took place at Sun City, North West Province, on 10 聽and 11 July 2023.

Over the past 10 years, cloud technology has redefined entire industries and changed how companies run their day-to-day businesses. 麻豆原创 has made a long-term commitment to become a fully-cloud company itself, and adopt 麻豆原创 standard solutions. In this regard, Dr Oliver Gutzeit, Vice President, Experience Technology 麻豆原创, 麻豆原创 SE Germany, presented on the topic of how 鈥樎槎乖粹�檚 Digital IT Organisation Paves The Way To 麻豆原创鈥檚 Future鈥�.

Gutzeit clarified: 鈥榃e run 麻豆原创 with 麻豆原创, using the full technology stacks. We are enabling our business transformation with the full integration of the IT department, keeping people at the heart of the business.鈥�

He noted that today鈥檚 business agility requirements have created a need for new business models that allow for growth, innovation and sustainability, adding: 鈥淪ustainability is embedded in everything we do at 麻豆原创, and our own transformation is influenced by these values. 麻豆原创 makes data-driven decisions but takes care to keep our culture, and therefore our people, in mind.

鈥淎t 麻豆原创, we are facing the same challenges as any other business, including the need to be attractive as a company to acquire talent, while also being cognisant of cybersecurity and sustainability issues. Our own IT division plays a crucial role in bringing the IT systems and business processes together.鈥�

Gutzeit advised that putting people at the centre of the business is more important than ever, clarifying: 鈥淲ithout people you can鈥檛 solve the organisation鈥檚 other issues. We have an excellent corporate culture at 麻豆原创: innovation is within our DNA.鈥�

In terms of catalysing business transformation through culture change, Gutzeit presented the following important points for a company to bear in mind:

路 聽 聽 聽 聽Cultivate an innovation mindset;
路 聽 聽 聽 聽Change thinking patterns and lead by example;
路 聽 聽 聽 聽Invest in skills development and enable career growth; and
路 聽 聽 聽 聽Create a culture of life-long learning.

With regards to the all-pervasive topic of generative artificial intelligence (AI), Gutzeit presented the following as 麻豆原创鈥檚 aims around AI:

路 聽 聽 聽 聽Scale high quality and deliver use cases;
路 聽 聽 聽 聽Prioritise best-in-class big data and AI platform;
路 聽 聽 聽 聽Become a global AI development partner and AI thought leader; and
路 聽 聽 聽 聽Focus on people, agility and organisational development.

He added: 鈥淵ou can talk about technology but you have to actually experience its power in order to become familiar with it. Therefore, at 麻豆原创, with the advent of commercial generative AI tools entering the consumer landscape in late 2022, 麻豆原创 took note immediately, and enabled our employees to play with generative AI within a safe and secure environment. We were rewarded by receiving 105 good business cases from our employees, and it is notable that these cases came from people who are not employed within the technology department.

鈥淭his is consistent with 麻豆原创鈥檚 overriding ambition to help the world run better, and improve people鈥檚 lives. This aim is admittedly a huge vision, but it lies at the heart of everything we do,鈥� Gutzeit concluded.

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Computers are essentially inert without instruction, and it is the role of data scientists to provide them with the guidance they need, the聽Saphila聽2023 conference聽at Sun City聽heard this week.

Saphila聽is聽a biennial conference for the 麻豆原创 user group community, hosted by the African 麻豆原创 User Group (AFSUG) in partnership with 麻豆原创.

鈥淎 computer does nothing without instruction鈥β燱e need聽people聽thinking about what the computer is going to do,鈥澛爏aid Peter Blignaut, manager of pre-sales at 麻豆原创 South Africa during a keynote address.聽鈥淢achines don鈥檛 learn from other machines,聽people聽teach them鈥�.

He says that聽AI, particularly machine learning, which enables computers to learn from data and improve their performance, is fundamentally a product of human teaching rather than machines teaching themselves.

Blignaut believes that聽AI聽has the potential to enhance our efficiency and grant us more time for meaningful tasks. By delegating repetitive and mundane tasks to computers, it will be possible to work more efficiently and devote attention to endeavours that require human ingenuity. However, he argues that the implementation of聽AI聽should not be solely driven by profit motives. Instead, it should aim to make us more effective as individuals, enabling us to become better versions of ourselves.

Involving聽people聽in the development and application of聽AI聽is crucial, and Blignaut stresses the importance of governance and ethics in this domain. The technology requires thoughtful deliberation and a framework for responsible decision-making. However, the practicality of implementing such governance measures in countries like South Africa .

