“Stargate”, a US initiative to build the largest AI data centers the world has ever seen, aims to invest $500-billion over the next four years. Saudi-Arabia and the United Arab Emirates just announced plans to buy hundreds of thousands of advanced AI chips.

And at France’s “AI Action Summit” earlier this year, public and private actors pledged investments surpassing €300 billion to advance AI in Europe.

It is very clear that expectations about the economic benefits of this technology are sky high. Yet, a recent McKinsey survey found that more than 80% of organisations worldwide are not yet seeing any tangible impact on their profits.

So where does this mismatch come from?

The key to the answer is that AI is not a stand-alone technology. For its benefits to materialise, AI has to be deeply embedded in business processes. And for that, companies have to put three pillars in place: modern cloud software, modern data management, and a consistent stack of AI technologies linking with them.

Let’s start with software: All successful companies use software to organize and optimise their business operations – from order intake and procurement to production, delivery and customer service. Yet, many enterprises still rely on legacy on-premise software – that is, a wide range of programs installed on the company’s local IT servers.

This “software landscape” often consists of disparate applications plugged together – heavily modified over the years and frequently not up to date with the latest innovations. These complex systems are costly to maintain, and they make it difficult for companies and their leaders to respond to challenges and opportunities with agility and speed.

AI applications, too, face major obstacles in legacy systems: They have a hard time grasping the company’s inner workings, making sense of fragmented and widely distributed datasets, and may not be able to find certain key information.

The first step towards powerful business AI, therefore, is the move from legacy on-premise software to modern cloud software – that is applications that are centrally managed and maintained in professional data centers, constantly updated with new innovations, and tightly linked so information can flow freely between the different parts of the company.

For companies today, this so-called cloud migration is faster, smoother and more transparent than ever before – thanks to the proven methods and advanced digital tools now available. And the prize is larger than ever before, too: integrated cloud applications work together out of the box and cover the company’s software needs end-to-end across departments.

This integration allows a car maker, for example, to reduce time and cost – say, from receiving an order through the vehicle’s production to its final delivery.

Similar benefits extend to all other industries and workflows.

A cloud migration, consequently, is more than an IT project: it is the digital foundation for a thorough modernisation of the entire enterprise, for moving from “good” to “great.”

Once in the cloud, companies can add advanced data management solutions with little effort. Think of advanced data management as a magic filing cabinet: it automatically stores and organises all documents, all information, all data automatically in the right place and in perfect order – always up to date, perfectly searchable, without duplicates and errors, smartly annotated, and everything in the right context.

In their combination, integrated cloud applications and advanced data management allow company leaders a holistic view of their enterprise. At the same time, they enable AI technologies to access, understand, and facilitate transactions across the company – assisting human users with repetitive tasks as well as with deep analyses and insights.

And the next evolution is already at hand: Based on integrated cloud applications and data management, digital coworkers – also known as “AI agents” – are now able to carry out complex work assignments. For example: find overdue invoices, identify what went wrong, resolve the issue, and make sure payment targets are met.

Realising the tremendous benefits of AI is thus about going on a journey: from on-premise software to cloud applications, then onwards to modern data management and the use of AI agents throughout the enterprise. It is this journey that unlocks the tremendous potential so many see in AI – and enables us to completely reimagine how our businesses and economies are run.

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This is according to enterprise software and digital solutions provider , which also lists AI, digital skills and closer partnerships as trends that will impact the channel.

, SAP’s partner  and ecosystems lead for MEA, says the main role that technology plays in business is pushing customers to involve partners  in strategic discussions to ensure proper guidance from the start. Effective partnerships across sectors, from government to non-profits, are essential to address industry challenges, she adds.

, MD of , concurs and notes the era of fragmented systems is ending.

She adds that unified partner ecosystems are now vital for streamlining operations, boosting collaboration and delivering value to customers while driving efficiency.

