A clear path to value: Overcome challenges on your FinOps journey

In recent years, cloud adoption services have accelerated, with companies increasingly moving from traditional on-premises hosting to public cloud solutions. However, the rise of hybrid and multi-cloud patterns has led to challenges in optimizing value and controlling cloud expenditure, resulting in a shift from capital to operational expenses.

According to a Gartner report, cloud operational expenses are expected to surpass traditional IT spending, reflecting the ongoing transformation in expenditure patterns by 2025. FinOps is an evolving cloud financial management discipline and cultural practice that aims to maximize business value in hybrid and multi-cloud environments. But without a thorough understanding, adopting FinOps can be challenging. To maximize benefits and realize the potential of FinOps, organizations must forge a clear path and avoid common mistakes.

Enhanced capabilities to drive growth 

FinOps is closely intertwined with DevOps and can represent a radical transformation for many organizations. It necessitates a revised approach to cost and value management, challenging organizations to move beyond their comfort zones and embrace continuous innovation. To achieve this, development teams, product owners, finance, and commercial departments must come together to rethink and reimagine how they collaborate and operate. This collective effort is essential for fostering a culture of innovation and driving meaningful change throughout the organization. 

FinOps enables your organization to control costs and enhance consistency by managing average compute costs per hour, reducing licensing fees, decreasing total ownership costs, and tracking idle instances. It also drives improved outcomes and performance through enhanced visibility and planning, which includes comparing actual spending against forecasts, ensuring that architecture aligns with business and technological objectives, and increasing automation.

These improvements lead to faster decision-making, quicker demand forecasting, and more efficient “go” or “no-go” decision processes for business cases. Also, FinOps helps align business and IT goals, fostering an environment where enterprise goals are interconnected, and business cases are developed with clear, quantifiable benefits. This alignment ensures that both existing and new capabilities are enhanced, supporting strategic growth and innovation. 

Challenges and common mistakes when adopting FinOps

Organizations should develop a phased approach over time instead of attempting to implement everything from day one. Having the right people, processes, and technology in place is essential for validating changes and understanding their impact on the consumption model and usability. 

It’s crucial to lay out a clear journey path by defining the current state, establishing the future state, and devising a transition plan from the current to the future state with a clear execution strategy. To ensure repeatability across different organizations or business units within your organization, it’s essential to establish well-defined design principles and maintain consistency in adoption. Monitoring key performance indicators (KPIs) is essential to track progress effectively.

Many organizations are already considering FinOps approaches today, although often not in the most cost-effective manner. Rather than addressing root causes, they apply temporary fixes that result in ongoing challenges. These temporary fixes include: 

• Periodic Reviews: IT teams convene periodically to address performance issues stemming from sizing or overspending, often in response to complaints from finance teams. However, this reactive approach perpetuates firefighting rather than proactive self-optimization. 
• Architecture Patterns: Regular updates to architectural patterns based on new features and native services from hyperscalers may inadvertently introduce complexity without clear metrics for success. 
• External SMEs: Bringing in external subject matter experts for reviews incurs significant costs and requires effort to bring them up to speed. Relying on this approach contributes to ongoing expenses without sustainable improvements. 

To avoid these pitfalls, it’s crucial to establish well-defined KPIs, benchmarking, and processes for real-time insights and measurable outcomes. 

While some organizations assign FinOps responsibility to a centralized team for monitoring spending and selecting cloud services. This approach can create silos and hinder visibility into planned changes, leading to dissatisfaction and downstream impacts on service delivery. Federating FinOps activities across the organization ensures broader participation and diverse skills, promoting collaboration and avoiding silos. 

The next steps in your FinOps journey

Regardless of where you are in your cloud journey, it is never too late to adopt best practices to make your cloud consumption more predictable. IBM Consulting®, along with Apptio as a product, can help you adopt the right architectural patterns for your unique journey.

Source: ibm.com

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Scaling generative AI with flexible model choices

This blog series demystifies enterprise generative AI (gen AI) for business and technology leaders. It provides simple frameworks and guiding principles for your transformative artificial intelligence (AI) journey. We discussed the differentiated approach by IBM to delivering enterprise-grade models. In this blog, we delve into why foundation model choices matter and how they empower businesses to scale gen AI with confidence.