An example of everyday predictive聽AI聽is Netflix and its personalised content algorithms that recommends content to its user based on their previously watched content. These algorithms are far too complex for manual execution, making it necessary for computers to take over this task. This integration of聽AI聽into our daily lives underscores its potential to enhance our experiences and streamline various processes.

Newer generative Ais, such as Chat GPT and Midjourney, hold great promise for the future. By feeding vast amounts of data into these systems, one can generate diverse outputs, ranging from art to essays. However, Blignaut warns of the dangers associated with generative聽AI, particularly the potential for individuals to create fake content. The responsible use of this technology requires careful consideration of where and how it is employed, weighing the benefits against potential risks.

Blignaut says it is crucial to maintain human agency in聽AI, ensuring that decisions made by machines are comprehensible to humans, so that a person understands the decision-making process and can verify its logicality. This understanding fosters trust between the parties involved, further reinforcing the argument for promoting聽AI聽education.

If聽people聽are unfamiliar with new technologies, they tend to avoid them, which is why it is essential to provide explanations about what algorithms are doing.聽聽As聽AI聽continues to evolve, it is important to approach its implementation thoughtfully, harnessing its potential to enhance lives while safeguarding against potential pitfalls.

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This is according to 麻豆原创 executives who spoke on the first day of the biennial African 麻豆原创 User Group (AFSUG) Saphila 2023 conference in Sun City yesterday.

It鈥檚 the first in-person and virtual Saphila event jointly hosted by AFSUG and 麻豆原创 since 2019.

Kholiwe Makhohliso, recently appointed MD of 麻豆原创 Southern Africa, said in the quest to help聽partners聽transform customers鈥� businesses and guide digital transformation journeys, it is important to recognise that a lack of in-house skills represents a challenge 鈥� particularly when it comes to AI.

This is where 麻豆原创 and its partners are looking to exert their influence during a time of industry convergence, where core businesses, such as聽banking聽and telecommunications, are merging through technology.

Sven Denecken, senior VP, chief marketing and solutions officer for industries and CX, 麻豆原创 SE Germany, said industry convergence is real and represents an opportunity as well as an obligation.

鈥淵ou still need to innovate at the vertical edge of the industry,鈥� said Denecken. 鈥淗ow ready are the customers? How ready are the partners to learn?鈥� In South Africa, and on the continent, many companies can leapfrog (but) they must learn from global best practices.鈥�

Denecken believes 麻豆原创 has evolved as a business through the COVID-19 pandemic to enable companies leverage technologies and run better. It also means that businesses are empowered with a realistic view of their technology posture and how this technology can be used.

鈥淚t is important to analyse where the customers are today and pick them up from that point. Don鈥檛 only show the future and the roads it will take to get there. Talk about the current challenges. For example, the degree of standardisation that a business leader allows, because that fuels innovation speed and the adoption of new technology, like AI.鈥�

Denecken said AI tools can analyse billions upon billions of data and do so quickly, but it鈥檚 important for business leaders to understand what they want analysed and they need to be certain about what they would like changed.

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While ChatGPT might be the best-known example of generative AI, there are dozens of large language models (LLMs) now available, says Timo Elliott, global innovation evangelist at 麻豆原创.

鈥淎t 麻豆原创, we want to use the best of these models to further your business processes.鈥�

麻豆原创 AI is built for business, he adds 鈥� it needs to be bult-in, relevant, and responsible.

鈥淵ou need the best data possible,鈥� Elliott says. 鈥淵ou need to know what to solve; and it needs to be used responsibly.鈥�

Indeed, AI has long been a part of 麻豆原创 solutions and millions of people use it already. 鈥淭o a great extent, we want most of this to be taken for granted. The best AI is the AI you don鈥檛 have to think about,鈥� Elliott says. 鈥淵ou want AI to just work.鈥�

For instance, Cash Application does sophisticated pattern matching for Mercedes-Benz, matching transactions automatically. 鈥淎nd it gets better all the time,鈥� Elliott explains. 鈥淓very time there is an exception, it is dealt with by a human and fed back into the algorithm so it knows how to handle it next time.

鈥淲here we are going is self-driving, intelligent applications that get better over time as people use them.鈥�

These capabilities are available already, but the advent of generative AI will add creativity in coding, formal writing, and more.

鈥淲e announced a set of new AI applications recently, many of which include new generative AI models.鈥�

Use cases include expediting freight and documentation; creating compelling job descriptions and interview questions; 聽generating ready-to-use process models and KPI recommendations; and enhancing employee and customer experience.