51ˇçÁ÷also identifies data and security as the top issues for organisations in 2025, with companies aware that disparate data can skew analytics and rising cyber security threats pose increasing challenges.

“Disparate data stored in different places is typically drawn up into an analytics platform, as a result, losing its contextual relevance. Actual analytics then become skewed, impacting outputs,” says Pillay.

The second biggest issue facing customers and partners is security, she continues. “Increased and more sophisticated levels of malicious intent are negatively impacting our industry at large.”

JSE-listed ICT firm says AI-driven security, zero trust models and human-centric security will be top of mind for business leaders, cyber security C-suite decision-makers, CISOs and cyber security services providers.

In addition to adopting advanced, AI-enabled threat detection systems, the company advocates a “trust no one, verify everything” architecture to protect sensitive data in hybrid work environments.

The company agrees with the notion that human error is a major cause of cyber security attacks and incidents. It underlines the need for ongoing employee training and fostering a culture of vigilance to reduce risks.

According to BCX, it understands the unique challenges African businesses face, from limited budgets to regulatory compliance and the persistent cyber security skills gap.

AI-driven operations

Taute believes AI can transform operations by enhancing decision-making through predictive insights, optimising resource allocation and uncovering growth opportunities. Partners offering AI-driven solutions will be key to meeting customer demand for automation and machine learning capabilities, Taute adds.

“By integrating AI into enablement platforms and operational workflows, partners can better anticipate customer needs, optimise resource allocation and uncover growth opportunities. Beyond operational benefits, AI also presents a significant sales opportunity for partners. As customers increasingly look for solutions incorporating AI-driven automation, predictive analytics and machine learning capabilities, tech partners can position themselves as key providers of these innovative technologies.”

The Westcon-Comstor Southern African executive adds that specialisation is becoming a key differentiator in the channel, with customers demanding tailored solutions that address industry-specific challenges.

“Partners with deep expertise in verticals such as healthcare, finance or manufacturing will stand out by delivering bespoke technology stacks and compliance-ready solutions. Distributors that support this trend by enabling multi-vendor solutions and providing specialised training will empower their partners to capture new market opportunities and thrive in niche segments. People enablement will be a serious determiner for success in 2025,” says Taute.

, GM and VP of , warns that AI moves quickly and can leave behind companies that cannot or will not adapt.

°Â´Ç´Çąôąôąđ˛âĚý held recently and said according to the Dell 2024 Innovation Catalyst study, 31% of South African respondents admit they’re struggling to keep up with the pace of disruption. “The whole industry is evolving at pace, and that creates a lot of tension within businesses. Most people understand it will have an impact.”

Balancing costs

’s highlights the challenge for companies to balance IT costs with modernisation, especially with rising expenses and AI advancements.

“Cloud repatriation, driven by cost concerns and regulatory compliance, is gaining momentum, with businesses opting for a mix of private and public cloud solutions. As businesses face increasing complexity, the cloud FinOps market is growing, with skills and resources in demand. AI adoption will require clear use cases and evidence of long-term business benefits, with prebuilt systems enabling faster implementation.

“With South African businesses under significant pressure to manage and reduce IT costs, company leaders are finding themselves in a tough spot. They need to balance these rising cost pressures with the urgent need to modernise, all while keeping a lid on operational complexity. These pressures will reach a tipping point in 2025, thanks to some unexpected cost spikes and advancements in generative AI. Because of this, many businesses are taking a hard look at their long-term IT strategies, trying to figure out how to handle the rising costs of their virtualised workloads, support both current and future needs, and streamline IT operations in an increasingly complex environment.”

Cloud repatriation is taking centre stage in 2025 as businesses reassess their public cloud strategies.

According to Ntuli, escalating costs and the need for better budget management are driving this trend. Many organisations are now opting for a strategic mix of private and public cloud solutions to balance expenses and manage resources effectively.

