Tag: cloud

Cloud ERP Wars: Is Infor Adoption Reaching the Tipping Point? | Blog

As enterprises turn to industry-specific ERP solutions, Infor’s growing presence in the Cloud ERP market is becoming more prominent. This blog explores Infor’s strengths and challenges as it aims to compete with traditional ERPs. Reach out to us to discuss further.

In recent interactions with enterprises regarding their ERP investments, it has become evident that there is a growing preference for industry-specific ERP that can bridge the gap between traditional ERP and core business systems. While traditional ERPs such as SAP, Oracle, and Dynamics cater to broader enterprise objectives, industry-specific ERPs are tailored for specific industries, offering specialized functionality, seamless integration, and industry-focused approaches that shape their offerings.

Industry-specific ERPs offer several advantages over traditional counterparts, including industry-specific features, cost efficiency, smooth integration, rapid implementation, enhanced user experience, comprehensive data insights, and adaptability to dynamic market conditions.

One prominent player in this landscape is Infor, a platform we have closely observed. In a previous blog from February 2020 titled “Koch Industries’ Takeover of Infor Signals Key Bet on Cloud ERP Market | Blog,” we delved into the reasons behind Infor’s acquisition and its implications for the Cloud ERP sector.

Infor’s financial performance is notable, boasting approximately US$3.5 billion in total revenue and around US$1.2 billion in SaaS revenue. The platform has achieved remarkable growth of around 20% over the past few years.

There are several key factors contributing to Infor’s success:

  • Deep industry-specificity: Infor’s primary strength lies in its strong focus on industry-tailored offerings, especially for manufacturing, healthcare, retail, and the public sector. Infor’s commitment to industry-specificity is evident from its investment in restructuring its internal organization around focus industries
  • Increasing global presence and partnerships: With operations spanning over 45 countries and a workforce of over 19,000, Infor’s global presence is substantial. Its extensive partnership network encompasses resellers, alliance partners, product partners, service partners, and support partners, featuring prominent names such as Accenture, HCLTech, Deloitte, Wipro, and TCS, as well as specialized partners such as Grant Thornton and Advoco
  • Cloud adaptability: While initially an on-premises ERP, Infor has effectively evolved its cloud capabilities over time. Its leadership in cloud adoption within the industry-specific ERP segment has been recognized, attributed in part to strategic collaborations with AWS for accelerated cloud deployment and innovation. Additionally, Infor’s unique approach to building three separate public cloud solutions, each designed to support a limited number of industries, helps it keep its solution compact, agile, and relevant.

While all the above key factors are driving Infor’s growth, there are some areas that enterprises need to be aware of while assessing Infor as their ERP of choice –

  • AI and gen AI capabilities: Technology is constantly evolving, and expectations for all platform functionality to have AI and gen AI embedded are also picking up. While Infor offers some capabilities, competitors such as Microsoft, Oracle, and SAP are making significant investments in this area. Enterprises may need to evaluate AI and related technologies closely relevant to their needs
  • Enterprise feedback: Some enterprises have raised concerns about Infor’s reporting tools, customer support, and the complexity of integrating with other systems. Enterprises must be aware of such concerns before starting their ERP implementation journey
  • Heavy customization needs: Infor’s strength lies in its industry-specific solutions, but this focus might not be ideal for companies that require extensive customization of their ERP system

The implications for both enterprises and service providers are noteworthy. While Infor’s platform primarily catered to SMBs, there is an observable shift towards larger deals and expanded market share, especially in comparison to traditional ERPs. Enterprises are becoming discerning in their ERP choices, exploring alternatives beyond conventional options to maximize value from their investments. Moreover, Infor is gaining traction even among larger corporations, as exemplified by companies such as Pfizer, Electrolux, Lenovo, GAP, and Jaguar. Instances have emerged where Infor’s solutions have been adopted to replace or supplement traditional ERPs. Recent examples include Riedel, SEG Automotive, Delta Plus, and Saudi Lime.

The adoption of cloud in manufacturing and related industries has hit the tipping point where we see accelerated adoption of cloud, whether this enables Infor to hit its tipping point is a story that is yet to unfold. As Infor scales up to become relevant for large and very large enterprise segments, it needs to address challenges around integration and business value realization from the ERP investments. At the same time, they would also need to get the mindshare of a partner network for them to scale up the talent needed for Infor implementation. Few providers have already started scaling their Infor practice; however, that may not be sufficient.

Watch this space for additional blogs on how the key niche ERP players are evolving with time, key considerations for enterprises and service providers, and what this means for traditional ERPs.

What has been your experience with Infor? Please feel free to write to us at [email protected] and [email protected].

Salesforce and IQVIA’s Partnership – A Match Made in Heaven? | Blog

What impact will Salesforce’s upcoming global partnership with IQVIA have? Get the expert view here, or get in touch to understand how this significant move in the life sciences CRM sector might impact your business.

Once again, the winds of change are blowing in the life sciences CRM landscape. The usual suspect, Salesforce, has announced its strategic global partnership with IQVIA to enhance the capabilities of its Life Sciences Cloud.

This is noteworthy, more so in the backdrop of the Veeva and Salesforce separation in 2022, where Veeva fully embraced its home-brewed offering, Veeva Vault. The Salesforce-IQVIA partnership marks a significant move in Salesforce’s commitment to delivering robust life sciences customer engagement solutions.

However, whether this move will truly propel Salesforce to the industry apex remains to be seen. Veeva has already established itself as the go-to solution for life sciences enterprises; on the other hand, Salesforce carries the baggage of being a jack-of-all-trades, master of some in the customer engagement arena. The hiring of Frank Defesche – a former Veeva executive – by Salesforce to lead its life sciences division is one of several initiatives that drives home the point that the battle for market leadership is going to be fierce.

