How AI-powered recruiting helps Spain’s leading soccer team score

Phrases like “striking the post” and “direct free kick outside the 18” may seem foreign if you’re not a fan of football (for Americans, see: soccer). But for a football scout, it’s the daily lexicon of the job, representing crucial language that helps assess a player’s value to a team. And now, it’s also the language spoken and understood by Scout Advisor—an innovative tool using natural language processing (NLP) and built on the IBM® watsonx™ platform especially for Spain’s Sevilla Fútbol Club. 

On any given day, a scout has several responsibilities: observing practices, talking to families of young players, taking notes on games and recording lots of follow-up paperwork. In fact, paperwork is a much more significant part of the job than one might imagine. 

As Victor Orta, Sevilla FC Sporting Director, explained at his conference during the World Football Summit in 2023: “We are never going to sign a player with data alone, but we will never do it without resorting to data either. In the end, the good player will always have good data, but then there is always the human eye, which is the one that must evaluate everything and decide.” 

Read on to learn more about IBM and Sevilla FC’s high-scoring partnership. 

Benched by paperwork 

Back in 2021, an avalanche of paperwork plagued Sevilla FC, a top-flight team based in Andalusia, Spain. With an elite scouting team featuring 20-to-25 scouts, a single player can accumulate up to 40 scout reports, requiring 200-to-300 hours of review. Overall, Sevilla FC was tasked with organizing more than 200,000 total reports on potential players—an immensely time-consuming job. 

Combining expert observation alongside the value of data remained key for the club. Scout reports look at the quantitative data of game-time minutiae, like scoring attempts, accurate pass percentages, assists, as well as qualitative data like a player’s attitude and alignment with team philosophy. At the time, Sevilla FC could efficiently access and use quantitative player data in a matter of seconds, but the process of extracting qualitative information from the database was much slower in comparison.  

In the case of Sevilla FC, using big data to recruit players had the potential to change the core business. Instead of scouts choosing players based on intuition and bias alone, they could also use statistics, and confidently make better business decisions on multi-million-dollar investments (that is, players). Not to mention, when, where and how to use said players. But harnessing that data was no easy task. 

Getting the IBM assist

Sevilla FC takes data almost as seriously as scoring goals. In 2021, the club created a dedicated data department specifically to help management make better business decisions. It has now grown to be the largest data department in European football, developing its own AI tool to help track player movements through news coverage, as well as internal ticketing solutions.  

But when it came to the massive amount of data collected by scouters, the department knew it had a challenge that would take a reliable partner. Initially, the department consulted with data scientists at the University of Sevilla to develop models to organize all their data. But soon, the club realized it would need more advanced technology. A cold call from an IBM representative was fortuitous. 

“I was contacted by [IBM Client Engineering Manager] Arturo Guerrero to know more about us and our data projects,” says Elias Zamora, Sevilla FC chief data officer. “We quickly understood there were ways to cooperate. Sevilla FC has one of the biggest scouting databases in the professional football, ready to be used in the framework of generative AI technologies. IBM had just released watsonx, its commercial generative AI and scientific data platform based on cloud. Therefore, a partnership to extract the most value from our scouting reports using AI was the right initiative.”  

Coordinating the play 

Sevilla FC connected with the IBM Client Engineering team to talk through its challenges and a plan was devised.  

Because Sevilla FC was able to clearly explain its challenges and goals—and IBM asked the right questions—the technology soon followed. The partnership determined that IBM watsonx.ai™ would be the best solution to quickly and easily sift through a massive player database using foundation models and generative AI to process prompts in natural language. Using semantic language for search provided richer results: for instance, a search for “talented winger” translated to “a talented winger is capable of taking on defenders with dribbling to create space and penetrate the opposition’s defense.”  

The solution—titled Scout Advisor—presents a curated list of players matching search criteria in a well-designed, user-friendly interface. Its technology helps unlock the entire potential of the Sevilla FC’s database, from the intangible impressions of a scout to specific data assets. 