“As a result, FinOps is becoming essential. Projected to hit almost $40 billion by 2034, the burgeoning cloud FinOps market underscores the need for skills and resources in this area,” he says.

In his overview of issues that will continue to impact the channel, , VP, data and analytics – Middle East, Turkey and Africa and MD South Africa at IDC, lists several significant external influences, including inflation, economy and global trends.

Walker says these trends include consumer discretionary spend, COVID amortisation at enterprises, the impact of AI, import tariffs/duties and the level of technical support that will trigger more activity in the channel and will escalate the level of competition.

This article first appeared here:

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, Director of Corporate Project Programme and Portfolio Management, City of Cape Town discusses with SmartProcurement how this maturity is achieved through the transformation of existing processes and empowering people with the necessary tools and technologies, fostering an environment of efficiency and effectiveness.

People: The Foundation of Organisational Maturity in SCM and Contract Management

The journey towards organisational maturity begins with people. Effective supply chain and contract management relies heavily on the engagement and competencies of the individuals involved. The City of Cape Town prioritises the development of its workforce through continuous training and professional development, with a clear focus on enhancing skills related to contract negotiation, compliance, and supplier relationship management. Clearly defined roles and responsibilities ensure that all stakeholders understand their contributions to supply chain and contract success. This emphasis on people includes rigorous training in document and data management, ensuring that processes are managed efficiently and fostering a collaborative environment across the organisation.

Processes: Streamlining for Efficiency and Quality

Streamlining processes is essential for achieving organisational maturity in SCM and contract management. The City of Cape Town has established comprehensive standards, guidelines, and procedures to ensure consistent, efficient, and high-quality performance across all supply chain and contract activities. These processes are designed with stringent checks and balances to minimise risks, enhance compliance, and prevent errors. By standardising supply chain and contract management processes, the City ensures that best practices are followed, leading to improved procurement outcomes, cost control, and contract performance.

Systems and Technology: Enhancing Workflow and Integration

Advanced systems and technology are critical enablers of efficient workflows in supply chain and contract management. The City utilises sophisticated management tools like 51ˇçÁ÷PPM and CMS, which help enforce process compliance, automate routine tasks, and integrate various functions, including procurement, contract administration, finance, and data analytics. These technologies provide a robust framework that supports effective contract lifecycle management, supplier performance tracking, and real-time data analysis, thereby ensuring that SCM activities are aligned with the City’s strategic goals.

Data: The Core of Strategic Decision-Making

Data management is the backbone of informed decision-making in SCM and contract management. The City of Cape Town ensures that data is accurate, complete, and aligned with relevant standards, enabling predictive analysis, performance monitoring, and continuous improvement. By leveraging data analytics, the City gains valuable insights into supply chain trends, contract compliance, and performance metrics, which inform strategic decisions and resource allocation. Data-driven decision-making ensures that the supply chain and contract management functions are optimised to support the City’s broader strategic objectives.

The City of Cape Town’s approach to achieving organisational maturity in supply chain and contract management is comprehensive and interconnected, focused on building a cohesive, efficient, and effective environment. This strategy supports the City’s commitment to excellence in service delivery and its overarching strategic goals.

This article first appeared on .

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It seems many organisations have either moved some parts of their estate to , or are actively analysing their next steps. A research study done at the end of 2023 by the UK and Ireland 51ˇçÁ÷User Group () showed that 92% of their user sample are either on S/4HANA (27%) or planning to move to S/4HANA (65%). This demonstrates how much of the market is on the journey to adopt 51ˇçÁ÷S/4HANA.

No matter how you are looking at the project, moving to S/4HANA is a huge endeavour – and also the ideal time to rethink how you have implemented SAP, and how to optimise business processes.

At , we have numerous 51ˇçÁ÷data experts. We sometimes use the term ‘data surgeons’ because of their exceptional ability to slice, move and manage 51ˇçÁ÷data! Our specialist software called the  has been used by thousands of organisations around the world to copy and scramble clients and data objects for testing and training for over 24 years. And we enhanced this software even further to provide support during business projects like Mergers and Acquisitions (M&A), and transformation projects like moving to S/4HANA.