Key takeaways of the Salesforce-IQVIA partnership

  • In this expanded partnership, IQVIA licenses its OCE software to Salesforce, accelerating the development of Salesforce Life Sciences Cloud for customer engagement that is slated for release in 2025
  • IQVIA will continue to market the OCE product and support its nearly 400 global OCE customers in over 130 countries up until 2029
  • IQVIA will collaborate with Salesforce to jointly market the new offering, with System Integrator (SI) partnerships being leveraged to provide support services (data migration, maintenance, etc.) for OCE customers

Clash of the CRM titans: potential prospects and pitfalls of the expanded partnership

Historically, Veeva has been at loggerheads with both CRM incumbents: IQVIA (Veeva’s Antitrust Lawsuit against IQVIA) and Salesforce (halting its partnership with Salesforce Cloud). However, currently, IQVIA and Salesforce have allied to confront the Customer Engagement Platform (CEP) market. This partnership brings forth several prospects and pitfalls, as illustrated in the exhibit below:

Slide2

Prospects: While IQVIA continues to lead the market in life sciences data management, it faces formidable competition from Veeva. However, the recent collaboration between IQVIA and Salesforce has fostered innovation and equipped Salesforce with data management expertise to leverage. Furthermore, this partnership extends Salesforce’s customer engagement market influence by granting access to IQVIA’s clientele. By integrating the data and analytics of IQVIA with the powerful CEP of Salesforce, the partnership promises a holistic overview of customer interaction and insights. This potential end-to-end, industry-specific solution will go on to streamline operations and efficiency through integrated systems and workflows.

Pitfalls: As the IQVIA-Salesforce transition gradually unfolds until 2029, they will encounter increased expenses for training, upskilling, onboarding, and more operational processes. Integrating existing legacy systems with the new IQVIA-Salesforce solutions will be challenging. Changing the status-quo will require a relook at data privacy and regulatory compliance by enterprises, which can be quite resource-intensive. The partnership also adds an uncertainty variable, as transitioning from the existing CRM may lead to concerns around the overall impact on business operations and workflows. As enterprises transition to the new system, there will be a risk of data migration, system downtime, and a potential loss to business. Currently, the Salesforce customer engagement platform is distinguished by its premium licensing fees, which might further increase due to the ongoing partnership. While this presents opportunities for SIs for project management endeavors, the new Salesforce Life Sciences Cloud should still demonstrate its value.

Amid the transition journey, the selection of appropriate SI will be paramount

The world of CRM is seeing a gigantic wave of customer-centricity, and service providers who still hold on to horizontal approaches will be swept under it. The days of a one-size-fits-all solution are over; now, enterprises seek solutions that can withstand the ever-changing dynamics of the market with technological and operational flexibility. Service providers must look beyond consultation and implementation by taking up change management initiatives that deliver long-term value for their clients. They are expected to stay abreast of the latest developments, and provide solutions tailored to the unique needs of enterprises.

Service providers will play a critical role in strategic consulting, data migration, implementation, customization, and ongoing support to ensure smooth transitions for enterprises adopting new customer engagement systems. It can cash in on these opportunities by monetizing various aspects of the collaboration, as elaborated below:

Slide3

Enterprises face a trilemma

Enterprises are weighing their options carefully as the life sciences CRM market continues to evolve in its trajectory. The three broad options for enterprises are as follows:

  • Adopt Salesforce’s Life Sciences Cloud: Enterprises may choose to be early adopters of Salesforce’s Life Sciences Cloud, embracing the perfect blend of IQVIA’s life sciences expertise and Salesforce’s customer engagement platform capabilities. This option promises a transformative engagement platform with enhanced data integration so that enterprises can leverage the best of both worlds
  • Shift to Veeva Vault: Enterprises familiar with Veeva’s industry-specific solutions may adopt the Veeva Vault for its proven capability. This option provides stability and continuity given Veeva’s deep industry focus and comprehensive suite of offerings, including closed-loop marketing, built-in compliance, and data-driven suggestions
  • Explore budding alternatives (such as TrueBlue, Exeevo, etc.): Enterprises that are open to experimentation, such as alternatives like TrueBlue and Exeevo, make for an interesting proposition. The emergent life sciences CEP players offer a fresh perspective with an emphasis on agility and customer-centricity. Compatibility, scalability, and support are some of the factors that are essential to evaluate for maximizing the value of CEP investment

Implication of the partnership to the broader CRM narrative

This partnership signifies the eventual departure of IQVIA from the competition by the decade’s end, leaving only two dominant incumbents, Veeva and Salesforce, in the market. Presently, Veeva commands the lion’s share of the life sciences CRM market, but this landscape is expected to evolve in the years ahead. Additional implications within the CRM market are depicted in the exhibit below:

Slide4

Is this the start of happily ever after for the industry?

With the life sciences commercial landscape evolving consistently and the ongoing evolution of Generative AI technology, the pace of innovation is frenetic within the life sciences industry. This rapid progress is also giving rise to a new wave of specialized providers catering to niche needs. Consequently, enterprises must continuously assess the evolving landscape of commercial technology offerings and augment their tech infrastructure accordingly.

If you have questions about the life sciences IQVIA’s extended partnership with Salesforce or would like to discuss developments in the life sciences commercial space, please reach out to [email protected] or [email protected] or [email protected]. For a deeper understanding of the shift to next-gen customer products in the life sciences sector, read our blog.

Watch our discussion on the critical shift from CRM ecosystems to CX platforms in our session, Key Insights: The Evolving Commercial Technology Landscape in Life Sciences.

Beyond the Hype: Approaching Gen AI in BFSI Enterprises with the Generative AI-EXCEL Framework | Blog

To successfully adopt Gen AI in BFSI, enterprises need to consider four fundamental aspects that can lead to responsible and effective deployment. Carefully evaluating each framework component is essential to ensure a positive Gen AI journey. Read on to learn about the Generative AI-EXCEL Framework and the importance of each element, or get in touch.

As there is urgency to embrace Generative Artificial Intelligence (Gen AI) across all industries – the BFSI industry is no exception given its prevalence. However, a thoughtful approach is required to fully reap the benefits of Gen AI.

Before immersing themselves in various use cases and integrating Gen AI into their operating structure, BFSI enterprises should strategically examine four fundamental components along the Gen AI value chain:

Generative AI-EXCEL framework

  • Enable AI
  • Execute AI
  • Champion AI Operations
  • Lead AI Change Management and Governance

These elements can guide enterprises toward harnessing the full potential of Gen AI in BFSI while ensuring responsible and effective deployment.