Generative AI can now code in ABAP (麻豆原创鈥檚 coding language) to create new 麻豆原创 applications. 鈥淭his can accelerate the efforts of your skilled people to create code much quicker,鈥� Elliott says.

Digital transformation requires companies to innovate faster and composable enterprises are key to this.

鈥淭he irony of composable business is that, if its done right, you shouldn鈥檛 have to do too much of it yourself,鈥� Elliott says. 鈥淪o we spend a lot of time working on content so customers can just take a bot off the shelf, plug it into their operations, and do their business processes faster.鈥�

The partner ecosystem is key to this and, ideally, partners will contribute to solutions in the 麻豆原创 store.

Business intelligence is key to modernisation and innovation which is why 麻豆原创 launched its Signavio Business Process Intelligence.

鈥淪ignavio can shine a light into your business processes and figure out what is going on 鈥� and what is going wrong,鈥� Elliott explains. 鈥淚t is then possible to find the best process to solve the issues. This is the future of what we call automated automation.鈥�

But what stops organisations from being successful? 鈥淭he real trick is not using AI 鈥� it鈥檚 about turning their minds to systems and processes,鈥� Elloitt says. 鈥淎nd this is where the AI magic happens.鈥�

Every organisation grapples with the issue of bad data quality. 鈥淭he good news is that, with AI, the opportunities are huge, the possibliities of cleaning up your data are greater then ever before.鈥�

An innovation roadblock has always been how to leverage the business data 鈥� but this tends to lose the metadata, the context of the business.

The idea of data mesh or data sphere is to bring the technology to the data to provide reliable data products using an API approach that understands and retains the business context. 鈥淎s much as possible, leave the data where it already is,鈥� Elliott says.

麻豆原创 Data Sphere is the solution here, he adds. It brings together a range of solutions that creates a data layer that could be stored just about anywhere; whether in 麻豆原创 or third-party repositories.

Value is key, of course, and companies need to get relevant data and information to the fingertips of every staff member.

鈥淭here is a huge opportunity to use data in new ways,鈥� Elliott says. 麻豆原创鈥檚 continuous intelligence prototype aims to push relevant information to people as they need it.

We will see the rise of the business technologist, more powerful users who can create new and profitable processes using the right data and tools. This will see us moving from low-code or no-code scenarios to the new world of co-code where IT and business work together to solve problems or innovate.

IT would supply basic application blocks to the business people who could use those to create their own innovations.

鈥淲e think 麻豆原创 has the biggest benefit here,鈥� Elliott says. 鈥淥ne thing we are good at is processes and governance.鈥�

Elliott believes we are in the 鈥渉orseless carriage鈥� phase of AI 鈥� using old things and just bolting new things on. 鈥淏ut it is a great time to reimagine what we want to do and to rethink value propositions.

鈥淟et鈥檚 spend some time thinking about what we don鈥檛 need, and how to leverage what we do.

鈥淩emember, AI is about empowering people to do more, not getting rid of them.鈥�

Elliott points out that only human beings will ever be able to innovate. 鈥淲e are the only ones that can understand what is going on, who can bring innovation.

鈥淎I will take away the parts of our jobs that make us act like robots 鈥� and let us focus on the things we do best.鈥�

In conclusion, Elliott reiterates that 麻豆原创 and business AI go hand in hand to help organisations to innovate faster and more effectively.

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As enterprises strive for the resilience to counter these challenges and pivot to new opportunities, digital transformation can be a critical weapon in their arsenal.

The way companies think about how they plan for technology has to take these macro-economic factors into account, says Nihmal Marrie, MD and partner at Boston Consulting Group (Johannesburg).

A massive 70% of CEOs have said they need to change 鈥� but only 12% have made plans to do so.

A lot of the global events are a result of the Ukraine war, Marrie says. So far, 12-milion people have been displaced and the cost of reconstruction runs into the trillions of dollars. But the global supply chain has also suffered from the conflict.

But the Ukraine conflict is not an isolated event, Marrie says. Across the globe unpredictable geopolitics is playing out, underlining other potential flashpoints.

鈥淲e have never seen the pace of change like now. So we need to anchor digital decisions on this level of uncertainty.鈥�

In Africa, we will suffer reverberations from the global situation, leading to food insecurity, ongoing conflict, and climate risk. So the continent, and South Africa, need to gear for these changes and prepare for higher inflation.

Dr Martin Kotula, global vice-president: industry and value at 麻豆原创, points out that inflation rates have surged by about 400%.