With our PRISM solutions, . We also use this capability to support any . But that is only a small part of the larger project.

To get deeper insights, I spoke to , CTO from our sister company , about his experience around what the critical factors for successful S/4HANA projects are.

Andrew Borresen | 51ˇçÁ÷Advisory Lead and CTO | G3G

Andrew is a seasoned Technology Executive with 24 years of business and 51ˇçÁ÷technology transformation leadership across consulting advisory, enterprise, and solution architecture disciplines. He has proven success in architecting solutions to support global business transformation initiatives, with experience in divestiture carve-outs, ERP platform consolidation programs through mergers and acquisitions, greenfield ERP installations and upgrades, and continuous business improvement initiatives.

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What are your top tips to clients who are starting with their S/4HANA project?

When we start to engage with clients, the first thing we do is to understand the client’s perspective on project objectives. This discussion helps us work out if there is a possibility to do some business transformation, or just a technical upgrade. And walking through this in some detail and playing it back to our clients helps us to set and manage expectations. We have seen that clients don’t always think about all the possibilities up front. So, talking about the objectives is a key place to start.

Secondly, we encourage clients to choose a proven, comprehensive methodology backed by 51ˇçÁ÷addressing business value discovery through to Application Lifecycle Management (ALM).

Then, the ace up your sleeve should be looking at accelerators and powerful software you can incorporate before, during and after your project. The EPI-USE Labs’ solutions are a good example of how clients can leverage products to bring immense value to the project. I have been impressed with the return on investment (ROI) clients can get by implementing Data Sync Manager to reduce their non-production footprint, for example.

By leveraging software and accelerators, you lower your risk and can get high predictability while reducing overall project cost and duration, and lowering the barrier of entry to S/4HANA.

Lastly, the success of your S/4HANA project can will depend on setting up some specialist teams. You need people to focus on areas such as advisory, functional, technical, Cloud infrastructure, mobility and testing. With G3G’s assessment, we take a ‘deep dive’ into the different streams needed for the project, and make recommendations across the board. Our experience has shown you need a strong track record across industries and delivery support models (cloud, technical, functional) to make the project a success.

You have touched on experts. What type of skillsets do people require going forward?

It is important that organisations are aware that a lot of the skillsets required are different. So you may have an in-house team today, but a lot of their skills will need to change. So as you consider your project, consider what blend you’re going to use from your in-house team, from consultants, or further upskilling your team in-house.

To mention two examples:

It’s critical to have Fiori expertise on your S/4HANA conversion project as well. With the interface having changed, the skill requirements are different. So your typical ABAP developers are not necessarily going to translate across to Fiori developers.

Secondly, SAP’s Business Technology Platform (BTP) is the cornerstone of SAP’s innovation strategy and supports capability around AI, workflow and external stakeholder access, as well as low code development, analytics and integration. If S/4HANA is the invitation to the party, BTP puts you straight into the VIP section where you can leverage all that 51ˇçÁ÷has to offer for digitising your business and surpassing your market competitors.

So you need to consider either upskilling your own team, or bringing in the appropriate consultants during your S/4 project, depending on how many innovations you decide to adopt and which new capabilities in BTP to introduce.

As well as expertise, you have also spoken about ‘cloud mindset’. Can you expand on that?

A cloud mindset is crucial for effective change management and project success in the new world. Methodologies have changed. And a lot more of the responsibility for the implementation now falls on the client, what we call client self-enablement. So what that means is that right from the early phases of the project, you’re starting with your change management, you’re getting your users involved in testing the system so they know exactly what they’re going to get when it goes live.

This is also helpful in supporting what are typically shorter project cycles now. We’re not wanting to do monolithic eighteen month to two-year projects anymore. We want to be able to adopt cloud solutions, including S/4HANA Cloud very, very quickly. So this is what’s required for that.