Beyond the Hype Approaching Gen AI in BFSI Enterprises with a Generative AI EXCEL Framework pdf

Beyond the Hype Approaching Gen AI in BFSI Enterprises with a Generative AI EXCEL Framework2 pdf

Enable AI

Embarking on AI initiatives demands the expertise of AI experts to define a clear vision and strategy. Seeking guidance from Gen AI experts is essential in laying a solid foundation for successful implementation. Assessing organizational readiness through an AI maturity and readiness assessment is recommended as this can provide insights into preparedness levels and potential challenges.

Developing a Gen AI roadmap and conducting a Return on Investment (ROI) analysis further ensures a well-structured approach, allowing organizations to navigate the complexities of integrating Gen AI effectively in their operations. A thoughtful approach is essential for consulting and enabling generative AI across the value chain before delving into specific use cases, relying on AI technology partners, and tool selection advisory services to ensure that organizations secure the right resources for success.

Adequate resources are crucial to ensure scalability, allowing Gen AI systems to manage increasing workloads efficiently. There is a lot of demand for talent, skills, and domain expertise, especially in Gen AI that needs to be plugged.

Moreover, hardware and infrastructure compatibility and version compatibility among different Gen AI models and frameworks are essential for seamless operations. Massive datasets play a pivotal role in training large-scale AI models, demanding significant computational power from specialized hardware such as graphics processing units (GPUs) and tensor processing units (TPUs). Balancing these elements is vital to harness the potential of Generative AI effectively.

Execute AI

When developing AI systems, some essential steps include preparing the data, refining features, utilizing and fine-tuning pre-built models, integrating AI with existing systems, creating custom models as needed, and conducting thorough testing to ensure reliability.

The increasing complexity of Gen AI models has led to the emergence of Machine Learning Operations (MLOps) and Large Language Model Operations (LLMOps) as services. These can play a pivotal role in easing the efficient deployment, orchestration, and monitoring of AI models.

Given the possibility of potential biases introduced by Gen AI, it becomes imperative for BFSI enterprises to ensure fairness. Vigilant model monitoring and drift analysis are some ways to achieve this. In addition, optimized performance can be achieved by incorporating accelerators.

Champion AI Operations

A robust change management strategy is essential for navigating a smooth transition. Leadership communication about AI’s benefits can set a positive tone for adoption. Equipping workforce with the necessary skills through comprehensive training and upskilling is essential. Developing a streamlined process for Gen AI adoption can enhance its acceptance rate. Recognizing and reinforcing Gen AI’s contributions can motivate the workforce, ensuring effective and sustainable AI integration.

Lead AI Change Management and Governance

Strong data governance can help address some of the concerns related to source attribution and confidence levels in data and foster trust in Gen AI outcomes.

Gen AI can generate content that is low in authenticity. Model explainability can help make AI decisions more understandable and traceable, boosting user confidence. Furthermore, enforcing compliance, validation, and auditing mechanisms can reinforce AI solutions’ reliability and ethical deployment.

The Gen AI model can potentially produce biased or dangerous results. Other AI models can be used to test results for risky outputs. Enterprises can also use data loss prevention and other security tools to prevent users from inputting sensitive data into prompts in the first place. Maintaining control over data is essential, and multiple levels of security are required.

In an industry where data security and privacy are paramount, governance becomes a linchpin for safeguarding sensitive information. Beyond regulatory compliance, governance can address critical aspects such as risk management, fairness, transparency, and accountability. With ongoing regulatory uncertainty and evolving laws, it is critically important to exercise caution about data breaches, privacy violations, or biased or discriminatory decisions that can create regulatory liabilities.

By following this Generative AI-EXCEL framework, BFSI enterprises can ensure they have addressed all essential aspects of enabling Gen AI. From identifying the right infrastructure and resources to developing and testing models and ensuring proper change management and governance, thoroughly evaluating each component guarantees a smooth AI transition. This approach will allow BFSI enterprises to harness Gen AI’s power fully.

To discuss Gen AI in BFSI, please reach out to [email protected], [email protected], and [email protected]. Learn more about how we can help your enterprise to leverage Gen AI, or read our report on revolutionizing BFSI workflows with Gen AI.

Generative AI and Cloud Integration Keep Mainframes Alive in the BFSI Industry | Blog

Though a recent Everest Group survey revealed the pressing need for mainframe modernization, the technology is far from dead in the banking, financial services, and insurance (BFSI) industry. The rise of generative AI (gen AI) will encourage more BFSI firms to adopt a comprehensive technical architecture, integrating cloud and mainframe technology at its core. Read on for insights from the survey or get in touch. 

Are BFSI firms really ditching mainframes? The BFSI industry is indeed grappling with the prospect of abandoning this approach. According to an Everest Group survey, about half of the respondent firms have shifted their peripheral tasks away from mainframes.  

Concerns about mainframe system scalability loom large for more than 50% of sizable BFSI firms, while about 60% of smaller firms struggle primarily with finding talent skilled in older programming languages such as COBOL.  

Operational complexity with mainframe systems is also reported as a challenge by over 90% of BFSI respondents, underscoring the pressing need for mainframe modernization. Evolving priorities such as building data-driven workflows, digitalization, and enhancing customer experiences further fuel this urgency. 

Cost efficiency and talent unavailability are the main drivers for mainframe modernization, closely followed by the imperative for innovation. North American firms prioritize core banking and CRM workloads over modernization, while European players emphasize digital channels and payment infrastructure. 

Despite these challenges, mainframes are expected to remain integral to BFSI operations. A significant majority, about 60% of the respondent firms, have not yet started modernizing their core systems. In the coming years, non-core applications will continue to have a higher migration rate than core applications.  

However, industry research underscores that BFSI enterprises optimize and enhance their mainframe ecosystems, presenting a promising opportunity for service providers to assist. Let’s explore this further.  