Some of the root causes have been exploding freight costs and volatile lead times; Covid-caused production and harbour shutdowns; food and grocery price increases; and material shortages and reduced supplies.

There have been further pressures from labour unions pushing for increases, spiralling inflation rates and foreign exchange fluctuations, changing company valuation and more.

Into the future, one potential scenario could see global power plays reverting to collaborative mode. Another scenario could see ongoing conflict with concomitant economic shocks.

We could potentially see the building of a western and eastern bloc, and undecided nations forming a third bloc.

The last scenario could see global escalation, which will lead to further conflict, more supply chain disruption and other economic challenges.

These scenarios are important for resilience planning for companies.

A massive 82% of CEOs expect high interest rate to affect their company鈥檚 performance; 52% pack the capability in comprehensive cost management to transition to a lean organisation; 97% will take action this year to address global challenges.

Technology and digital transformation could be a game-changer, says Marrie.

鈥淲e see an unpredictable outcome, and anything could change day by day,鈥� he says. 鈥淭he good news is that the advances in digital technology allow us to chart a path to make organisations much more resilient.鈥�

Making the right decisions means building a more resilient and secure tech platform; and to build digital and technology as a capability that can increase efficiency and create competitive advantage.

These organisations will be more resilient and more agile and more innovative.

Enterprises can turn ambiguity into opportunity by rapidly deploying and adapting technology and digitalisation to withstand, recover and thrive in altered circumstances.

Of course, cost is a key element of any CEO鈥檚 agenda, Marrie says. 鈥淲e use the term fit for purpose 鈥� tech should be a key enabler of business outcomes, but must be built on a fit for purpose platform.鈥�

Companies are spending significant amounts of money on tech, but there is significant value to be realised.

鈥淗owever, in gaining cost savings, the technology function must also be fit for purpose.鈥�

New technology projects could save 30% to 50% in costs. But only part of these savings can be realised purely by technology 鈥� the rest have to be achieved through business collaboration, with a systematic approach to a business technology model.

Disentangling technology is going to be key to these savings, Marrie says. Regulatory compliance is one driver, followed by risk mitigation, and business and user expectations.

Technology leaders are already looking at various decoupling projects, including social media, applications, data platform, infrastructure, network and vendors. But these all need to be undertaken against the backdrop of regulator compliance, risk mitigation and expectations.

Enterprises have to pay special attention to reducing the digital risk. The potential cost of cyber threats is $2-trillion this year 鈥� which is a big potential loss.

At the same time, 82% of breaches are still caused by organisational and people failure. But, with 3,5-million unfilled cybersecurity roles, tis number is not expected to decrease in the short- to medium-term.

Against the backdrop of these challenges, technology and digitalisation re a key driver to future-proofing the business, says Dr Kotula.

It might be obvious, but companies need to focus on planning and forecasting, optimising forecasting and panning, optimising prices and contribution margins, and ensuring supply chain transparency.

Funding the journey can be done by bringing the cost of operations down 鈥� using technology. Kotula says defining use cases can be useful in doing this.

鈥淲e also have the opportunity free up money t fund large systems, but enterprises also need to protect the core.鈥�

Marrie sys this can be done by disentangling technology and reducing digital risk.

The ideal outcome is to future-proof the business by building a business with growth and resilience.

Technology and digitalisation can help companies to do this.

Analytics can guide companies to fast, informed decisions across all business dimensions. A digital supply chain lets companies identify and analyse the supply chain disruptions, take corrective actions and respond and collaborate in realtime.

Sourcing and procurement lets companies understand spending patterns.

Sales can be optimised with an omni-channel presence with realtime adjustment depending on material availability, lead times and demand changes.

Supply chain finance enables digital capabilities for suppliers in vital cash flow freedom. Working capital can be achieved by leveraging inventory optimisation strategies and hedge risk. Receivables finance gives companies an understanding of when the customer might pay, and how to speed it up.

Human resources systems let employers monitor the employees鈥� pulse of engagement levels, identify problem areas and mitigate them.

Kotula advises that, to combat inflation, companies must have insight-driven analytics to assess the impact of price spirals. They must look to accelerate cost and cash management. The should become more nimble in decisions and pricing. They must build an agile supply and demand chain.

鈥淭he hardest thing is to become a digital and resilient company,鈥� he concludes.

This article first appeared on .

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鈥淚n our vision, every organisation and industry will become a network of intelligent, sustainable enterprises,鈥� says Dr Oliver Gutzeit, vice-president: experience technology 麻豆原创 at 麻豆原创.