The second part of cloud mindset is also understanding that the way we make changes to the system has changed. In the past, we used to customise our core solution a lot; in the future, we want to rather customise on cloud platforms that run alongside our core solution.

So that when we want to upgrade in the future, it’s very, very easy to do so.

The new way to approach customisations is to adopt a ‘clean core’ by moving your developments and integrations to 51ˇçÁ÷BTP. What has your experience been with BTP?

The BTP platform is an excellent platform for clients to leverage. From no code/low code capabilities to leveraging the latest AI solutions, it can be a game-changer for our clients. We have recently collaborated with EPI-USE Labs in developing a BTP application for a client to manage their proof of delivery. I get excited about what we can achieve with the BTP technology to enhance the usability and adoption of 51ˇçÁ÷S/4HANA.

Any last thoughts for people to consider?

Business is always affected. However you approach your S/4HANA project, there will be an impact on the business. So, we see a lot of times we’re dealing with CIOs, and they’re trying to do a technical upgrade behind the scenes so to speak, which is all good and well, but they are mandatory adaptations that need to happen as part of an S/4 upgrade as well.

So, my recommendation is to engage your business as early as possible, even in a process of doing a proof of concept. Once you have an upgraded S/4HANA system from a proof of concept, then use it to start building consensus within your business for the S/4HANA product. Spend time with them showing them new innovations, showing them the system.

Many thanks to Andrew for answering our questions!  if you need any further info, or .

This article first appeared on the EPI-USE site:

 

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By leveraging AI technologies, SMEs can achieve performance and innovation boosts across multiple areas of the business, from financial management to sales and marketing to human capital management and product development.

The global AI market is expected to grow from $208-billion in 2023 . For SMEs, the growth of AI holds huge promise: one study found that .

However, AI is still in its relative infancy. While technology providers have made huge strides in the power and quality of their AI tools, the technology has not yet reached its full potential and can be prone to error if not deployed in an optimised environment.

The intelligent SME

The adoption of AI forms part of a broader shift among businesses to establish intelligent enterprise capabilities. An intelligent enterprise consistently applies advanced technologies and best practices within agile, integrated business processes.

For SMEs, this means establishing a powerful core that links departments, integrates business processes, connects data, and embeds intelligence to accelerate innovation and growth. And AI is the latest essential technology in the intelligent enterprise mix.

However, a successful deployment of AI in an SME requires accurate, relevant and reliable data. The better the data, the better the AI-generated outcomes.

For example, deploying AI to make decisions based on unstructured third-party data – such as social media posts by potential customers – can lead to inaccurate or downright incorrect outcomes. In contrast, deploying AI to trusted business systems, such as an SME’s enterprise resource planning solution, means the algorithm is basing its recommendations and outcomes on data that is accurate, up-to-date, reliable and relevant, leading to higher-quality outcomes that can truly drive the business forward.

Practical applications of AI

Despite the technology still being in its relative infancy, AI holds huge potential to SMEs. Unlocking its value will be a critical aspect of the success of any business in the coming years.

For SMEs, the journey to value-generating AI for business really starts with a digital transformation process that establishes a single source of truth for all business data. Here, enterprise resource planning (ERP) systems are key: cloud ERP systems enable greater speed and predictability across all of an SME’s core business processes and can scale as the business grows or expands to new markets.

With the core ERP in place, SMEs can choose to deploy AI to a wide range of business processes to accelerate daily tasks, minimise human error, cut costs and boost innovation, including:

Human Capital Management: Generative AI integrated with human capital management software can streamline content creation and provide access to in-depth analytics that provide valuable insights into the talent management and hiring process.

Finance: SMEs can increase the performance of their finance operations by leveraging AI for expense management, invoicing, auditing, financial forecasting and payments. One of the biggest challenges for SMEs is managing cash flow. AI can reduce the sales outstanding days with intelligent invoice matching to improve cash flow and keep the balance sheet healthy.

