing new technological systems of functioning that interconnects with

the old and traditional systems presents a major challenge as it slows down the processes

involved in the embrace of the passed organizational transformation agenda.

7. Training and Education Needs

When it comes to training or educating the workforce towards the acceptance of new

technologies and digitization of workplace practices, extensive packages are needed. The issues

concerning knowledge gaps between the existing situation and the state-of-the-art technologies,

and the lack of controllable methods for the stakeholders to enhance their competencies in using

the digital solutions is still an important problem.

Company Overview

The companies, namely: PrüvIT Technologies and Canadian Sheep Federation are part of

the leading organizations aiming at the industry of livestock management with the use of digital

technologies. This partnership reflects a synergy between a non-profit industry association and a

for-profit technology company focused on the advancement of innovation and improvements in

the sustainability of the Canadian sheep industry.

Canadian Sheep Federation was established with the aim of protecting the Canadian

sheep’s farmers interests. It is a non-governmental body involved in encouraging producer,

processors, government and other players towards improvement of sheep industry (About CSF,

n.d). The implementation of this objective has helped foster better traces within the industry,

which introduced the program known as AgroLedger, a trace technology.

PrüvIT Technologies Limited is a for-profit company that is an subsidiary of the

Canadian Sheep Federation established to market the AgroLedger technology and expand its

usage beyond the sheep industry (About, n.d). The firm applies blockchain, artificial intelligence,

biometrics, and analytics to improve disease management, food security, and supply chain

management in livestock farming.

Altogether, they are transforming the system of tracing and monitoring sheep and other

livestock by making it more digital. Their primary business strategies concern the design and

implementation of advanced methods of data gathering, improved traceability, and solutions to

the problems encountered during the digitalization of all aspects related to raising livestock.

Their flagship trace technology, AgroLedger, is a blockchain-based innovation useful in

optimally tracking sheep from the supply chain to enhance transparency and accountability.

Moreover, PrüvIT Technologies provides solutions like FaceIT (facial recognition for stock),

ReadIT (Data capture using RFID and Biometric), and FreshOrigins (Transparency solution for

Supply chain) to help the company implement digital transformation in all the stages.

Still, both with Canadian Sheep Federation being a national association for producers of

approximately 10,000 sheep farmers, and PrüvIT Technologies being a new subsidiary, they are

quite influential. This they do with producers, processors, regulators, and other technology

partners with an aim at unlocking innovation and employing advanced technologies to the

livestock sector.

Organizational Goals and Objectives

Both the companies namely PrüvIT Technologies and the Canadian Sheep Federation

have defined clear goals and objectives in line with their mission of revamping the management

of livestock. Their mission is to improve the sustainability, transparency and efficiency of the

Sheep sector and the Livestock industry in Canadian context and that through the use of

technology.

As a major goal, the enhancement and development of the sheep and other livestock

series traceability system is also planned. In realizing this, they seek to use blockchain and

advanced analytical tools which shall enhance the supply chain accountability and transparency.

This goal is achieved by their leading product, AgroLedger through which one can track the

livestock from producer to consumer.

Another goal that has to be met is in the area of food safety and quality assurance, where

comprehensive monitoring and disease control systems have to be established. Applications such

as FaceIT (biometric facial recognition for identifying livestock) and ReadIT (sensory RFID and

biometric data collection tool) also help capture useful data which if analyzed, can help in early

identification of instances of possible breakout of diseases and thereby reducing on chances of

the diseases breaking out.

Knowledge Capture and Integration

An important concern is how to gather and use information that is often dispersed across

different sources such as farm operations, processing facilities, and governmental regulatory

agencies. This information must be accurate and complete so is important to reflect all aspect and

used for decision making and analysis.

As the numerous actors across the supply chain create huge volumes of data, getting the

knowledge generated structured in a manner that it is easily accessible and usable, is an emergent

necessity. It is critical to have a coherent and efficient knowledge management system for the

knowledge base and successful collaboration between employees.

Management often faces challenges when adopting new technologies and digital

solutions as most of the stakeholders stick to conventional approaches (Weerasinghe & Nirere,

2022). The other crucial factor that has been identified as a major issue and challenge that needs

to be dealt with is the ability to provide proper training and education to enable people to become

proficient in the use of the mentioned technologies.