Why are model choices important?

In the dynamic world of gen AI, one-size-fits-all approaches are inadequate. As businesses strive to harness the power of AI, having a spectrum of model choices at their disposal is necessary to:

• Spur innovation: A diverse palette of models not only fosters innovation by bringing distinct strengths to tackle a wide array of problems but also enables teams to adapt to evolving business needs and customer expectations.
• Customize for competitive advantage: A range of models allows companies to tailor AI applications for niche requirements, providing a competitive edge. Gen AI can be fine-tuned to specific tasks, whether it’s question-answering chat applications or writing code to generate quick summaries.
• Accelerate time to market: In today’s fast-paced business environment, time is of the essence. A diverse portfolio of models can expedite the development process, allowing companies to introduce AI-powered offerings rapidly. This is especially crucial in gen AI, where access to the latest innovations provides a pivotal competitive advantage.
• Stay flexible in the face of change: Market conditions and business strategies constantly evolve. Various model choices allow businesses to pivot quickly and effectively. Access to multiple options enables rapid adaptation when new trends or strategic shifts occur, maintaining agility and resilience.
• Optimize costs across use cases: Different models have varying cost implications. By accessing a range of models, businesses can select the most cost-effective option for each application. While some tasks might require the precision of high-cost models, others can be addressed with more affordable alternatives without sacrificing quality. For instance, in customer care, throughput and latency might be more critical than accuracy, whereas in resource and development, accuracy matters more.
• Mitigate risks: Relying on a single model or a limited selection can be risky. A diverse portfolio of models helps mitigate concentration risks, helping to ensure that businesses remain resilient to the shortcomings or failure of one specific approach. This strategy allows for risk distribution and provides alternative solutions if challenges arise.
• Comply with regulations:The regulatory landscape for AI is still evolving, with ethical considerations at the forefront. Different models can have varied implications for fairness, privacy and compliance. A broad selection allows businesses to navigate this complex terrain and choose models that meet legal and ethical standards.

Selecting the right AI models

Now that we understand the importance of model selection, how do we address the choice overload problem when selecting the right model for a specific use case? We can break down this complex problem into a set of simple steps that you can apply today:

1. Identify a clear use case: Determine the specific needs and requirements of your business application. This involves crafting detailed prompts that consider subtleties within your industry and business to help ensure that the model aligns closely with your objectives.

2. List all model options: Evaluate various models based on size, accuracy, latency and associated risks. This includes understanding each model’s strengths and weaknesses, such as the tradeoffs between accuracy, latency and throughput.

3. Evaluate model attributes: Assess the appropriateness of the model’s size relative to your needs, considering how the model’s scale might affect its performance and the risks involved. This step focuses on right-sizing the model to fit the use case optimally as bigger is not necessarily better. Smaller models can outperform larger ones in targeted domains and use cases.

4. Test model options: Conduct tests to see if the model performs as expected under conditions that mimic real-world scenarios. This involves using academic benchmarks and domain-specific data sets to evaluate output quality and tweaking the model, for example, through prompt engineering or model tuning to optimize its performance.

5. Refine your selection based on cost and deployment needs: After testing, refine your choice by considering factors such as return on investment, cost-effectiveness and the practicalities of deploying the model within your existing systems and infrastructure. Adjust the choice based on other benefits such as lower latency or higher transparency.

6. Choose the model that provides the most value: Make the final selection of an AI model that offers the best balance between performance, cost and associated risks, tailored to the specific demands of your use case.

IBM watsonx model library

By pursuing a multimodel strategy, the IBM watsonx library offers proprietary, open source and third-party models, as shown in the image:

List of watsonx foundation models as of 8 May 2024.

This provides clients with a range of choices, allowing them to select the model that best fits their unique business, regional and risk preferences.

Also, watsonx enables clients to deploy models on the infrastructure of their choice, with hybrid, multicloud and on-premises options, to avoid vendor lock-in and reduce the total cost of ownership.