Sevilla FC Scout Advisor UI 

Scoring the goal 

Scout Advisor’s pilot program went into production in January 2024, and is currently training with 200,000 existing reports. The club’s plan is to use the tool during the summer 2024 recruiting season and see results in September. So far, the reviews have been positive.   

 

“Scout Advisor has the capability to revolutionize the way we approach player recruitment,” Zamora says. “It permits the identification of players based on the opinion of football experts embedded in the scouting reports and expressed in natural language. That is, we use the technology to fully extract the value and knowledge of our scouting department.”  

And with the time saved, scouts can now concentrate on human tasks: connecting with recruits, watching games and making decisions backed by data. 

When considering the high functionality of Scout Advisor’s NLP technology, it’s natural to think about how the same technology can be applied to other sports recruiting and other functions. But one thing is certain: making better decisions about who, when and why to play a footballer has transformed the way Sevilla FC recruits.  

Says Zamora: “This is the most revolutionary technology I have seen in football.” 

Source: ibm.com

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Product lifecycle management for data-driven organizations

In a world where every company is now a technology company, all enterprises must become well-versed in managing their digital products to remain competitive. In other words, they need a robust digital product lifecycle management (PLM) strategy. PLM delivers value by standardizing product-related processes, from ideation to product development to go-to-market to enhancements and maintenance. This ensures a modern customer experience. The key foundation of a strong PLM strategy is healthy and orderly product data, but data management is where enterprises struggle the most. To take advantage of new technologies such as AI for product innovation, it is crucial that enterprises have well-organized and managed data assets.

Gartner has estimated that 80% of organizations fail to scale digital businesses because of outdated governance processes. Data is an asset, but to provide value, it must be organized, standardized and governed. Enterprises must invest in data governance upfront, as it is challenging, time-consuming and computationally expensive to remedy vast amounts of unorganized and disparate data assets. In addition to providing data security, governance programs must focus on organizing data, identifying non-compliance and preventing data leaks or losses.  

In product-centric organizations, a lack of governance can lead to exacerbated downstream effects in two key scenarios:  

1. Acquisitions and mergers

Consider this fictional example: A company that sells three-wheeled cars has created a robust data model where it is easy to get to any piece of data and the format is understood across the business. This company is so successful that it acquired another company that also makes three-wheeled cars. The new company’s data model is completely different from the original company. Companies commonly ignore this issue and allow the two models to operate separately. Eventually, the enterprise will have weaved a web of misaligned data requiring manual remediation. 

2. Siloed business units

Now, imagine a company where the order management team owns order data and the sales team owns sales data. In addition, there is a downstream team that owns product transactional data. When each business unit or product team manages their own data, product data can overlap with the other unit’s data causing several issues, such as duplication, manual remediation, inconsistent pricing, unnecessary data storage and an inability to use data insights. It becomes increasingly difficult to get information in a timely fashion and inaccuracies are bound to occur. Siloed business units hamper the leadership’s ability to make data-driven decisions. In a well-run enterprise, each team would connect their data across systems to enable unified product management and data-informed business strategy.  

How to thrive in today’s digital landscape

In order to thrive in today’s data-driven landscape, organizations must proactively implement PLM processes, embrace a unified data approach and fortify their data governance structures. These strategic initiatives not only mitigate risks but also serve as catalysts for unleashing the full potential of AI technologies. By prioritizing these solutions, organizations can equip themselves to harness data as the fuel for innovation and competitive advantage. In essence, PLM processes, a unified data approach and robust data governance emerge as the cornerstone of a forward-thinking strategy, empowering organizations to navigate the complexities of the AI-driven world with confidence and success.

Source: ibm.com

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ManagePlus—your journey before, with and beyond RISE with SAP

RISE with SAP has not only been a major cloud player in recent years, it’s also become the standard cloud offering from SAP across different products.  

But when assessing what it takes to onboard into RISE with SAP, there are multiple points to consider. Especially important is a good understanding of the RACI split around Standard, Additional and Optional Services, along with relevant CAS (Cloud Application Service) packages. 