Capturing cloud value through a hybrid infrastructure

With mainframes here to stay in the BFSI industry, enterprises can gain a competitive advantage by investing in the private cloud to capture the underserved and large demand for hybrid IT. Hybrid cloud is a constant across all our BFSI industry enterprise conversations.  

Of the respondent BFSI firms, 35% utilize private cloud for their modernization initiatives — mainly in a hybrid cloud environment — while 65% rely on a multi-cloud strategy.  

IBM’s focus on transforming the mainframe’s interface to other environments validates this trend. The launch of z15 and z16 is the company’s answer to the age of cloud computing. It is an evolution to meet the needs of hybrid cloud deployments, leveraging investment in data, generative Artificial Intelligence (gen AI), and applications, adding features and functionality to complement this strategy. IBM is focusing its messaging on rightsizing over downsizing. The strategy to provide more flexibility, predictability, and cost-effectiveness is evident in the company’s push for tailored fit pricing.   

The survey reveals many firms believe the disconnection between mainframe environments and new cloud-native systems and applications is a big challenge. Further investments in technologies like application programming interfaces (APIs), in collaboration with technology and service providers, will help bridge this gap in the coming years. 

Will banking’s AI revolution enable cloud-based modernization? 

We expect a symbiotic relationship between gen AI and IT modernization, each complementing the other’s growth. Cloud computing is the foundational block providing the right computational power to run AI applications, while AI’s enhanced speed and efficiency will support cloud migrations.  

BFSI firms are channeling investments into gen AI, crafting use cases to support their modernization initiatives and business operations. The survey found that 40% of the BFSI firms have proof of concepts or use cases for gen AI to support mainframe modernization.  

Firms have moved beyond experimenting with gen AI. Goldman Sachs and Deutsch Bank have started using gen AI to generate code and refactor their modernization initiatives, closely watching the impact. They are building and rolling out use cases to improve operational efficiency. We believe that the banks poised for future success are identifying use cases that solve specific business problems aligned with their organization’s strategy. This can enable them to measure the results easily and encourage leadership buy-in.  

With mainframe modernization services growing at a steady 4-5%, the ability to adapt and innovate using newer technologies such as gen AI will drive more BFSI firms to adopt a more robust and holistic technical architecture with both cloud and mainframes at its core. 

However, the question remains: will gen AI bring exponential change in the next three years? There is one certainty: the need for a strong IBM, service provider, and hyperscaler value proposition will continue to grow for BFSI clients. 

To discuss mainframe modernization further, please contact [email protected] and [email protected]. Understand more about the future of the enterprise mainframe, or watch our on-demand webinar on the future of generative AI implementation at enterprise level.

Navigating Cloud Portability and Exit Strategies in Banking and Financial Services | Blog

Cloud service providers are vital partners in helping Banking and Financial Services (BFS) institutions build robust systems for cloud migration and exit strategies to maneuver complex regulatory and operational environments. These approaches promise to ignite technological innovation. Discover actions the world’s leading banks are taking and their importance in today’s financial landscape in this blog. Contact us to discuss further.

In the BFS industry, cloud has become synonymous with innovation and agility. Yet, as the space matures in its digital transformation journey, a crucial pivot is taking place. The focus is not solely on cloud migration but on nimbly and cautiously maneuvering within it. This shift brings to the forefront the importance of cloud portability and exit strategies – concepts rapidly gaining traction as BFS enterprises seek to future-proof technology investments. Let’s explore this further.

The strategic imperative of cloud portability

Cloud portability has risen to a strategic imperative within the BFS space. It encapsulates the capability to seamlessly transition applications and workloads between cloud environments, ensuring operational resilience and uninterrupted compliance. This degree of agility is fundamental in mitigating risks associated with vendor lock-in. Additionally, it enables BFS enterprises to adapt rapidly to evolving regulatory requirements and market conditions.

Major banks have spearheaded the charge towards cloud portability by embracing technologies that allow flexibility. Adopting containerization technologies and microservices architecture, notably through Kubernetes, is a case in point. These technologies provide a layer of abstraction, decoupling applications from the underlying cloud infrastructure, which empowers banks to maneuver digital assets across platforms without the burdens of significant downtime or exorbitant costs.

For instance, major financial institutions such as Bank of America and JPMorgan Chase have been at the forefront of embracing cloud-native technologies. Bank of America has utilized Kubernetes to enhance its application deployment processes, enabling faster innovation and improved customer service. Similarly, JPMorgan Chase has invested in containerization to streamline its IT infrastructure, demonstrating the significant efficiency and flexibility benefits these technologies offer to the BFS industry.

Navigating exit strategies in a regulated landscape

While less discussed, cloud exit strategies are vital to a comprehensive cloud governance framework. In an industry where strategic pivots or regulatory mandates can necessitate a change in cloud service providers, BFS enterprises must have clear, actionable plans for such eventualities. Crafting a cloud exit strategy involves thoroughly understanding service agreements and ensuring the transition can be executed with minimal disruption to operations and compliance protocols.

Goldman Sachs’ adoption of a multi-cloud strategy exemplifies a preemptive approach to exit planning. By distributing workloads across AWS, Azure, and Google Cloud, it is poised to maintain continuity of service and positioned to negotiate the transition of services, should strategic or regulatory circumstances change.

The formulation of cloud exit strategies is intricately linked to the BFS industry’s regulatory environment. Institutions must have actionable plans to transition away from cloud providers as strategic, regulatory, or operational landscapes evolve.

Over the last decade, regulations such as the General Data Protection Regulation (GDPR) in Europe and the Federal Financial Institutions Examination Council (FFIEC) guidelines in the United States have necessitated that banks maintain strict data governance and security protocols during such transitions.

These regulatory frameworks compel banks to plan their cloud engagements meticulously. For instance, compliance with GDPR requires that any BFS institution operating in or serving customers in the European Union (EU) must ensure its cloud exit strategy does not compromise data protection standards, even during service provider transitions.

For BFS enterprises, investing in cloud portability and a strategic exit plan is a direct response to the industry’s complex risk profile. These strategies protect them against the uncertainties of the cloud market and the evolving regulatory landscape. The goal is to safeguard investments and ensure that cloud engagements remain agile, compliant, and aligned with the overarching business objectives.