Supply Chain: In the wake of ongoing supply chain challenges, SMEs may want to leverage AI to better predict customer demand and increase production efficiency with intelligent auto-dispatching. In the manufacturing sector, SMEs can mitigate risk with preventive maintenance guided by AI that is integrated to the core production systems.

Procurement: Buying and procurement can become more agile, with AI simplifying the buying process while maintaining compliance with various internal and external controls. The use of AI can also automate the creation of sourcing events, drawing on past successes and real-time business information to provide an intuitive automated sourcing capability.

Sales & Marketing: Considering the importance of customer engagement and CX in the sales process, SMEs may also want to leverage AI for hyper-personalised product recommendations across multiple channels, with AI predicting customer behaviour to enable companies to minimise costly customer churn.

Innovation: Finally, SMEs can accelerate their innovation efforts by deploying and running AI models at scale without compromising data privacy. By leveraging the work by leading technology providers such as SAP, SMEs can also build AI into their core business applications with a library of pretrained models, accelerating the time-to-value of new innovation projects.

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As organisations increasingly embrace generative AI to derive insights, automate processes, and drive innovation, the foundation of accurate and well-organised data within their business systems becomes pivotal for realising the full potential of AI applications.

The IDC forecasts that , growing at a CAGR of more than 73%. Much of the spend will be directed to GenAI business cases where productivity boosts are paramount. found that GenAI could add the equivalent of $2.6-trillion to $4.4-trillion in productivity gains annually.

However, much of this latent potential will remain untapped unless organisations can safeguard their AI investments with accurate, dependable data. There is an indispensable connection between the correct data setup in enterprise systems and the success of generative Artificial Intelligence (AI).

Companies seeking to leverage AI as a long-term value driver must therefore ensure they maintain trust and integrity in the data powering their algorithms.

Trust drives AI value

Trust is a critical component of responsible AI adoption. By utilising reliable data, organisations can build and maintain trust with users and stakeholders, fostering a positive relationship between AI technology and society.

Trust is also important for accurate real-time decision making. In today’s dynamic and fast-paced business landscape, organisations and leaders need to make informed decisions based on accurate data-driven insights. By aligning the outcomes of analytics processes with their own strategic objectives, business leaders are better able to take optimal action and steer the company through adversity, or take advantage of emerging opportunities.

It is therefore important that the data is indeed reliable to prevent erroneous outputs which could be costly and negatively impact an organisation and its reputation. When users trust the output of generative AI applications, the business benefits from higher levels of collaboration and innovation.

To build trust and mitigate risks associated with AI adoption, companies need dependable data that holds the necessary insights and avoids bias. This increases the likelihood that businesses and end-users take the calculated risks necessary for broader AI deployment.

Advantages of data-driven business strategies

To drive greater adoption of AI solutions, organisations must continuously improve their data strategies. This provides several advantages to the success of the business, including:

Greater competitiveness: Organisations with a good data strategy gain a competitive edge when their high-quality data is partnered with powerful AI algorithms to produce better strategic choices and business outcomes.

Increased operational efficiency: Well-managed and high-quality data promotes streamlined business processes. When data is accurate and readily available, operations can more easily be optimised, resulting in cost efficiencies .

Improved innovation and scalability: By leveraging insights built on a good data strategy, businesses can identify market gaps, explore new opportunities, and create products or services that meet evolving customer needs faster than their competitors.

Organisations must also not underestimate the impact of transformative data innovations that help them harness the full power of their data to drive deeper insights, faster growth and more efficiency in the era of AI. The introduction of new data innovations enable organisations to deliver meaningful data to every data consumer with business context and logic intact – enabling them to adapt faster to market changes and make more efficient decisions. The newly-launched 51ˇçÁ÷Datasphere solutions, for example, mobilise an extensive global partner ecosystem to enable organisations to transform their business data fabric architecture, allowing them to access insights from their data wherever it resides.