If you’re wondering whether RISE with SAP is the right solution for you, consider the following scenarios: 

Data centre move 

You’re looking to move from Capex to Opex in IT spend or have an end-of-data centre contract which can end up triggering evaluation for alternate hosting options —this time, a hyperscaler-based journey (Azure, AWS, GCP, IBM Cloud® and so forth). Also consider the cost of hardware refresh and for possible opportunities around on demand cloud computing. 

S/4HANA contract conversion 

You’re in your journey towards adoption of S/4HANA either with Greenfield, Brownfield or Bluefield by planning a potential contract renegotiation and restructuring with SAP, then RISE with SAP is the only contract presented by SAP (majority of the time) to customers offering S/4HANA capabilities and a move to cloud computing. 

Enabling true transformation 

You’re on the lookout for adoption of industry best practices along with the capabilities of process mining and process discovery to both simplify and standardize the process flows. From a business and IT perspective, this helps in cycle time and eventually price per business object.  

M&A and divestiture 

You have a potential ask of simplifying the divestiture of Company Codes and with that, the split of IT systems with ease of license segregation. 

System consolidation 

You want to reduce the solution footprint and by doing so, reduce infrastructure cost and help shift toward a single source of truth across different components. 

License audit gap/shelfware 

You’re looking for a long-term solution that’s not only subscription-based, but can also address potential compliance gaps. 

IT project issues 

You’d like to worry less about physical provisioning of capacity within your data centre and rely more on faster onboarding of new resources in terms of on-demand capacity. 

End to end security 

You’re required to maintain gold standard of security both from a platform and application point of view, cutting across different security requirements. 

IT Ops issues 

You don’t want to deal with the challenges in managing multiple vendors and SLAs. 

Industry focus 

To complement your current IT setup and add operating flexibility, you’re also looking to address the rapid demand for cloud ERP in industries such as healthcare, retail, education and telecom. In addition, you want an automated resource management and industry specific functions such as sales and customer support at the core of operations. The image below shows what’s included within RISE at a high level. 

To top it off, SAP recently announced “Grow with SAP,” an offering that includes products, best practice support, adoption acceleration services, community and learning opportunities to help use SAP S/4HANA public cloud edition with speed, predictability and continuous innovation. 

What else should you know about RISE with SAP? 

RISE with SAP comes with different activities, included as part of the standard/ tailored RACI published by SAP. These activities are categorized as: 

• Standard: Default activities that maintain systems without additional charge such as DB, network, platform and system maintenance. More details about roles and responsibilities.  
• Additional: One-time activities—such as additional DR testing—required to be performed by SAP beyond what’s standard
• Optional: Both one-time and recurring impacts on the solution, such as adding additional memory or upgrading on size and scale. 
• Cloud Application Services (CAS) packages: Activities which a client might be able to handle within their IT team internally, or with the vendor who might already have been a part of their IT landscape. These activities may include supporting the client’s transport management, release version upgrades and test management needs. 

Based on the requirements, it’s not only additional CAS packages to consider—it’s also the SAP and non-SAP systems you don’t want to include into the RISE landscape. This could be due to multiple reasons, primarily, certain combinations of hardware and DB might not be supported in RISE.  

To address this, consider ManagePlus, which maintains similar standards to RISE without some of the incentives which may not be required. A few other compelling reasons in favor of ManagePlus: 

 

 You have not yet decided if RISE with SAP is appropriate for your business 

• You have multiple add-ons which might not be allowed into RISE with SAP 
• You want a single vendor to take responsibility for both RISE-based workloads and non-RISE-based workloads 
• You would like to still transition into cloud services before making a jump into S/4HANA, but want to make sure you don’t end up paying twice—once for the current move through ManagePlus, and at a later point, into RISE with SAP 
• You’re looking for the same landing zone with pre-defined architectural patterns being leveraged for a true hybrid cloud deployment 

As announced earlier, IBM® is at the frontier, deploying RISE with SAP as a premium supplier successfully delivering RISE with SAP both from a cloud provisioning and from a technical managed services point of view. As part of the breakthrough partnership with IBM for RISE with SAP, global clients have been successfully provided with advisory, support and implementation services including the CAS package related services.