IBM® Granite™: Enterprise-grade foundation models from IBM

The characteristics of foundation models can be grouped into 3 main attributes. Organizations must understand that overly emphasizing one attribute might compromise the others. Balancing these attributes is key to customize the model for an organization’s specific needs:

1. Trusted: Models that are clear, explainable and harmless.

2. Performant: The right level of performance for targeted business domains and use cases.

3. Cost-effective: Models that offer gen AI at a lower total cost of ownership and reduced risk.

IBM Granite is a flagship series of enterprise-grade models developed by IBM Research®. These models feature an optimal mix of these attributes, with a focus on trust and reliability, enabling businesses to succeed in their gen AI initiatives. Remember, businesses cannot scale gen AI with foundation models they cannot trust.

IBM watsonx offers enterprise-grade AI models resulting from a rigorous refinement process. This process begins with model innovation led by IBM Research, involving open collaborations and training on enterprise-relevant content under the IBM AI Ethics Code to promote data transparency.

IBM Research has developed an instruction-tuning technique that enhances both IBM-developed and select open-source models with capabilities essential for enterprise use. Beyond academic benchmarks, our ‘FM_EVAL’ data set simulates real-world enterprise AI applications. The most robust models from this pipeline are made available on IBM® watsonx.ai™, providing clients with reliable, enterprise-grade gen AI foundation models, as shown in the image:

Latest model announcements:

• Granite code models: a family of models trained in 116 programming languages and ranging in size from 3 to 34 billion parameters, in both a base model and instruction-following model variants.
• Granite-7b-lab: Supports general-purpose tasks and is tuned using the IBM’s large-scale alignment of chatbots (LAB) methodology to incorporate new skills and knowledge.

Try our enterprise-grade foundation models on watsonx with our new watsonx.ai chat demo. Discover their capabilities in summarization, content generation and document processing through a simple and intuitive chat interface.

Source: ibm.com

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Empowering security excellence: The dynamic partnership between FreeDivision and IBM

In the ever-evolving landscape of cybersecurity, businesses are constantly seeking robust solutions to fortify their defenses and navigate the complex challenges posed by cyberthreats. FreeDivision, an IBM Business Partner, stands out in the field by understanding the local needs of its clients. Operating as a security service partner, FreeDivision leverages IBM’s endpoint detection and response (EDR) solution, IBM Security® QRadar® EDR, as part of its solution, freedivision.io, to address the unique security concerns of its clients.  

Clients look to FreeDivision for help in two key areas: Security audit and consultation, and incident response and recovery.  

Security audit and consultation

Many companies still underestimate the depth of security required, often relying solely on antivirus solutions. FreeDivision’s products and expertise distinctly stand out when conducting comprehensive security checks for clients. Its solution not only protects against threats, but also acts as a vigilant hunting tool.  

Through in-depth analysis of logs, FreeDivision guides clients toward fortified security postures, minimizing the risk of ransomware and other cyberthreats. Protection against ransomware is provided by IBM QRadar EDR’s adaptive system. Due to QRadar EDR, FreeDivision can resolve security incidents in seconds. The response procedures use artificial intelligence to prevent human error and enable rapid response to threats. 

“IBM Security QRadar EDR is like a powerful EDR–the built-in AI and automation make it fast, efficient and easy to use.”  —Sandro Huber, Chief Information Officer and Co-owner of FreeDivision

Incident response and recovery

For clients who seek assistance after falling victim to attacks, FreeDivision steps in to remediate the situation and fortify defenses. By engaging with clients who experienced a ransomware attack, FreeDivision not only resolves immediate threats, but also collaborates with them to establish resilient security measures for the future. To prepare its clients for any future attacks, FreeDivision has embedded IBM QRadar EDR to detect and block new and unknown threats, from ransomware to sophisticated file attacks, to memory-only attacks.  