Key elements of an AI-ready data strategy

Organisations that consistently unlock business value from their data-driven strategies have a few characteristics in common. The key elements to enhancing data strategies for AI readiness include:

Strong alignment with business objectives: A well-defined data strategy aligns with the overall goals and objectives of the organisation by establishing a clear roadmap for leveraging data to meet business requirements and objectives.

Effective data governance: Establishing data governance frameworks within the data strategy ensures that data is treated as a valuable asset. Clear ownership, accountability, and data stewardship protocols lay the foundation for maintaining data integrity and consistency.

The highest levels of data quality: The accuracy and reliability of digital transformation and related AI implementations hinge on the quality of the data being input into the system. Incorrect or inconsistent data at the outset can lead to errors and inefficiencies, extending project timelines and adding layers of additional costs and complexity.

The use of industry best practices: Following industry best practices for data setup ensures compatibility and optimal utilisation of the modules being implemented at lower cost and with less complexity. Adhering to recommended data structures, field configurations, and master data management principles is essential for a seamless project in support of AI readiness.

A careful and considered data migration: Proper data setup involves meticulous planning for data migration from legacy systems to the new system. This includes data cleansing, transformation, and validation processes to ensure a smooth transition without compromising data integrity.

Achieving AI readiness demands a holistic approach to data setup, data strategy, and governance. Organisations that prioritise these guidelines will be better positioned to unlock the full potential of AI, foster innovation, and maintain the highest ethical standards.

By adhering to these principles, businesses can navigate the complexities of AI deployment responsibly and contribute positively to societal and economic advancements.

The post Why We Need to Safeguard AI’s Future with Dependable Data appeared first on 51ˇçÁ÷Africa News Center.

This has become a critical value-add for organisations seeking to tap into their vast repositories of data to improve processes and engage in ongoing transformation. It is also precisely what a leading South African producer of wines, spirits and ciders wanted – to integrate its data from different business groups within the company to gain insights that could drive growth, transformation and innovation.

• The 51ˇçÁ÷technologies included , ,
• , , and

The consumer goods company is well-known in the country and also has a strong global presence. It uses to store and manage its massive quantities of data from multiple sources across business groups and units, and is in the process of moving into the to leverage innovation capabilities and bring its digital transformation strategies to life.

The company turned to to gain rich visibility into its data and to leverage next-generation technologies that would allow for seamless and sustainable growth over the long-term.

The integration included multiple technologies across the business, allowing for the company to fully realise the potential locked within its data. Azure Synapse was used to ingest the data with Azure Data Factory for the data science teams, allowing them to build models with Azure Machine Learning. This has allowed for the company to quickly and effectively query the data to gather knowledge and make informed decisions.

With the solution in place, the firm can analyse its consumer data and find trends and patterns that it can use to better manage risk, increase sales, optimise products and services, and refine offerings. Some of the most relevant insights provided by the solution include:

• Visibility into the most popular products and services.
• The most lucrative customer categories.
• The weakest performance areas within the company.

In addition, the solution allowed for the company to take third-party sales data from aggregators to compare sales and products between competitors. This part of the data architecture enables the data science teams to build models that thread the insights found in the data into accessible reporting that decision-makers can use to create relevant marketing strategies and to increase market share.

By combining a team of data architects, data modellers, data engineers and 51ˇçÁ÷HANA developers, Intellinexus was able to refine the technology stack perfectly for the client. This allowed for the company to truly revolutionise how it uses, accesses and understands its data, and to benefit from an architecture capable of scale to meet changing business demands and expectations.

The company is now working with Intellinexus on an ongoing basis, focusing on more use cases and solutions to enhance operations and processes and remain on track with its digital transformation strategy.

Intellinexus’ expertise across a wide range of consultants, engineers and developers allowed for the company to create the perfect solution. Today, the client has exceptional access to rich data insights that can be used on demand to enhance decision-making and drive the business into new markets while delivering superb customer experiences.