Concerns to enhance stakeholder information privacy and security are critical given the

nature of data being sought in relation to livestock health and business. Implementing strong data

management and protection policies is one of the most important requirements of KM.

A number of rules and policies pertaining to food safety, animal rights and welfare, and

the management of the negative impact of the livestock industry on the environment apply to the

livestock industry. Addressing these regulations during the adoption of new technologies and the

management of the knowledge inherent to these processes present a considerable difficulty.

In recent years, many organizations have attempted to adopt new digital solutions into

established applications or workflows. Interconnectedness is a key necessity for efficient

knowledge management and the flow of work and business on the supply chain (Kassaneh et al.,

2021).

To ensure that information is gathered effectively from various sources, and information

sharing is done properly, PrüvIT Technologies and the Canadian Sheep Federation will

implement a holistic approach based on some of the key issues discussed under digital

transformation. The following strategies will be implemented:

1. Internet of Things (IoT) and Sensor Integration

The team will integrate IoT devices with the existing AgroLedger platform, enabling

automatic data capture and storage on the blockchain ledger, ensuring transparency and

immutability.

2. Mobile Applications and Field Data Capture

Create easy-to-use smartphone applications for farmers, veterinarians, and field officers for

entering observations and records of treatments and other data at the farm level.

3. Artificial Intelligence (AI) and Machine Learning (ML)

Incorporate the use of big data AI and ML to process data from different sources such as IoT

sensors applications data feeds from other sources such as the weather market and changes in

regulatory frameworks.

4. Stakeholder Collaboration and Knowledge Sharing

Design safe and accessible block chain environments for interaction between stakeholders

(such as producers, processors, retailers, researchers, regulators) and sharing information as well

as experience and know how related to the field.

Knowledge Organization

For the efficient indexing and usage of existing knowledge, it is prerequisite that PrüvIT

Technologies and the Canadian Sheep Federation apply a profound knowledge organization plan

based on digital transformation ideas and tools.

The first activity will involve creating a sound ontology and taxonomy, which organizes

knowledge into domain specific categories and sub-categories of concepts, relationships and

hierarchies applicable in the livestock industry. Semantic technologies and knowledge graphs

will be adopted to encode and connect cognate concepts, thus allowing future and flexible

navigation and other the discovery in knowledge sources.

In addition, the organization will also use a decentralized knowledge indexing model that

utilizes the AgroLedger blockchain technology, through which it will effectively be possible to

store, organize, and protect knowledge assets. Knowledge updates and modifications shall be

consistent with the following characteristics; distributed ledger technology, and substantially

improve on data integrity and transparency.

The metadata management shall occur systematically with the metadata being stored and

linked to assets in a consistent manner, an example being source, date, and location data,

keywords amongst others. Metadata enrichment of material such as music, video and text will be

made easier through the use of tagging and classification systems that are automated and based

on machine learning and natural language processing.

For easy understanding and knowledge management the organization will create and

implement the knowledge maps and charts which will help in identifying the dependencies,

connections and logical hierarchies between the various types of knowledge within the

organizational knowledge base. The obtained results of scientific research activities will motivate

data visualization tools and techniques for further representation of complex knowledge

structures in an easily understandable form.

Integrated search functions will be provided to search the integrated knowledge base,

knowledge databases and external sources within a single click to get a holistic view of the

available knowledge. Both Natural language processing and technologies of Semantic search will

help the database inquiries to become more accurate and oriented on the current tasks, thus

making the process of knowledge finding more effective.

The delivery of knowledge will also be made personal where the system will be designed

to deliver knowledge based on an individual choice of preference, roles and access rights.

Intelligent recommendation services and knowledge-based agents will match the right

knowledge resources based on a user’s learning context and previous interaction history.

Last but not least, a decentralized knowledge curation platform will be created where

some end-users including but not limited to subject matter experts, stakeholders, and key

community influencers will be able to participate in the review, validation, and organization of

knowledge assets. Incentive mechanisms and reputation systems will help to draw crowds and

guarantee the originality and verity of the curated knowledge.