A ransomware hacker attack 

When PeHtoo, a Czech manufacturer, was attacked by a ransomware hacker, it engaged FreeDivision to help it recover. Ivan Eminger, CEO of PeHtoo, tells the story: 

“By our standards, we have invested considerable resources in IT operations and security. Unfortunately, it turns out that this alone was not enough. We were attacked by a ransomware hacker. Our data was completely stolen and then encrypted. We had to start rebuilding the company from scratch. 

Fortunately, FreeDivision experts helped us set up new IT processes and security standards. Thanks to its MDR services, we have a constant overview of all user processes started in our company infrastructure and any deviation from normal user behavior is immediately addressed in an isolated environment outside of production operations. Combined with network security and a next-generation security gateway at the perimeter, we are now much better prepared to counter existing threats, allowing us to focus on the core activities of our business with greater peace of mind.” 

Why partner with IBM 

The choice of FreeDivision to build its solutions with IBM is rooted in the exceptional capabilities and support offered by IBM Security QRadar EDR, formerly known as ReaQta. It remediates known and unknown endpoint threats in near real-time with easy-to-use intelligent automation that requires little-to-no human interaction. You can make quick and informed decisions with attack visualization storyboards and leverage automated alert management and advanced continuous learning AI capabilities. 

FreeDivision shared 3 key features that made its decision to choose QRadar EDR easy: 

• The console is intuitive for users. It’s customizable, and easy to use. 
• The support from IBM is unparalleled. IBM not only delivers a solution but also stands by it when challenges arise. 
• Its customers appreciate the depth of their investigation tools. 

“Our strength lies in the perfect blend of IBM’s global stature and our localized insights,” says Sandro Huber, Chief Information Officer and Co-owner of FreeDivision. “It’s the combination of IBM’s cutting-edge technology and our deep understanding of what matters in the local market. It’s a dynamic relationship built on trust, expertise, and a shared commitment to elevating cybersecurity standards.” 

Source: ibm.com

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Build the foundation for SAP ERP modernization

Successful SAP ERP modernization programs begin with clear organizational alignment on wanted outcomes and expected business value, end-to-end scope and roadmap. This alignment is critical to enterprises that run their core operations on SAP ECC for years. It helps them determine where to start their modernization initiatives and how to prioritize, organize and plan to see the value of this investment.

To build this strategic plan, enterprises need a fact base that enables them to move forward with critical SAP S/4HANA-enabled transformation decisions across people, process, enterprise architecture and next-gen technology. 

With hundreds of successful implementations of S/4HANA programs that involved both SAP ERP applications and infrastructure modernization, IBM® has a well-defined approach that is called Rapid Discovery. This approach helps determine the what, why and how for SAP ERP modernization and is infrastructure agnostic. Whether you are running SAP ERP on AIX, IBM i, Linux® or Windows, the approach remains the same. IBM’s team of cross-functional experts uses innovative tools and frameworks to build a transformative foundation composed of six essential ingredients: 

1. Enterprise Capability Model—Agreement on the business process hierarchy that defines the scope of the ERP implementation while also defining business requirements in the to-be business processes 
2. Governance Model—Clear structure, framework and operating model for program oversight and implementation including key roles, responsibilities and decision authority 
3. Business Value—Financial case for change in transformation that quantifies the tangible benefits of the program and compares them to the costs of implementation 
4. Implementation Roadmap—Clear articulation of key architectural decisions, scope of services, data strategy and implementation roadmap for transformation 
5. Executive Alignment—Alignment of executives across the business on the purpose, priorities, path forward, responsibilities and business benefits of transformation 
6. Sustainability Framework—Alignment of sustainable goals into the overall ERP strategy to allow for single source of truth data access for regulatory requirements 

As part of Rapid Discovery, we also help clients work through issues that are related to the following enablers: 

• Modern Enterprise Architecture—Design the future-state enterprise architecture, including strategic direction for application rationalization and RISE or non-RISE cloud strategy. 
• Data and Analytics—Determine the current-state realities of data readiness and develop an optimized data and analytics strategy to support and utilize the move to SAP S/4HANA. 
• Security and Controls—Define the security and controls architecture after reviewing the current maturity levels. 
• Change management—Uncover and understand the organizational change management opportunities and impacts related to ERP transformation and develop a high-level approach to unlock user adoption and value realization.