How can service providers become strategic partners in this roadmap?

Cloud service providers are pivotal in facilitating the BFS sector’s cloud transitions, having evolved from mere hosts of workloads to strategic partners. Mid-market providers illustrate this evolution by aiding BFS institutions in cloud migration and strategically planning portability and exit. These service providers ensure that cloud architectures are crafted to be vendor-agnostic and that exit strategies are incorporated into the engagement from the outset, aligning with the BFS industry’s stringent standards.

Elements of a comprehensive cloud strategy

The evolving cloud landscape necessitates a proactive and all-encompassing approach to strategy development. A holistic cloud strategy should incorporate the following:

  • Prioritizing open standards and application programming interfaces (APIs) to facilitate easy transition between cloud environments
  • Evaluating technology stacks in detail to uncover and mitigate potential lock-in risks
  • Negotiating transparent and favorable contractual terms with cloud providers that account for the potential need to exit
  • Developing robust business continuity plans that include cloud service transitions

The road ahead

As the BFS sector looks to the future, the trajectory of cloud computing strategies points toward greater flexibility, regulatory compliance, and strategic agility. The increasing importance of cloud portability and exit strategies is set to catalyze a new wave of technological innovation and strategic foresight. The pioneering steps some of the world’s leading banks are already taking demonstrate this evolution.

Large banks have been front-runners in leveraging cloud technology to enhance their financial services. Collaboration with hyperscalers, such as AWS, Azure, and Google Cloud, is part of the broader strategy to adopt a cloud-first approach by distributing workloads across different cloud providers.

Goldman Sachs has been using AWS’s capabilities to innovate in financial data management, leveraging cloud technology for scalability and efficiency and ensuring its architecture supports portability and compliance. This move indicates a broader trend among BFS institutions to harness the power of cloud computing while emphasizing the importance of cloud portability and the ability to adapt and exit in line with strategic and regulatory needs.

Moving forward, collaboration between BFS institutions and cloud service providers is expected to deepen, focusing on creating more robust frameworks for cloud portability and exit strategies. This partnership will be crucial in navigating the modern financial world’s regulatory complexities and operational demands, setting new standards for innovation, security, and customer-centric services in the banking sector.

BFS enterprises that diligently incorporate cloud portability and strategic exit planning into their operational frameworks are setting themselves up for enduring success. They will safeguard current investments and position themselves to leverage future technological advances and adapt to an ever-evolving regulatory landscape. We foresee that these proactive enterprises and service providers will spearhead the next wave of innovation and resilience in the BFS sector’s cloud journey.

To explore how to achieve cloud-first transformation in tandem with safeguarding the existing technology estate, contact Ayan Pandey, [email protected], and Pranati Dave, [email protected].

Don’t miss the webinar, Global Services Lessons Learned in 2023 and Top Trends to Know for 2024, to learn about the successes, challenges, and transformative trends that defined the global services industry in 2023 and discuss the opportunities that lie ahead for business leaders in 2024.

AWS re:Invent: The Story Beyond Generative AI | Blog

While Generative Artificial Intelligence was a major focus at the recent Amazon Web Services (AWS) annual user conference in Las Vegas, other important themes stood out to our analyst team. These include an increased focus on partnerships, cost optimization, and new growth channels. Read on for our analysis of the trends to pay attention to from AWS re:Invent 2023.

Since attending AWS re:Invent from Nov. 27 to Dec. 1, we have been digesting the newer offerings, alliances, and strategic focus areas for AWS. This blog explores the top three themes we believe make their mark in the sea of announcements, initiatives, and even unspoken priorities.

Increased focus on the partner ecosystem

Much like prior years, a significant focus was put on the partner network, including service providers (global system integrators, niche system integrators, etc.), technology partners (large and small vendors), and others (e.g., resellers).

The AWS Marketplace witnessed significant changes to help partners that are already well supported. Many service providers demonstrated high-value client transformation case studies during keynote sessions, round tables, and in expo booths.

With the massive spectrum of service partners and their diverse wish lists, we firmly believe a key focus area for AWS should be improving the profitability of its AWS business. AWS needs to make it simple to use its many offerings, scale personnel training, and help build tools and intellectual property (IP).

AWS continuously assesses its partner program and the results shared were encouraging. However, with the market transitioning to Generative AI, the earlier approach of building partnerships based on core infrastructure will need to evolve.

We observed that clients want service partners to proactively have strong views on specific cloud vendors they should work with rather than be indecisive. To remain the preferred choice, AWS needs to continue engaging its service partners, especially with the newer demand for cloud services.

Nonetheless, AWS will need to work with service partners to strike a balance between being the primary cloud partner, which AWS wants, while maintaining the partner’s professed cloud agnosticism to ensure they both deliver client value.

Service providers’ industry expertise is another critical engagement area. This can explain why the event did not heavily emphasize the “industry cloud” because a large part of industry-centric development will be done in collaboration with service partners.

We believe the earlier witnessed “client ownership” friction between service partners and AWS is now resolved. However, as some service partners still raise this concern with us, AWS should address this issue through partner communication and stronger action.

Cost optimization at the center of all conversations

One notable feature of AWS re:Invent 2023 was the presence of a large number of financial operations (FinOps)-focused providers in the booths. While FinOps is not new and cost optimization has always been a CIO agenda, the sudden surge in their relevance can be attributed to the current macroeconomic situation and the frantic, unplanned post-COVID cloud adoption. As a result, most enterprises ended up having complex, hybrid cloud estates and a lack of visibility, leading to spiraling costs.

According to an Everest Group survey of 450 enterprises, 63% dedicate more than 7% of their cloud spend to FinOps as they are becoming more aware of the potential cost-saving available through investments in FinOps.

The FinOps space has become quite crowded with several specialists, global and regional system integrators, and technology providers, including AWS, offering these solutions. Enterprises currently have too many choices and identifying the right partner is difficult.

The provider type also varies by their offering within FinOps and typically can be categorized by: reseller, Reserved Instances (RI)/Savings plan (SP) management provider, consulting and managed services provider, visibility and recommendations provider, and end-to-end FinOps capability and offering provider.