Knowledge Storage and Access

To address the knowledge storage solution, one of the key components that will be

employed is the usage of a distributed ledger that is based on blockchain. The proposed solution

will build on the organization’s current digital platform known as AgroLedger; this will act as

the distributed and tamper-proof ledger to store and provide accountability for the recorded

knowledge assets. This will provide accurate, secure, and auditable information and knowledge

resources to end-users, along with improved knowledge management and control.

In addition to bitcoin-based storage, the organization is to use a distributed file system

and a distributed object storage. This will enable one to store petabytes of multimedia and

unstructured data which include images, videos, and documents to name but a few, more so

without compromising on the distribution of these data across the availability and durability of

the system as well as its scalability. A backup and data replication system will be implemented to

allow for easy replication and data redundancy to avoid loss of critical data.

Knowledge assets will be made more retrievable through a well secured and easily

navigated knowledge management system. With this platform, there will be an easy and unified

interface for linking the multiple types of storage elements, and show control for the roles and

permissions. Sophisticated searching and indexing technologies including Elasticsearch and

Apache Lucene among others shall also be incorporated with a view of enhancing the process of

acquisition of knowledge on particular topics of interest.

For the deployed strategies of remote and mobile access, a web application will be

created as well as mobile application, this will allow users to access and contribute to knowledge

resources regardless of their geographical location or device. All of these applications will be

built using newer Web 2. 0 technologies and will operate under strict security protocols to

protect any sensitive data that may be collected.

Also, it will develop cloud relationships with cloud service providers to strengthen the

organization’s knowledge management system as it would need to be scalable and secure. This

would help in accomplishing efficient management of resources in the network as well as

distributing the load suitably; it also includes the management of high availability and disaster

recovery and backup strategies.

Knowledge Sharing and Collaboration

To foster a culture of knowledge sharing and collaboration among employees and

stakeholders, PrüvIT Technologies and the Canadian Sheep Federation will implement a

comprehensive suite of mechanisms and tools:

1. Blockchain-based collaboration platform

Through employment of the blockchain technology, it will be possible to create a secure and

transparent platform that will be effective in creating an environment whereby producers,

processors, researchers, as well as regulators will be in a position to share handy information,

best practices, and codified domain-specific knowledge.

2. Virtual communities of practice

Through knowledge spaces, specialists in certain subjects, representatives of the company’s

staff, as well as partners and investors will be able to continue their discussions, share valuable

experiences, and work together on knowledge-related activities and projects. Such communities

will be moderated by moderators and backed up by sophisticated CT and collaboration tools.

Knowledge Transfer

PrüvIT Technologies and the Canadian Sheep Federation will implement the following

strategies to ensure the effective transfer of critical knowledge from experts to newcomers or

across different teams and departments:

1. Mentorship and Apprenticeship Programs

Skilled employees that possess vast knowledge in a particular area will be grouped with

employees that are new to that particular area or employees that want to learn about a specific

area of knowledge. There is an opportunity for organizational learning and skill acquisition since

tacit knowledge can be passed on by means of training, observation, and drills.

2. Knowledge Capture and Documentation

Domain knowledge gathered from specialists will be stored and indexed using various

methods that include one-on-one interviews, brainstorming sessions and screen captures. This

documented knowledge will be stored in a central knowledge bank so it will always be available

and can be retrieved easily in the future.

3. Expert Lectures and Webinars

Power point presentation or recorded versions of experts’ lectures, seminars, and webinars

will be conducted to increase the availability of specialized knowledge derived from the fields of

industry experts, researchers, and other thought leaders to a wider audience within the

organization and its stakeholders.

Knowledge Maintenance and Updates

1. Continuous Knowledge Auditing

Knowledge audits will be carried out from time to time so as to determine the reliability,

correctness, and applicability of the knowledge assets. This will entail domain specialists,

interested parties, as well as, automated modes on various aspects of data validation and quality

control.

2. Knowledge Expiration and Archiving

It is obligatory that all kinds of knowledge assets will either have some definite expiry or be

subjected to review after a certain period of time depending upon the importance and type of

KAM.

3. Knowledge Feedback Loops

There shall be feedback systems which enable the user, stakeholder and external sources to

give their feedback on any knowledge asset as regards to its quality, its completeness and its

relevance. This feedback will be part of the knowledge acquired and incorporated into the

knowledge update and management cycle.