鈥淲hen we talk about business transformation, we talk about business agility, supply chain resilience, and sustainability outcomes.鈥�

Transforming the business is the first step in any journey, Dr Gutzeit explains.

This starts with defining the strategic priorities and the business capabilities that support them.

At 麻豆原创 this started with defining the corporate strategy, defining strategic themes, going through a review and decision-making processes, then moving to IT architecture 鈥� and finally delivery of systems that map to the corporate strategies.

Importantly, 麻豆原创 leveraged its capabilities as a steering instrument to establish a clear link between strategy and execution.

鈥淎t the end of the day, IT had to deliver to 麻豆原创 useful systems to deliver on the business strategy.

鈥淭his was a huge game-changer, enabling the business transformation through technology.鈥�

The technology part of the transformation started with translating the business strategy into enterprise architecture, future-proofing this with data management and democratisation of the data.

Scale was vital, and this was achieved with hyperautomation and AI. The end result is to enable a sustainable enterprise that makes sense for employees and customers.

When designing a new enterprise architecture a new business model is vital. At 麻豆原创, the traditional business models were run while the new ones were developed within the house of business architecture that encompasses both runways in tandem, on the same foundation with common configuration and master data.

This tandem operation continues as business processes are migrated, modernised and simplified.

麻豆原创 runs S/4 HANA on a private cloud while running some traditional enterprise systems on-premise.

鈥淭hat is why we dare to tell customers how to make the migration,鈥� says Dr Gutzeit. 鈥淏ecause we are doing it ourselves.鈥濃��

Once the architecture is in place, and there is a runway for enterprise transformation, 麻豆原创 moved to future-proofing the enterprise with data management.

鈥淲e are also affected by trends in the market,鈥� Dr Gutzeit says. These include data quality, multi-domain master data, data literacy, data automation, data marketplaces, and a requirement for a chief data officer.

麻豆原创 focuses on five strategic priorities: configurable material, one customer view, data governance, third-party centre of excellence, and cloud product master data.

麻豆原创 has defined data as a business capability within the company which is a strategic way of looking at data, Dr Gutzeit explains.

The end goal for data transformation is to democratise data which will increase productivity, accessibility, and agility.

麻豆原创鈥檚 data democratisation framework is based on the data foundation layer, enriched with the semantic layer, and the consumption layer which gives users insights, based on the user persona. These personas could be consumers, data analysers, report creator, data modeler or data scientist among others.

Hyperautomation and AI are vital for scaling the digital enterprise.

麻豆原创 focused on the priorities identified to execute its AI strategy, defined in accordance with the company AI global AI ethics policy.

The priorities were to scale high-quality AI and deliver big data use cases; and to prioritise best-in-class big data and AI platform. The company aims to become a global AI development partner and AI thought leader and focuses on people, agility and organisational development

The company needed to realise value, and it did this by highlighting use cases and successful deployments.

A good example of how 麻豆原创 embraced the digital enterprise was enhancing more than 50 live AI and ML use cases with new technology trends. The result was 105 new business processes that, developed by business users, increase innovation and outcomes.

鈥淓mployees can use these processes every day to increase their innovation and productivity,鈥� Dr Gutzeit says.

Sustainability is at the centre of 麻豆原创鈥檚 policies, and the digitalisation of processes has helped the company to be more sustainable, to improve people鈥檚 lives.

鈥淲e have such a multiplication impact at 麻豆原创 by doing things right,鈥� Dr Gutzeit says.

At the end of the day, the mandate of the transformation journey is to create a digital experience for employees and customers.

The ONE customer portal transforms the digital experience, offering a single point of entry and delivering intelligent and personalised services.

No big change in any enterprise can be accomplished without keeping the people front and centre of the project.

麻豆原创 realised it had to catalyse transformation through a culture of change. This involved cultivating an innovation mindset, changing thinking patterns, and leading by example; investing in skills development and enabling career growth; and creating a culture of life-long learning, Dr Gutzeit explains.

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鈥淭he end of the project is not the end of the story,鈥� says Wassilios Lolas, global vice-president and head of the Signavio Centre of Excellence at 麻豆原创. 鈥淚t is the beginning.鈥�

麻豆原创 has been in this business for a long time and customers all tell them the same things: it is hard to get the business excited about IT transformation and that transformation is often IT-driven not business-driven.