To add onto these great solutions and services, clients have also been given a comprehensive end-to-end solution under “ManagePlus,” which can address all of the above pain points around your aspiration to be RISE-ready, while still deciding when to move to RISE with SAP.  ManagePlus also covers SAP and non-SAP workloads, which are not on RISE, but can maintain similar standards. Last but not least, the scenario around CAS package-based scope to support your RISE with SAP based scope. 

We leverage our master control plane driven approach guided by AI and automation to support your requirements both for the build and manage on SAP and non-SAP workloads. This enables you to have a seamless transition across the systems with a single vendor-based experience and with improvement in Mean time to Diagnose (MTTD) and Mean Time to Resolve (MTTR). The control plane also allows you to easily extend across multiple hyperscalers using the same architectural patterns established earlier. This provides the ease of maintenance and repeatability of effort, without looking into different integration points between each solution. 

This solution brings the best capabilities to the forefront when it comes to industry best practices, industry solutions, technical core operations, migration/implementation of the functionality, functional/technical application management services and adoption of AI. To help you achieve no-touch and low-touch operations model. We leverage our SAP-certified Digital Operations framework at the core of the solution to generate insights and reduce the noise when it comes to the most complex landscape management-based functionality. 

The following are the benefits of using this solution either with RISE with SAP or beyond RISE with SAP: 

• Provides a consistent platform of less than 3 days for system provisioning end-to-end 
• Provides a single platform for not only RISE with SAP-based workloads, but for all systems both SAP and non-SAP with same standards as RISE with SAP 
• Well-defined CAS package-related services around system monitoring, job scheduling/monitoring, print setup and monitoring, transport management, ChaRM maintenance and custom add-on management (along with other issues around usage of DBs, such as Oracle, DB2 with AIX and other operating systems)
• 50–60% improvement in MTTD and MTTR leveraging AI

Source: ibm.com

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The blueprint for a modern data center

Part one of this series examined the dynamic forces behind data center retransformation. Now, we’ll look at designing the modern data center, exploring the role of advanced technologies, such as AI and containerization, in the quest for resiliency and sustainability. 

Strategize and plan for differentiation 

As a leader, you need to know where you want to take the business—understanding the trajectory of your organization is nonnegotiable. However, your perspective must be grounded in reality; meaning, you must understand the limitations of your current environment: 

• Where does it currently fall short? 
• Where have you already identified room for improvement? 
• Where can you make meaningful changes? 

The answers to these questions can help guide your transformation plan with achievable goals. Changes will likely come through outdated, disjointed technology systems and inefficient, costly processes. 

It’s also important to clearly define the role of new advanced technologies in your new environment. AI and containerization are not just buzzwords. They are powerful tools and methods that can help you drive efficiency, agility and resiliency throughout the data center and into everything the business does through digital means. 

• AI offers insights and the ability to automate capabilities intelligently. 
• More than half of surveyed organizations seek to increase value and revenue through the adoption of generative AI.
• Containerization gives you greater flexibility and growth potential in deploying applications in any hybrid cloud environment that you can envision (and need). 
• Gartner predicts that 15% of on-premises production workloads will run in containers by 2026.

Don’t just keep pace with these advancements in technology. Use them and build advanced data-driven processes around them to enable your entire organization to create a distinct, competitive edge. 

When you have your objectives and mission clearly defined, you can develop a strategic plan that incorporates advanced technologies, processes—and even partner services—to achieve the outcomes you’ve outlined. This plan should not just solely address the immediate needs but should also be flexible and adaptable to overcome future challenges and use future opportunities. It should also include resiliency and sustainability as core tenants to make sure you can keep growing and transforming for years to come. 

Use data and automated precision to produce results

What is automated precision? When you can integrate data, tools and processes to manage and optimize various aspects of a data center, automated precision becomes about harnessing technology to run operations with: 

• High accuracy 
• Minimal intervention 
• Consistent performance 
• Predictable outcomes 

The global data center automation market was valued at $7.6 billion in 2022. It is expected to reach $20.9 billion by 2030.