Implementation Considerations

Possible difficulties, threats, and limitations

1. Organizational Culture and Resistance to Change

It has been evident that the livestock industry has used traditional methods in the course of its

activities, and implementing new ideas and innovations in this field may be met with mistrustful

reactions on behalf of the beneficiaries who are accustomed to such practices. Bearing this in

mind, eradicating culture, as well as promoting the spirit of change and adaptability, may be

regarded as rather difficult.

2. Data Privacy and Security Concerns

Since the information has to do with the health of the livestock and production the issue of

data privacy and security comes into question especially when it involves important persons.

Maintaining both the protection of data and adequate data sharing and collaboration is another

major concern.

3. Integration with Legacy Systems

Applying new innovations within pre-existing IT environments and frameworks can often

prove to be a rather difficult process. The processes of knowledge management and functional

organization must be integrated to make the interrelated supply chain activities as efficient as

possible.

4. Scalability and Future-Proofing

It is crucial to include provisions for the scalability of the knowledge management system as

well as to design it in a way that will allow it to be enhanced in future for compatibility with new

technologies and for expansion to meet the increasing demand. Failure to future-proof the above

system might result to ageing an become obsolete or require a new overhaul which may be so

expensive.

5. Stakeholder Engagement and Buy-In

Gaining commitment and engagement of multi-stakeholders including producers, processors,

researchers and regulators is always cumbersome. The long-term motivation of both parties and

their self-interest that will push them to share knowledge is very important in the system.

6. Connectivity and Infrastructure Limitations

The nature of digital solutions requires reliable internet connectivity, and better infrastructure

especially in farming regions, which may at times be quite remote. Overcoming these limitations

can be expensive and practically complicated.

7. Regulatory Compliance

Several significant issues can be identified when it comes to compliance with the different

laws and standards in this sphere as well as to the application of the new technologies and the

related knowledge management: the need to adhere to the different regulatory requirements on

food safety, animal treatment, and environmental aspects.

Mitigation Strategies and Measures

1. Change Management and Communication

We will outline measures that should be put in place to support change, such as task-related

and communication plans along with training activities.

2. Data Governance and Security Framework

We plan to implement a well-coordinated data management framework that will effectively

deal with such issues as privacy and security of data, method of accessing and managing data

besides adhering to local/international policies and standards.

3. Phased Implementation and Pilot Testing

The plan includes implementing the adaptation of the metrics in a step-by-step manner,

using pilot projects and then expansion. It means that there is a possibility to make the

corrections to the implementing solution, to hear from the stakeholders and to reveal the possible

problems before the large-scale implementing.

4. Legacy System Integration and Data Migration

Our team suggests coming up with a detailed integration and data migration plan that would

integrate and work in synergy with existing legacy systems and practices advanced in the

organization.

5. Scalability and Flexibility

The team should always ensure that the features of the knowledge management system are

made in such a way that it can be easily changed and adapted in the future.

6. Infrastructure Investments and Partnerships

To do this the management should seek partnership with ISPs, telecommunication firms and

technology companies to work on challenges of connectivity and infrastructure especially in the

farming regions. Consider other connection types, including satellite or a mesh network.

7. Continuous Training and Support

Provide training at different levels to incorporate all the fellow stakeholders into the

knowledge management system training the entire human resource for the utilization of the

knowledge management system.

Benefits and Measurement

1. Enhanced Supply Chain Transparency and Traceability

The knowledge management system will enable end-to-end visibility into the livestock

supply chain by leveraging blockchain technology, AI, and advanced analytics. This

transparency will foster trust among consumers, ensure regulatory compliance, and facilitate

rapid identification and resolution of issues.

2. Improved Disease Control and Animal Welfare

The integration of biometric data, IoT sensors, and predictive analytics will enable early

detection and prevention of diseases, such as the foot melt disease (Akhigbe et al., 2021). This

proactive approach will enhance animal welfare, reduce losses, and improve overall productivity.

3. Increased Operational Efficiency and Cost Savings

Streamlined knowledge sharing, collaboration, and access to best practices will optimize

operational processes, reduce redundancies, and minimize waste. This efficiency gain will

translate into cost savings and improved profitability for the organization and its stakeholders

(Ikpe & Shamsuddoha, 2024).