This well-defined discovery process for SAP ERP modernization helps you assess your current SAP ERP landscape, define your to-be state and align on business case, operating model and a modern enterprise architecture. If you would like to learn more, join us for the webinar, “Build the foundation for SAP ERP modernization with rapid discovery assessment” where we take a detailed analysis of this process. 

Source: ibm.com

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Simplifying IAM through orchestration

The recent validated what many of us in the industry already knew: Identity has become the leading attack vector. The 2024 report showed a 71% increase in valid identities used in cyberattacks year-over-year. What really puts it into perspective is the realization that you are just as likely to have your valid identity used in a cyberattack as you are to see a phishing attack in your organization. Hackers don’t hack in; they log in.

The risk of valid identities being used as the entry point by bad actors is expected to continue with the ever-increasing applications and systems being added in today’s hybrid environments. We are finding an overwhelming majority of organizations are choosing to use different identity vendors that offer the best capability for each use case, instead of consolidating with one vendor. The use of various identity tools is further compounded with managing access to your legacy application infrastructure, integrating new users during mergers and acquisitions. The hybrid reality has also led to an inconsistent user experience for your workers, partners and customers, an increased risk of identity-based attacks, and added an additional burden on your admins. 

To solve the identity challenges created by today’s hybrid environments, businesses need a versatile solution that complements existing identity solutions while effectively integrating various identity and access management (IAM) silos into a cohesive whole. Solutions that help create a consistent user experience for your workers, partners and customers across all applications and systems. Organizations and industry analysts refer to this connected IAM infrastructure as an Identity fabric. Organizations have begun to move toward connecting multiple IAM solutions through a common identity fabric.

Securing the digital journey

To protect the integrity of digital user journeys, organizations use a range of tools spanning bot mitigation, identity verification and affirmation, user authentication, authorization, fraud detection and adjacent capabilities such as risk analytics and access management. Building and maintaining these integrations is complex and carries an operational overhead regarding time and resources. These various tools don’t easily interconnect and don’t generate standardized types of signals. As a result, the interpretation of the varied risk signals is siloed across different events along the digital user journey. This lack of an integrated approach to managing risk along the digital user journey hinders the adoption of continuous adaptive trust principles and adds undue risk into the system. Various, disconnected identity tools prohibit you from creating that consistent user experience and security controls. Orchestration solutions improve the efficacy and efficiency of risk management along digital user journeys.

Identity orchestration

Identity and access management projects are complex enough with many taking 12-18 months. They require skilled staff to solve today’s identity challenges such as integrating IAM silos together and modernizing access to legacy applications. Many of the solutions out there are not helpful and actually create more vendor lock-in. What is really needed is an open integration ecosystem that allows for flexibility and integrations that are simple and require fewer skills to accomplish. This is where an identity fabric and identity orchestration come into play. Orchestration is the critical component and the integration glue for an identity fabric. Without it, building an identity fabric would be resource-intensive and costly. Orchestration allows more intelligent decision-making and simplifies everything from onboarding to offboarding and enables you to build consistent security policies. Identity orchestration takes the burden off your administrators by quickly and easily automating processes at scale. This enables consistent, frictionless user experiences, while improving identity risk posture, and helping you avoid vendor lock-in. 

Benefits of identity orchestration

Design consistent, frictionless user experiences

Identity orchestration enables you to streamline consistent and frictionless experiences for your workers, partners and customers across the entire identity lifecycle. From account creation to login to passwordless authentication using passkeys to account management, makes it easy to orchestrate identity journeys across your identity stack, facilitating a frictionless experience. IBM’s identity orchestration flow designer enables you to build consistent, secure authentication journeys for users regardless of the application. These journeys can be built effortlessly with low-code, no-code orchestration engines to simplify administrative burden.