Some of the specialist providers that caught our attention at the event include Alteryx, Archera, Aviatrix, CAST, Chronosphere, Cloudability, CloudFix, Cloudflare, CloudKeeper, CloudZero, Coralogix, DoiT, Finout, Flexera, Harness, Kubecost, LogicMonitor, Ollion, ProsperOps, Splunk, Stacklet, Ternary, Vantage, Vega, Virtasant, Xosphere, and Zesty.

Each enterprise should identify the right solution to meet its requirements. A few considerations to keep in mind when choosing a FinOps solution or service include the ability to manage environment complexity, the metrics and key performance indicators (KPIs) used to track progress, cross-team collaboration features, availability of skilled FinOps personnel, and the visibility and dashboarding quality.

Newer channels for growth acceleration

In the third quarter of 2023, AWS reported US$23.1 billion in revenue, up 12% year-on-year, but the growth rate was below the company’s typical historical increases in the mid-20 to low-30% range. The same trend is visible across its partner ecosystem, except for a few specialist players.

The growth rate of most global cloud system integrators has diminished by more than half compared to 2021 and 2022. Amid this slowdown, we sense an emphasis on identifying channels for growth acceleration within AWS and across its entire ecosystem partners.

Generative AI was the biggest growth bet and talking point for all attendees at the event. Almost every major announcement by AWS was around Generative AI. However, it’s worth noting that Generative AI has had little influence on the top line of hyperscalers, technology vendors, or system integrators.

Most Generative AI implementations are still in the proof of concept stage, with more than 90% of deal sizes being under US$1 million. AWS expects that many Large Language Models (LLMs) will require public cloud computing capacity and is pushing all its partners to drive enterprise adoption.

However, the founder of a leading Generative AI company at the event mentioned that while the potential is enormous, the shape and form of future adoption are completely uncertain. Interestingly, he suggested with the rapid rate AI models are evolving, LLMs might get replaced by something completely new in two years. While AWS and the entire ecosystem need to continue investing and exploring Generative AI use cases, placing big bets on it could be a risky short-term proposition.

Other Focus Areas at AWS re:Invent

If not for the emergence of Generative AI, industry cloud and complex workload migration to AWS would have dominated the event. These AWS industry cloud solutions had dedicated booths right at the center of the expo hall.

However, its impact was muted by limited announcements by AWS and the lack of a serious investment intent displayed. As suggested earlier, this could be due to AWS focusing the industry cloud narrative with service provider partners who have a better understanding of industries. The impression created by AWS at re:Invent in this area was low, making it appear the hyperscaler is taking a wait-and-see approach.

Another growth area AWS is expected to pursue is the migration of complex workloads, like mainframes, to its platform. It announced partnerships with a few system integrator partners and showcased its intent to help enterprises migrate.

With a significant portion of simple workloads already migrated to the cloud, complex workload migration could be the most stable growth potential for AWS in the next few years. AWS and its partners should double down on investments in this area.

Undeniably, AWS re:Invent 2023 turned out to be a delicate balancing act of strengthening the partnership network, investing in emerging innovation areas, maximizing client value, and ensuring cost optimization in the current macroeconomic environment. We would love to hear your observations from AWS re:Invent. To share your views or to discuss other details, please reach out to [email protected] or [email protected].

Learn more about the AWS services market, including trends, demand drivers, and key considerations for enterprises.

A Delicate Balancing Act: Maximizing Cloud Value from AWS | Blog

With cloud spending under scrutiny, generating the most value from AWS investments while still delivering the innovation enterprises demand is crucial. To achieve their goals through AWS, enterprises need to consider strategic alignment, cost optimization, technical implementation, organizational readiness, and continuous improvement. Learn the key questions stakeholders should ask when evaluating their AWS cloud strategy in this blog.

As AWS re:Invent 2023 rapidly nears, cautious optimism has replaced the blissful ignorance that once characterized enterprise cloud spending. Enterprises, for justifiable reasons, are scrutinizing every dollar allocated to the cloud, and cost optimization is leading conversations across the board.

This muted atmosphere has slowed AWS’ revenue growth in recent quarters, reflecting the broader enterprise cloud adoption slowdown. In the third quarter of 2023, AWS reported US$23.1 billion in revenue, up 12% year-on-year, but the growth rate was below the company’s typical historical increases in the mid-20 to low-30% range.

Despite these cloud spending challenges, Everest Group research shows that enterprises still understand the need to innovate and expand their operations through cloud-driven digital transformation. Amidst prevailing economic and geopolitical uncertainties, enterprises are seeking to innovate and grow by carefully evaluating their cloud strategy.

The duality of cautious spending sentiment and continuously evolving customer expectations facing digital businesses has brought AWS to a crucial juncture. As Amazon’s Chief Financial Officer Brian Olsavsky pointed out during the third quarter 2023 earnings call, this has put the division in “a delicate situation.” Let’s explore how AWS is managing this.

AWS helps enterprises differentiate through innovation and partnership

AWS continues to be the leading cloud service provider, with a strong record of innovation, a large and loyal customer base, and a vast and active developer community.

In our research, enterprises have highlighted these key AWS differentiations:

  • Continued investments in strengthening IaaS offerings: Since its inception, enterprises have chosen AWS IaaS offerings for their comprehensiveness and reliability across foundational infrastructure components such as compute, network, and storage. Its secure, scalable, and global infrastructure services, along with its comprehensive capacity management tools, have made it a strong enterprise choice. Additionally, AWS’ continued innovations in building next-gen silicon chips help it support enterprises with critical Artificial Intelligence/Machine Learning (AI/ML) and high-performance computing (HPC) workloads
  • End-to-end data on cloud capabilities: With the renewed focus on data to drive AI’s future, enterprises are looking for data integration, governance, and analytics capabilities to address data privacy challenges, improve customer experience, and drive business growth. With offerings such as Amazon Aurora, DynamoDB, and RedShift, AWS dominates enterprise adoption trends for cloud-native data platforms and data analytics. Further, AWS has also become relevant for enterprises seeking to accurately address data regulation and compliance demands
  • Comprehensive partner ecosystem and AWS Marketplace popularity: The AWS partner ecosystem is a comprehensive and ever-evolving network of system integrators (SIs) and technology vendors. As a result of its strong partnerships with technology vendors and tiered classification of SIs, enterprises find AWS beneficial for identifying and enabling successful integrations across different platforms and tools through a tripartite engagement model. AWS also provides an alternate way to engage with multiple system integrators and independent software vendors (ISV) through its extremely popular AWS Marketplace to enable cost savings and procurement efficiencies, reduce licensing costs, and fulfill enterprise AWS commit

Enterprises need AWS to solve for transparency and empower cloud value

AWS’ revenue growth decline can be attributed to several factors, including the economic slowdown, cloud computing market maturation, and increased cloud provider competition.