4. Accelerated Innovation and Competitive Advantage

PrüvIT Technologies will cultivate an environment conducive to innovation by fostering a

culture of continuous learning, knowledge sharing, and collaboration. This will enable the

development of new products, services, and solutions, providing a competitive edge in the

livestock industry.

5. Effective Knowledge Retention and Transfer

The KMS will ensure the preservation and transfer of critical knowledge from experts to

newcomers, mitigating the risk of knowledge loss due to employee turnover or retirement.

6. Improved Decision-Making and Risk Management

Access to accurate, up-to-date, and comprehensive knowledge assets will enable data-driven

decision-making, thereby reducing risks and increasing the likelihood of successful outcomes.

Key Performance Indicators

Metric KPI

Supply Chain Visibility and Traceability Track metrics such as end-to-end traceability

coverage, time-to-trace, and accuracy of

traceability data

Animal health and welfare Disease incidence rates

Mortality rates

Overall livestock productivity

Operational efficiency Inventory turnover rates

Process cycle times

Cost savings achieved through process

optimizations

Knowledge sharing and collaboration Number of active contributors

Knowledge assets shared

Level of engagement within virtual

communities and collaboration platforms

Employee productivity and retention Employee productivity

Knowledge retention rates

Employee satisfaction and engagement levels

Recommendations

1. An implementation strategy that will be needed to be adopted by PrüvIT Technologies is

the implementation through pilot projects in order to realize some of the problems which

affect the company so that they may be fixed before passing to the next level of

implementation.

2. It should encourage proactive knowledge sharing and collaboration and this should be

achieved by having motivation techniques, games and even awards that are given to

people who actively contribute.

3. Additionally, the organization must appoint a specific knowledge management group

assigned for system supervision, data quality check, and development.

4. Entering formalised collaborations with technology suppliers, academic establishments,

as well as industrial bodies will help PrüvIT Technologies get hold of innovative

solutions, know-how, and information from outside the company.

5. Last but not least, to maintain the efficiency of the knowledge management system as a

long-term solution, the company should update and adjust it periodically regarding the

shifts in the industry, changes in the legislation, and the ever-changing demands of the

key stakeholders.

Conclusion

Digital transformation is impacting livestock industry in Canada positively through this

beneficial partnership of PrüvIT Technologies and Canadian Sheep Federation. AgroLedger,

FaceIT, and ReadIT are some of the products being offered by the company, which uses

technologies – blockchain, AI, and IoT to improve traceability, disease detection, and foods

security. It targets increasing the chain value, ensuring the stakeholders’ accountability, and

enhancing the organizations’ operations through knowledge management. Some of the risks that

are inherent to this initiative include: resistance to change, data privacy issues, and infrastructural

bottlenecks. The suggested mitigations include the phased approach, skill development and

training and, cooperation with stakeholders. The expected advantages consist of enhanced supply

chain visibility, enhanced control of the diseases, the enhancement of the organization process,

and the enhancement of innovations These outcomes will be tracked by key performance

indicators to make sure the overall long-term success and relevancy. Finally, this partnership

establishes a new benchmark for the livestock industry and illustrated how digital technology can

revolutionize farming.

References

About CSF. (n.d.). Cansheep. https://www.cansheep.ca/about-csf

About. (n.d.). Www.pruvit.io. https://www.pruvit.io/about

Akhigbe, B. I., Munir, K., Akinade, O., Akanbi, L., & Oyedele, L. O. (2021). IoT Technologies

for Livestock Management: A Review of Present Status, Opportunities, and Future

Trends. Big Data and Cognitive Computing, 5(1), 10.

https://doi.org/10.3390/bdcc5010010

Ikpe, V., & Shamsuddoha, M. (2024). Functional Model of Supply Chain Waste Reduction and

Control Strategies for Retailers—The USA Retail Industry. Logistics, 8(1), 22.

https://doi.org/10.3390/logistics8010022

Kassaneh, T. C., Bolisani, E., & Cegarra-Navarro, J.-G. (2021). Knowledge Management

Practices for Sustainable Supply Chain Management: A Challenge for Business

Education. Sustainability, 13(5), 2956. https://doi.org/10.3390/su13052956

Weerasinghe, L., & Nirere, B. (2022). CHALLENGES OF DIGITAL TRANSFORMATION: A

case study of the restaurant industry.

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