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Blood transfusions are commonly used to provide blood or blood components to a patient who has either lost blood due to an accident or suffer from a medical condition that affects their blood.

Typically, blood is donated anonymously and then stored by hospitals or blood banks until needed. Due to the critical nature of the procedure, donated blood must be collected, stored, categorised, and transported using extremely high levels of safety and care.

Donors must be carefully screened for a variety of medical conditions and lifestyle aspects to ensure the blood is free of potential risks to the patient. Blood is tested according to national guidelines and stored according to blood type.

It is estimated that one in ten people entering hospital need some kind of blood transfusion as part of their treatment.

Data, traceability vital to safe transfusions

The key to successful, lifesaving blood transfusions is accurate documentation to ensure consistency and avoid any unnecessary risk. Due to the sensitive nature of blood, the way it is transported and stored is equally important, especially when the blood supply chain network covers a large geographic area where donated blood must travel thousands of kilometers.

Ultimately, hospitals and clinics seek the ability to track the journey from vein to vein in real time with accurate data and while maintaining the integrity of the value chain.

Here, blockchain technology holds huge potential. Blockchain encodes data in a secure and transparent way that can add visibility and security to the blood transfusion value chain. Blockchain could be a more effective way of storing the precise records that allow medical professionals to use donated blood with confidence during life-saving and other medical procedures.

Using blockchain, medical facilities can register vital data about every step in the blood transfusion value chain, from donation to testing to transport, storage and ultimately its use in a medical procedure.

Due to strict requirements for how blood is stored, technologies such as IoT can also play an important supporting role by tracking the temperature at which the blood is stored and recording that to the blockchain. As blood travels through the value chain, the data stored to the blockchain creates an audit trail that links the entire value chain from donor to recipient.

Advances expected from emerging tech

Other emerging technologies hold promise for greater efficiency and transparency in the blood transfusion value chain. Augmented reality could solve one of the key issues with blood donations by helping medical professionals find the vein more consistently and without the trial-and-error that most donors experience.

Machine learning and artificial intelligence also holds huge promise for driving improvements in the blood transfusion value chain, especially since so much data is already created and stored to ensure transfusions are safe and effective.

used machine learning to optimise the time between blood donation intervals to ensure donors don’t experience adverse outcomes. Using the model, the researchers could estimate the risk of adverse outcomes and how such risks may change with longer or shorter intervals. This data could then inform how often the donors could donate blood without suffering iron deficiency or other complications.

So-called digital footprinting using AI and machine learning could also help reduce errors when doctors order blood samples. Using RFID integrated to an AI platform, doctors could improve specimen identification and reduce specimen labelling errors while also ensuring accurate transport tracking.

Technology platforms unlock new capabilities

New advances in Laboratory Information Management Systems have also unlocked access to unprecedented levels of visibility and control over lab data and other associated processes. A Laboratory Information Management System is used to manage samples, lab users, instruments and other lab functions, as well as back-office operations such as invoicing.

For example, the 51ˇçÁ÷Quality Management helps businesses implement and run quality control processes, and is designed to prevent defects, enable continuous process improvement, and establish sustained quality control programs. Global pharmaceutical companies use 51ˇçÁ÷Quality Management as a primary Laboratory Information Management System to drive supply chain processes, maintain high levels of quality control during production processes, and support research and development.

When matched to a business transformation platform that enables the seamless integration of new technologies, there is virtually no limit to the powerful capabilities that laboratories can unlock. With an intelligent core in place and a quality management system to maintain the highest information standards, laboratories and other stakeholders can protect the integrity of the life-saving blood transfusion supply chain while enabling greater innovation.

The post Vein-to-vein-to-value: How Tech is Enhancing Life-saving Blood Transfusion Value Chain appeared first on 51ˇçÁ÷Africa News Center.