Enterprises have highlighted the following challenges in their AWS engagements:

  • Commitment to consumption gap: Enterprises continue to get caught in the vicious cycle of overcommitment and underutilization. This has led to a significant waste of money and has made it difficult for enterprises to control cloud costs
  • Complex contracts and commercials: Enterprises have often struggled with inflexible AWS cost structures with complex caveats that lead to potential budget overruns
  • Cost management and visibility concerns: AWS’ current cost optimization offerings do not completely offer a solution for inefficient resource allocation and underutilization. This creates strong concerns about return on investments (RoI) among enterprises
  • Standalone professional services: AWS ProServe teams lack cohesiveness with SI teams during collaborative engagements, preventing enterprises from realizing the maximum potential value. This disconnect has led to inefficiencies, delays, and communication breakdowns, ultimately hindering project objectives

In addition to the above challenges, enterprises have underscored common cloud service provider challenges around integrating with legacy systems, talent shortage, vendor lock-in, and offerings complexity.

Deriving the desired value from AWS requires careful enterprise planning

Enterprises must adopt a right-fit approach for cloud engagements and workloads present on AWS. Choosing a strategic cloud service provider by mapping key business and technical requirements with the strengths of various providers is highly likely to prevail as the next differentiating factor for mature enterprises in the future.

To develop a clear understanding of how AWS can help them achieve their goals, enterprises need to consider strategic alignment, cost optimization, technical implementation, organizational readiness, and continuous improvement.

For instance, enterprise stakeholders considering how AWS can help achieve the desired value from generative AI (Gen AI) should ask:

Strategic alignment:

  • How do AWS’ Gen AI capabilities align with the overall IT strategy and business goals?
  • How can AWS’ Gen AI services help achieve desired outcomes such as increased automation, improved decision-making, or enhanced customer experiences?

Cost optimization:

  • How can the cost of Gen AI workloads on AWS be effectively managed?
  • What are the different pricing models for AWS services related to AI and Gen AI, such as Amazon Bedrock, Amazon SageMaker, Amazon Rekognition, and Amazon Comprehend?

Technical implementation:

  • What is the optimal approach to deploy and manage Gen AI models on AWS?
  • How can the security and compliance of Gen AI applications be ensured on AWS?
  • How can AI and Gen AI applications be integrated with other AWS services such as Amazon S3, Amazon DynamoDB, and Amazon CloudWatch?

Organizational readiness:

  • What skills and training are required to develop, deploy, and manage Gen AI applications on AWS?
  • How can clear governance policies and guidelines for Gen AI usage on AWS be established?

Continuous improvement:

  • What is the best method to continuously monitor, evaluate, and refine the performance of AWS Gen AI workloads?
  • How can the ROI in AWS’ Gen AI solutions be maximized?

By addressing these specific questions, enterprises can comprehensively understand how AWS can empower them to achieve their strategic objectives, optimize their cloud investments, and derive the most value from AWS.

To discuss maximizing the value from AWS and cloud spending, contact [email protected] and [email protected].

Learn more about the AWS services market, including trends, demand drivers, and key considerations for enterprises.

Unveiling Hidden Dangers: Proactive Measures to Address Cloud Migration Risks | Blog

Moving an IT ecosystem to the cloud can be a complex undertaking that involves a multitude of risks – from technology and regulatory challenges to internal hurdles, as well as other unexpected problems that can arise without proper planning. Understanding these potential pitfalls and developing a comprehensive plan to mitigate them will ensure enterprises reap the many benefits cloud offers. Uncover the risks and learn recommendations to address them in this blog.  

In the last decade, cloud has risen to immense importance across all geographies and verticals, offering enterprises numerous benefits such as scalability, agility, and cost efficiency. As a result, it has become the bedrock of any digital business, leading more enterprises to increasingly migrate to the cloud. Additionally, enterprises are now also undergoing inter-cloud migration as they strengthen their cloud strategy and prioritize IT asset optimization.

Despite its apparent simplicity and prevalence in most digital transformation initiatives, enterprises must understand the associated cloud migration risks and proactively plan for contingencies. More than 55% of enterprises believe the COVID-19 pandemic rushed cloud adoptions and limited returns from cloud investments. This reinforces the importance of understanding cloud migration risks to fully realize the benefits that cloud promises.

Let’s look at the most commonly understood and observed risks that generally fall under the following categories:

  • Technology – This encompasses risk arising from challenges in integrating legacy and modern systems, possible misconfigurations during migration, and the ever-increasing technology skill gap
  • Regulatory – This pertains to risk related to data security and privacy, vertical and geography-specific compliance and regulations, and data governance and sovereignty
  • Client’s internal environment – This involves risks such as untrained internal resources, broken security controls, reliance on third-party vendors for different services, and possible operations disruptions

While service providers generally tackle these threats from the get-go, a few other potential impediments often get overlooked during the migration phase, creating larger issues later on if not proactively addressed.