Fraud and risk protection

Orchestration allows you to combine fraud signals, decisions and mitigation controls, such as various types of authenticators and identity verification technologies. You can clearly define how trusted individuals are granted access and how untrusted users are mitigated with security authentication. This approach overlays a consistent and continuous overlaying risk and fraud context across identity journey. IBM Security® Verify orchestration allows you to bring together fraud and risk signals to detect threats. It also provides native, modern and strong phishing-resistant risk-based authentication to all applications, including legacy apps, with drag-and-drop work-flows.

Avoid vendor lock-in with identity-agnostic modernization

Organizations have invested in many existing tools and assets across their IAM stack. This can range from existing directories to legacy applications to existing fraud signals, to name a few. IBM Security Verify identity orchestration enables organizations to bring their existing tools to apply consistent, continuous and contextual orchestration across all identity journeys.It enables you to easily consolidate and unify directories, modernize legacy applications and streamline third-party integration for multifactor authentication (MFA), and risk and notification systems

Leverage IBM Security Verify

IBM Security Verify simplifies IAM with orchestration to reduce complexity, improves your identity risk posture, and simplifies the user journey by enabling you to easily integrate multiple identity system providers (IdPs) across hybrid environments through low-code or no-code experiences.

IBM provides identity-agnostic modernization tools enabling you to manage, migrate and enforce consistent identity security from one IAM solution to another while complementing your existing identity tools. By consolidating user journeys and policies, you can maintain security consistency across all systems and applications, creating frictionless user experiences and security controls across your entire identity landscape.

Source: ibm.com

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Unlocking business value: Maximizing returns from your SAP investments

Amid the dynamic realms of modern business and technology, organizations seek to maintain a competitive edge and elevate business outcomes and user experiences through their SAP investments. The crux of this endeavor lies in fostering continuous value creation throughout the journey. Drawing from my experience with clients across expansive, multi-year SAP engagements, there are three areas where collaborative value creation and charting future roadmaps intertwine seamlessly.

1. Value assurance throughout the engagement journey:

Value assurance is the cornerstone of every SAP engagement, ensuring alignment with strategic imperatives, adherence to predefined objectives and delivery of anticipated outcomes. To achieve this, a meticulous comprehension of the client’s requirements, goals and challenges is essential. It is important to structure the engagement journey with periodic assessments, clear milestones and ongoing feedback to ensure the transformation stays on track.

Using structured methodologies such as the IBM® SAP Value Continuum augments this assurance significantly. This comprehensive framework embraces the pillars of cooperate, co-execute and co-create to facilitate collaborative ideation, outcome delineation and executional prowess. This fosters a symbiotic journey towards value realization.

2. Drive micro transformations with process mining:

Micro transformations, characterized by incremental yet impactful alterations, serve as the catalysts for paradigm shifts in business outcomes. Using process mining methodologies unveils latent opportunities for enhancing operational efficiencies, thereby allowing clients to achieve quick wins and build momentum for larger-scale transformations.

Process mining is a powerful service offering that helps organizations identify inefficiencies in business processes and uncover areas for improvement. Whether streamlining order-to-cash processes, optimizing supply chain logistics or enhancing customer experience touchpoints, process mining catalyzes tangible enhancements such as cost reduction, heightened productivity and augmented customer satisfaction.

Process mining can help at every stage of the SAP lifecycle and enables the right decisions at the right time. Some of the key use cases are as follows:

• Process analysis: Mine critical processes for process behaviors, deviations and KPIs. Establish a performance baseline.
• Process visualization: Convert results into models or develop to collaborate and enrich. Establish as-is processes.
• Comparison and enrichment: Compare to industry best practices. Adjust for unique processes. Adopt standards and define critical unique processes.
• Simulation and measurement: Generate embedded business cases for value realization, including cost, time, resource and bottleneck impact. 
• Opportunity identification: Analyze process performance, blockers, root cause and recommendations. Get improvements and a business case.