鈥淲e see that customers face two major internal challenges: the one is the C-level perspective; and the other is the businesses and IT realities.鈥�

One the one side, the CEO wants to move quickly, be more agile, able to respond to changing businesses or crises.

On the other side, the reality is the complexity of systems and huge variety of processes.

In most cases, business and IT have grown in complexity together and often lose control of where they are.

Almost all companies find themselves in the position of facing enormous complexity, so they don鈥檛 know where or how to start their transformation.

Once a project has started it takes months to prepare, to implement, and to go live 鈥� it is too time-consuming.

And once the solutions are up and running, customers often find they have not created enough business value.

鈥淚t is this complexity on one side, and the disconnect between business and IT on the other, leading to the decision to move the old ECC systems, as is, without trying to implement changes,鈥� 聽says Lolas.

To make it more complicated, decision-makers want facts to make data-driven decisions.

鈥淏ut it is very hard to fix past mistakes if you don鈥檛 know where they are, or how they run today.鈥�

Typically, these problems are solved by external consultants. It takes a lot of time and money 鈥� and, at the end, only a part of the picture is uncovered.

The end result is that no-one really trusts the answers and business models that don鈥檛 necessarily reflect the reality are produced.

麻豆原创 has launched Signavio, what it calls a plug-and-gain approach to running a RISE initiative and transforming processes fast and with confidence.

Lolas points out that a transformation project usually includes preparation, deployment, and run phases.

In the preparation phase, it is literally as simple as connecting the 麻豆原创 system to Signavio. This gives the fastest time to direct insight, offering C-level driver summaries, over 1聽000 process performance indicators, almost 100 process flows, most frequent blockers, industry-level benchmarks, and more than 1聽000 recommendations.

This preparation step can be done in literally a couple of hours, Lolas says. Teams can quickly decide which processes need to be fixed or changed using trusted data.

In deciding how to proceed with business process transformation, Signavio offers the fastest time to deeper intelligence through process variant analysis, process execution investigations, pre-defined dashboards, detailed mining analysis, and best scores across key process areas.

Signavio now includes a best run score comparing the way a process is executed with the best way it could be run. 鈥淭his comparison gives you an understanding about the best possible performance versus how a business unit is actually performing,鈥� Lolas explains.

The final piece of the preparation picture is the faster time to business process design. It does this via reverse engineering of process models, identifying the company鈥檚 best-run execution, defining the to-be processes, and simulating the final process. Signavio offers a library of more than 7聽000 best-practice processes that can be plugged in if relevant.

These preparation capabilities are on a platform of process reference content, and collaboration and governance.

The second phase, deployment, is about bringing together the worlds of business and IT.

Signavio helps enterprises to deploy faster, offering a collaboration hub that facilitates collaboration and governance between business and IT. The Solution Manager/cloud application lifecycle manager makes application lifecycle management easier. Meanwhile, the Central Business Configuration helps to ensure applications are properly configured.

Signavio offers fast insights when running the processes, enabling continual innovation.

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The聽metaverse聽may not seem viable in South Africa and other countries facing similar socio-economic challenges, but a global expert believes that the cost of聽virtual reality (VR) headsets and controllers are not an issue.

鈥淭he聽metaverse聽is helping in democratising and creating equal chances and access by design,鈥� said聽Dr Oliver Gutzeit, global vice president of 麻豆原创鈥檚 experience technology team, in an interview during last week鈥檚聽Saphila聽2023 conference at Sun City.聽Saphila聽is聽a biennial conference hosted by the African 麻豆原创 User Group (AFSUG) in partnership with 麻豆原创.聽Gutzeit delivered a presentation聽titled聽麻豆原创 in the聽Metaverse聽鈥� Innovation in Action.聽We spoke to him later about its potential in South Africa.

鈥淚f it is done in the right way, it is really not a place that is聽depending聽on money to work in, or access,鈥� he said. 鈥淚t is helping to open opportunities. If inequality is high, the聽metaverse聽is a technology that can help, and is worth looking聽into. 鈥淗olograms and VR have long been a feature of the supposed fourth industrial revolution. When President Cyril Ramaphosa opened the first 4th Industrial Revolution SA summit in 2019, his address was live-streamed as a hologram to the Rustenburg Civic Centre. It was touted as the first live holographic presentation by a head of state, although India, China and France could have laid claim to the same laurels.

It鈥檚 just over four years later, and we have yet to see heads of state ditching their microphones for holograms. That鈥檚 the problem with most 4IR tech, from VR to 3D printing: it鈥檚 all very cool, but not often of practical use.