Some of these additional risks can include:

  • Underwhelming perceived value: Enterprises often do not have clear post-migration expectations, resulting in most enterprises being dissatisfied within a year or two of starting the cloud migration process. An alarming 67% of enterprises have expressed their inability to realize the expected level of value from cloud. This extends beyond monetary value and also encompasses aspects such as innovation, compliance, resilience, and agility, which are expected as by-products of successful cloud migration
  • Negative stakeholder experience: Cloud migration can impact internal and external stakeholder experience. Any security breach or service disruption can expose corporate data and applications to cyberattacks and even damage the enterprise’s reputation and erode customer trust. Additionally, any unnecessary delay in migration timelines due to factors such as network issues, application incompatibility, or inefficient processes can lead to downtime and productivity loss
  • Exceeding budget expectations: Unplanned migration costs and the complexities surrounding the entire multi-cloud system end up giving most customers price shock. Around 60-70% of global enterprises believe cloud adoption costs were higher than their initial expectations of cost reduction. This occurs due to factors such as complex multi- and hybrid cloud environments, inefficient cloud resource management, lack of governance guardrails, and gaps in consumption visibility and management
  • Conflicting objectives: Senior stakeholders from various departments often view cloud migration from different lenses and have disparate objectives. Even if service providers meet the defined Key Performance Indicators (KPIs) and Service Level Agreements (SLAs), stakeholders still can be highly dissatisfied. This commonly arises due to misalignment between cloud, product, technical, and finance teams and the lack of defined accountability and ownership that results
  • Unplanned transitions: During the enterprise transition from one provider to another or from on-premise to an outsourced service provider, a proper transition methodology is crucial. Many enterprises struggle in this phase because transition teams do not contextualize their approach to the enterprise. This often results in a disconnect between expectations and outcomes in areas such as migration velocity, proposed SLAs, and risk management

Recommendations for mitigating cloud migration risks

To lessen these risks, enterprises should take the following actions:

  1. Define the value expected from cloud expectations
  • Define what value means to your enterprise. Different stakeholders often have varying ideas of value. Conduct a comprehensive assessment to come to a shared definition of value
  • Measure alignment to the defined value metrics at all stages of executing the migration plan
  • Recognize that value realization is continuous and emphasize the importance of making it a cyclic process rather than a one-time event
  1. Plan and assemble the right delivery team
  • Include an integrated cyber-cloud team to mitigate cloud security risks associated with migration efforts
  • Conduct a comprehensive RFP procedure to ensure the onboarding of certified and skilled talent with prior similar on-ground experience. Develop a detailed talent management plan across different execution phases
  • Ensure the availability of well-structured transition teams that offer industry- and enterprise-specific contextualization, particularly when transitioning from another vendor or a captive center
  1. Leverage Intellectual Properties (IPs) and frameworks
  • Implement a value-based migration framework internally or with a service provider partner to define and measure future value
  • Adopt an open communication framework that allows regular, timely, and contextualized communication with internal and external stakeholders to ensure consistent experience. This should be in addition to technology measures such as disaster recovery plans, incident response plans, and security measures
  • Prioritize the implementation of FinOps tools and solutions to enable cost optimization and visibility at all times
  1. Evolve contracting methodologies
  • Define Objectives and Key Results (OKRs), and don’t just contract for KPIs and SLAs
  • Push for some “skin in the game” from partners by encouraging transparent and flexible pricing models
  • Include knowledge transfer in the project scope to upskill internal teams to handle post-migration changes in the enterprise IT landscape

For more strategies to tackle cloud migration risks or to share your views on this topic, feel free to reach out to [email protected] or [email protected].

Negotiating a Successful UKG Workforce Dimensions Contract: Top Five Questions to Ask to Get a Better Deal | Blog

Cloud-based Human Capital Management (HCM) tool, UKG Workforce Dimensions, uses Artificial Intelligence (AI) to offer enhanced workforce management capabilities over the current product version. But understanding the financial terms, pricing structures for various modules, and the benefits can be confusing. Continue reading to equip your organization for successful UKG Workforce Dimensions contract negotiations.

Reach out to Everest Group’s pricing experts for more information.

Enterprises benefit by using different HCM software tools and platforms to manage and optimize various aspects of the employee lifecycle, ranging from recruitment and onboarding to performance management and offboarding. These tools help enterprises transform traditional HR administrative functions into opportunities to increase employee satisfaction, engagement, and productivity.

The cloud-based HCM tool, Workforce Dimensions, developed by Ultimate Kronos Group (UKG), provides advanced capabilities compared to the company’s widely used Workforce Central tool. Some of Workforce Dimensions’ key features and capabilities include time and attendance management, absence management, workforce scheduling, payroll and HR administration, analytics, and reporting.

By leveraging AI, UKG Workforce Dimensions provides more comprehensive analytics, forecasting, scheduling, and reporting. Many existing UKG Central customers have already started migrating to UKG Workforce Dimensions.

However, many enterprises are still trying to understand the financial implications of migrating, the right price for various UKG Workforce Dimensions modules, and the benefits of the new functionalities.

Top questions to ask in negotiations

To get the best possible deal from UKG, enterprises should seek to get answers to the following five important questions:

  • What is the cost increase from UKG Workforce Central to UKG Workforce Dimensions?
  • What other aspects should be negotiated in addition to the per employee per month (PEPM) price of the UKG Dimensions bundle?
  • Does UKG support existing customers in migrating to Workforce Dimensions by investing in implementation or professional services?
  • What is the best time to negotiate with UKG?
  • Are there giveaways or other incentives that enterprises can leverage during negotiations?

In addition to these questions, we recommend enterprises also focus on the following factors:

  • Consider future demand projections – When negotiating with UKG, businesses should take into account their future demand projections. This is because the PEPM price for the UKG Workforce Dimensions bundle decreases as the number of employees increases. By assessing their near-term demand projections, enterprises can identify the optimal volume and negotiate prices accordingly
  • Seek enhanced capabilities in the base bundle – To maximize their investment in UKG, enterprises should not focus on cost alone. Instead, they also should strive to get the most feature-rich base bundle that meets their requirements. Enterprises should push for the inclusion of additional modules, like Data Hub, Analytics, etc., in the base bundle with zero or very minimal increase in the base rate

While each relationship with UKG is unique, we firmly believe these recommendations can put your enterprise in a better negotiating position. To discuss software contract negotiation and for a detailed analysis, please reach out to us at [email protected]. Explore Everest Group’s contract benchmarking offerings to learn more.

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