3. Infusing latest technology trends:

In an era where mere stability is not enough, relentless innovation takes the lead. Constant evaluation of evolving business needs, coupled with technologies and product features, defines the pathway to market differentiation. Embracing the right blend of new technological trends such as generative AI (gen AI), RPA and new SAP products and features (such as BTP, Joule, SAP Build) resonates at every stage of the SAP lifecycle. As you work to achieve this balance, focus on:

• A strong foundation: Build the fact base to confidently move forward with SAP S/4HANA-enabled transformation decisions and SAP technology roadmap using advisory frameworks such as IBM® Rapid Discovery.
• Transformation: Co-execute your transformation journey by moving ERP to cloud with RISE with SAP and IBM ManagePlus offerings.
• Next-gen managed services: Deploy noiseless operations with gen AI-enabled digital operations and modernized ways of working.
• Sustainable and continuous innovation: Achieve continuous micro-transformations with intelligent process mining, SAP clean core capabilities and extreme automation.

A holistic approach to value creation in SAP engagements is essential to ensure that clients achieve their desired business outcomes. By focusing on value assurance throughout the engagement journey, driving micro-transformations with process mining, infusing the latest technology trends like gen AI and achieving high business outcomes, organizations embark on a transformative journey to achieve their strategic objectives.

Source: ibm.com

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How generative AI will revolutionize supply chain

Unlocking the full potential of supply chain management has long been a goal for businesses that seek efficiency, resilience and sustainability. In the age of digital transformation, the integration of advanced technologies like generative artificial intelligence brings a new era of innovation and optimization. AI tools help users address queries and resolve alerts by using supply chain data, and natural language processing helps analysts access inventory, order and shipment data for decision-making.

A recent IBM Institute of Business Value study, The CEO’s guide to generative AI: Supply chain, explains how the powerful combination of data and AI will transform businesses from reactive to proactive. Generative AI, with its ability to autonomously generate solutions to complex problems, will revolutionize every aspect of the supply chain landscape. From demand forecasting to route optimization, inventory management and risk mitigation, the applications of generative AI are limitless. 

Here are some ways generative AI is transforming supply chain management: 

Sustainability

Generative AI helps to optimize companies’ supply chains for sustainability by identifying opportunities to reduce carbon emissions, minimize waste and promote ethical sourcing practices through scenario analysis and optimization algorithms. For example, combining generative AI with technologies such as blockchain helps to keep data about the material-to-product transformation unchangeable across different entities, providing clear visibility into products’ origin and carbon footprint. This allows companies proof of sustainability to drive customer loyalty and comply with regulations. 

Inventory management

Generative AI models can continuously generate optimized replenishment plans based on real-time demand signals, supplier lead times and inventory levels. This helps maintain optimal stock levels that minimize carrying costs and can improve customer satisfaction through accurate available-to-promise (ATP) calculations and AI-driven fulfillment optimization. 

Supplier relationship management

Generative AI can analyze supplier performance data and market conditions to identify potential risks and opportunities, recommend alternative suppliers and negotiate favorable terms, enhancing supplier relationship management. 

Risk management

Generative AI models can simulate various risk scenarios, such as supplier disruptions, natural disasters, weather events or even geopolitical events, allowing companies to proactively identify vulnerabilities or react to disruptions with agility. AI-supported what-if modeling helps develop contingency plans such as inventory, supplier or distribution center reallocation. 

Route optimization

Generative AI algorithms can dynamically optimize transportation routes based on factors like traffic conditions, weather forecasts and delivery deadlines, reducing transportation costs and improving delivery efficiency. 

Demand forecasting

Generative AI can analyze historical data and market trends to generate accurate demand forecasts, which helps companies optimize inventory levels and minimize stockouts or overstock situations. Users can predict outcomes by quickly analyzing large-scale, fine-grain data for what-if scenarios in real time, allowing companies to pivot quickly. 

The integration of generative AI in supply chain management holds immense promise for businesses seeking to transform their operations. By using generative AI, companies can enhance efficiency, resilience and sustainability while staying ahead in today’s dynamic marketplace. 

Source: ibm.com

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How fintech innovation is driving digital transformation for communities across the globe

To meet the demands of today’s consumers, enterprises must be continuously innovating. But innovation doesn’t happen in silos. Fintechs, for example, have been transformational for the financial services industry, from democratizing finance to establishing digital currencies that revolutionized the way that we think of money. 