However, Gutzeit鈥檚 presentation suggested that VR and AR, or the聽metaverse, as such tech has been marketed since Facebook changed its name to Meta, is moving closer to true industrial application.

Introducing the topic, he exploded a few myths about the聽metaverse, including the misconceptions that it is all about Mark Zuckerberg鈥檚 Meta, that it is losing money, and that it is a 鈥渨alled garden鈥� that limits access.

More significantly, he underlined the commercial opportunity it offered in the industrial and manufacturing spaces. He shared projections by Deloitte that showed that the industrial聽metaverse, a virtual mirror of real-life industrial processes, was especially promising. It was expected to generate $22,73-billion in revenue by 2025, an $100-billion annual potential by 2030.

Deloitte鈥檚 research found that 85% of enterprises think that preparation for the聽Metaverse聽is necessary today, while 20% of manufacturers are developing聽metaverse聽applications or underlying solutions. Only 6% of enterprises see the聽metaverse聽as just a hype.

That was just a warm-up for Gutzeit鈥檚 own demonstration of the聽metaverse. He introduced his own avatar, a user鈥檚 digital representation of themselves in an online or virtual environment, and took the audience through a series of virtual rooms that make up a 麻豆原创聽Metaverse聽showcase.

From a leisure lounge to a 麻豆原创 history museum to a virtual workbench to a convenience store that was quickly converted聽into聽a clothes shop, he encapsulated a range of settings possible in the聽metaverse. He demonstrated how he could customise a company car with different models and colours before the specs could be sent off for delivery of the real thing.

With a controller in his hands, he navigated through a videogame-like environment to demonstrate a real-life application of the聽metaverse聽in an industrial setting, rearranging items to simulate how it would affect a real environment. Is that enough to convince operators of factories and other industrial operations?

The fact that the聽metaverse聽has not yet taken off in this sector could turn out to be a good thing, said Gutzeit.

鈥淲e have more time to explore the聽metaverse, and we need to find out in which cases it will be an effective technology,鈥� he told us later. 鈥淚n the next few years, we will have a breakthrough for this technology. It won鈥檛 have the same disruptive effect as AI, but it will be an added piece of technology in our future.

鈥淥verall, the聽metaverse聽is nothing to be in fear of. There will not be a sudden disruption, but rather a change over time. Talking about it, and being in the聽Metaverse, are two totally different things. You don鈥檛 have to like it, or stay there, or use it, but at least try it once 鈥� even if you think it has nothing to do with you or your business.鈥�

* Arthur Goldstuck is founder of World Wide Worx and editor-in-chief of聽. Follow him on Twitter and Threads on @art2gee Jason Bannier is a data analyst at World Wide Worx and writer for聽. Follow him on Threads and Instagram at聽@jase_bann

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Intelligent automation can help to address challenges in 麻豆原创 custom codes, says Arndt Hoffman, chief customer officer at smartShift, and BMW has achieved some major inroads.

The 麻豆原创 modernisation story to 麻豆原创 S/4 HANA is pretty simple on the surface, he says. The end result should be a new 麻豆原创 system with custom code neatly decoupled from the system.

The reality is not so simple, though 鈥� and one of the biggest issues is legacy custom code. In BMW鈥檚 case, this goes back to 1989.

Indeed, the average 麻豆原创 systems has about 22聽000 customer objects, 2,7-million lines of code, and up to 2聽000 transports per month. Making it worse, about 40% to 60% of custom applications are not used.

All of this leads to an average of 9聽000 HANA issues, 17聽000 S/4 HANA issues, and thousands of person days of technical debt.

鈥淪o why not just throw all the custom code away?鈥� Hoffman asks. 鈥淏ecause there are good reasons to have custom code 鈥� so 72% of customers want to keep their customisations.鈥�

The traditional approach to this is manual remediation which is labour intensive, time-consuming, and risky. 鈥淎nd it only scratches the surface, not looking at how you can optimise the code for the future.鈥�

The manual approach is not satisfactory to customers, with most of them giving it a poor score.

smartShift developed its Intelligent Automation Platform to improve this process. Since first developing it 15 years ago, it has enhanced it considerably to cater for new challenges as they arise.

The system takes custom code in the existing 麻豆原创 environment, analyses it and then transforms it for the target 麻豆原创 environment 鈥� usually 麻豆原创 S/4 HANA. It can then do a clean core analysis and clean core realisation. The result is a modern 麻豆原创 system that allows for future innovation in a flexible, scalable, and agile environment.