Automation will play a pivotal role in transforming the data center, where scale and complexity will outpace the ability of humans to keep everything running smoothly. For you as a business leader, this means pivoting from manual methods to a more streamlined, technology-driven and data-enabled approach. 

AI is a critical component in this advancement toward automated precision. Able to analyze large data sets, predict trends and make informed decisions, AI’s role will be to transform mere automation into intelligent operation. 34% of surveyed organizations plan to invest the most in AI and machine learning (ML) over the year. 

When you apply AI-enabled automated precision to your data center, you can: 

• Handle repetitive, time-consuming tasks with unmatched speed and accuracy 
• Free up human resources for more strategic initiatives that can’t be automated 
• Identify anomalies swiftly and predict failures before they occur 
• Intelligently distribute resources based on real-time demand 
• Detect and mitigate threats more effectively compared to traditional methods 
• Optimize power usage and reduce waste in alignment with your sustainability goals 

Chart a course for resilience and sustainability 

The evolution of the data center helps position your organization at the forefront of technological advancement and at the heart of sustainable business practices. Adopting a modern data center that embraces AI, edge computing and containerization can help ensure that your organization will emerge as a dynamic, efficient and environmentally conscious business. 

IBM® and VMware can help you design the data center of the future—one that uses automation, hyperconvergence and cloud technologies to support high performance, reliability and sustainability. With offerings for security, compliance, analytics and containerization, IBM and VMware can ensure that your modern data center meets your business goals

Source: ibm.com

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The dynamic forces behind data center re-transformation

Data centers are undergoing significant evolution. Initially, they were massive, centralized facilities that were complex, costly and difficult to replicate or restore. Now, advancements in hardware and software as well as increased focus on sustainability are driving rapid transformation.

Catalysts and conundrums

A dramatic shift in development and operations is making data centers more agile and cost-effective. These changes are driven by the following:

• market changes and customer requirements prompting organizations to decentralize and diversify their data storage and processing functions; 
• policy and regulatory requirements such as data sovereignty, affecting data center operations and locations; 
• the push to reduce complexity, risk and cost with the widespread adoption of cloud and hybrid infrastructure; 
• the pressure for improved sustainability with greener, more energy-efficient practices; and 
• AI adoption, both to improve operations and increase performance requirements. 

IDC predicts a surge in AI-enabled automation, reducing the need for human operations intervention by 70% by 2027​​. 

However, AI is also a disruptor, necessitating advanced infrastructure to meet data-intensive computational demands. This isn’t to suggest that disruption is a negative attribute. It’s quite the opposite. If embraced, disruption can push the organization to new heights and lead to tremendous outcomes. 

Embrace change and innovation 

The data center of the future is ripe for further growth and transformation. As-a-service models are expected to become more prevalent, with IDC forecasting that 65% of tech buyers will prioritize these models by 2026​​. This shift echoes the response to economic pressures and the need to fill talent gaps in IT operations. 

The growing importance of edge computing, driven by the need for faster data processing and reduced latency, also reshapes data center architecture. Gartner predicts data center teams will adopt cloud principles even for on-premises infrastructure to help optimize performance, management and cost. 

Sustainability will remain a key focus, with Gartner noting that 87% of business leaders plan to invest more in sustainability in the coming years​. This commitment is critical in reducing the environmental impact data centers will have, aligning their transformation with broader global efforts to combat climate change. This will allow organizations to demonstrate their commitment to ESG efforts as consumers look to differentiate between those that take real action and those that are simply greenwashing for marketing purposes. 

Envision the data center of tomorrow

Data centers will continue transitioning from the monolithic configurations from yesteryear to become agile, high-powered, AI-driven, sustainable ecosystems distributed globally. They will mirror the broader evolution of technology, business and society, sometimes even leading the charge to a new frontier. The data center of the future will be at the center of innovation, efficiency and environmental responsibility, playing a critical role in shaping a sustainable digital world.

Source: ibm.com

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