As fintechs race to keep up with the needs of their customers and co-create with larger financial institutions, they can leverage AI and hybrid cloud solutions to drive true digital transformation and meet these evolving demands. 

How Dollarito is connecting larger financial institutions with financially underserved communities 

According to research from the US Government Accountability Office, roughly 45 million people lack credit scores because they don’t have certain data points that credit scores are based on, which limits their eligibility. Traditional credit report models use parameters such as the status of an active loan or credit card payment records to give an individual a credit score. If someone does not fit within these parameters, it can be difficult to procure a loan, take out a mortgage or even buy a car. However, with a more accurate model, such as one powered by AI, financial institutions can better identify applicants who are fit for credit. This can result in a higher approval rate for these populations that otherwise would typically be overlooked. 

Dollarito, a digital lending platform, is focused on helping the Hispanic population with no credit history or low FICO scores access fair credit. The platform offers a unique solution that measures repayment capabilities by using new methodology based on AI, behavioral economics, cloud technology and real-time data. Leveraging AI, Dollarito’s models tap into a wide store of data from banking transactions, behavioral data and economic variables related to the credit applicant’s income source. 

With IBM Cloud for Financial Services, Dollarito, an IBM Business Partner, is able to scale their models continuously and quickly deploy the services that their clients need, while ensuring their services meet the standards and regulations of the industry.  

“Dollarito uses IBM Cloud for Financial Services technologies to optimize infrastructure and demonstrate compliance, allowing us to focus on our mission of providing financial services to underserved communities. We are dedicated to building a bridge of trust between these populations and traditional financial institutions and capital markets. With AI and hybrid cloud technologies from IBM, we are developing solutions to serve these groups in a cost-effective way while addressing risk.” – Carmen Roman, CEO and Founder of Dollarito 

Dollarito is also embracing generative AI, integrating IBM watsonx™ assistant to help its users interact easily and get financial insights to improve the likelihood of access to credit. Like IBM®, Dollarito recognizes the great opportunity that AI brings for the financial services industry, allowing enterprises to tap into a wealth of new market opportunities.  

How Ionburst is helping to protect critical data in a hybrid world 

Data security is central to nearly everything that we do, especially within financial services as banks and other institutions are trusted to protect the most sensitive consumer data. As data now lives everywhere, across multiple clouds, on-premises and at the edge, it is more important than ever before that banks manage their security centrally. And this is where Ionburst comes in. 

With their platform running on IBM Cloud, Ionburst provides data protection across hybrid cloud environments, prioritizing compliance, security and recovery of data. Ionburst’s platform provides a seamless and unified interface allowing for central management of data and is designed to help clients address their regulatory requirements, including data sovereignty, which can ultimately help them reduce compliance costs.  

Ionburst is actively bridging the security gap between data on-premises and the cloud by providing strong security guardrails and integrated data management. With Ionburst’s solution available on IBM Cloud for Financial Services, we are working together to reduce data security risks throughout the financial services industry. 

“It’s critical financial institutions consider how they can best mitigate risk. With Ionburst’s platform, we’re working to give organizations control and visibility over their data everywhere. IBM Cloud’s focus on compliance and security is helping us make this possible and enabling us to give customers confidence that their data is protected – which is critically important in the financial services sector,” – David Lanc and Anne Lanc, Co-Founders and Inventors of Ionburst 

Leveraging the value of ecosystems

Tapping into innovations from fintechs has immensely impacted the financial services industry. As shown by Ionburst and Dollarito, having an innovative ecosystem that supports your mission as a larger financial institution is critical for success and accelerating the adoption of AI and hybrid cloud technology can help drive innovation throughout the industry. 

With IBM Cloud for Financial Services, IBM is positioned to help fintechs ensure that their products and services are compliant and adhere to the same stringent regulations that banks must meet. With security and controls built into the cloud platform and designed by the industry, we aim to help fintechs and larger financial institutions mitigate risk, address evolving regulations and accelerate cloud and AI adoption. 

Source: ibm.com

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