BMW South Africa has over 16聽000 applications, with plenty of custom code. 鈥淲e wanted to use custom code in an efficient way, but we couldn鈥檛 afford to have our developers sitting there and changing it,鈥� says Hanlie van der Berg, 麻豆原创 architect at BMW鈥檚 Rosslyn plant.

The company decided to take a custom code transformation approach customised for each project, using the smartShift Intelligent Automation Platform.

鈥淲e had to have guaranteed KPIs,鈥� Van der Berg adds.

BMW identified 69 麻豆原创 system landscapes in the scope of a multi-year transformation roadmap.

The intent of the project was to improve systems stability and resilience, and allow true speed and agility in transformation.

The project started in September 2018 and so far 116 projects in 45 麻豆原创 landscapes have been successfully completed.

A massive 60聽151 custom objects and 9,7-million lines of code have been decommissioned.

This has resulted in massively reduced yearly maintenance costs, addressed 950聽000 issues, and saved 60聽000 days of manual labour. 鈥淲e feel our developers should be working on new systems, not wasting their time modernising old custom code.鈥�

Van der Berg adds that the IT risk has been reduced as well, and agility improved to a two week lead time today.

Manufacturing plant system

The BMW ZAP system at Rosslyn is the local manufacturing plant system that is fully integrated with logistics, finance, retail and sales. It was established in 1995 on release 麻豆原创 ECC6 Eh97. It is an extra large system with more than 50聽000 objects and more than 22聽000 interfaces.

鈥淚t is an old system and a massive system, but it runs well. And, like all systems, it has to be transformed to the new systems.鈥�

Among the challenges relating to custom code are those relating to upgrades, security, maintenance, performance, documentation, and support.

Using intelligent automation, BMW was able to define how the custom code should change, and the platform takes over from there.

In 2019, the initial analysis was undertaken and a repository cleanup initiated to eliminate unused custom code. 鈥淭hen we were left with the code that we actually use.. We wanted to modernise this, and also build in more security.鈥�

The code security remediation began in 2020 and was completed in 2022.

BMW and smartShift then did an interface analysis, which 聽is still ongoing.

The next step will be the S/4 HANA clean-core analysis to let BMW know what code needs to be replaced and what needs to be done to clean up the core.

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The consulting firm says the practice brings together industry experience, skilled AI engineers as well as ecosystem and alliance聽partners聽to help customers build generative AI solutions to accelerate business innovation.

The use of AI to make business processes more efficient in realtime is a central theme at Saphila 2023.

According to Deloitte Africa, generative AI is already revolutionising industries with its capability to analyse unstructured and structured data and model it in a way that makes human sense. This results in simplifying the engagement between humans and digital systems, enhancing productivity and innovation at an accelerated pace.

Quentin Williams, Deloitte Africa.

Quentin Williams, director and AI leader for Deloitte Africa, said, 鈥淭here鈥檚 been extensive discussion across industries around the capabilities of generative AI technology and its potential to revolutionise the way we work, how it allows for digital systems to understand us as humans, without effort; and for us humans to create digital systems and solutions quickly and at scale. We will be going much further than exploring what鈥檚 possible 鈥� we enter the market with the aim of creating what鈥檚 next.鈥�

Jania Okwechime, partner, data analytics and AI peader for Deloitte West Africa, added, 鈥淭hrough this practice, our clients now have access to AI labs, accelerated use-case development and Large Language Model managed services – all within our trustworthy AI framework. […] We aim to, and will; increase AI fluency within the market, grow AI talent on the continent and together with our alliance partners, take enterprise scale generative AI solutions to our clients.鈥�

The practice aims to help clients create innovative AI-fuelled applications聽to bring about business process efficiency gains and productivity improvements.

Deloitte identifies power supply and healthcare as emerging use cases for generative AI.

The technology can optimise electricity delivery, including maintenance scheduling, by simulating distribution choices and generating cost-effective strategies.

In healthcare, AI can streamline diagnostics and treatment by providing physicians with real-time, data-driven insights.

Deloitte noted that while generative AI can increase efficiency, there are risks to consider.聽The technology may not incorporate ethics in decision-making, potentially causing reputational harm. Additionally, unidentified flaws or inadequate data could result in financial losses

Wessel Oosthuizen, associate director for digital risk solutions and Africa AI Institute leader at Deloitte Africa, said, 鈥淲e can help organisations build the right infrastructure, collect, and manage the right data, train the right models to create generative AI solutions that are effective and scalable and validate prebuilt models to ensure alignment to your firm鈥檚 ethics and values.鈥�

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