CIO CIO

Over the past several decades, organizations in both the private and public sectors have turned to shared services. Sometimes, the goal was reducing operational costs or improving efficiency. Other times, it was more about consolidating functions and improving service. In most cases, the shared services concept focused on a single back-office function like human resources (HR), finance and accounting, facilities management, procurement, and IT. In the IT realm, that might mean troubleshooting, help desk, datacenter management, and maintenance. In procurement, it might focus on sourcing, negotiation, contract management, and spending. While the shared services model can provide real benefits, cracks in the seams began to show about 10 years ago, fueled by changing customer demands, new supply chain realities, and a push toward full digitization. In the Asia/Pacific region, for example, companies are facing challenges in shared services implementation ranging from inaccuracies in outcomes to prolonged request completion times (IDC Survey: Shared Services Automation for Business Optimization, March 2024). These issues can impact operational efficiency and hamper both customer satisfaction and agility for organizations across the globe. More importantly, it points to a misalignment between shared services delivery and organizational needs. Factors like these are just some of the reasons why shared services has morphed into a more comprehensive service called global business services (GBS). While the goals are similar, GBS takes a completely different approach; GBS entities operate as strategic business partners that actively contribute to an organization’s shared objectives. As explained in IDC’s recent Growth and Transformation of Global Business Services (September 2024), while shared services typically pertain to a single function that can serve multiple business units, GBS can serve every unit or person in an enterprise and can execute the processes for any function anywhere in the world centrally and at scale. Typically, they provide a single point of services for combined process flows. Enterprises move to the GBS model for many reasons, including better process execution; lower cycle time; continuous visibility of process status; continually optimized workloads; flexibility; and better-balanced teams based on skills, availability, and SLAs. Over the past several years, many large organizations have benefitted from the GBS approach. IDC’s Evolution of Global Business Services (May 2023) describes several successes with this approach. For example, Siemens operates a large GBS organization that services Siemens while providing services to other firms. HSBC’s GBS organization consists of 27,000 staff in 53 countries and supports 2 trillion transactions per year. Amazon operates a large GBS organization to support its finance processes, with large teams in India, Slovakia, and the Philippines. Yet GBS growth may still be in its infancy. The model continues to evolve to embrace higher levels of technology and automation like artificial intelligence, robotic process automation (RPA), process mining, and process discovery. These advances will bring much-needed transparency, customization, and efficiency. At the same time, it has become more functional and all-encompassing. For example, KPMG has partnered with ServiceNow to provide not only comprehensive GBS services for IT, procurement, finance, HR, risk, cybersecurity, and ESG but also new solutions that will incorporate AI, low-code development capabilities, and industry-specific knowledge. These types of partnerships, in concert with new capabilities, can lead to greater transparency — which may tempt enterprises on the fence to finally lean in. Business today demands full transparency into process status and execution. While higher-level technology like RPA and process mining are critical, the centerpiece of next-generation GBS is artificial intelligence, especially generative AI, which has already begun to deliver greater automation and efficiencies that result in new capabilities at lower costs. IDC research predicts that GenAI will revolutionize the way GBS serves customers. Next-generation GBS will embrace AI in a big way, with the ultimate goal of providing more customized, transparent, and efficient services. For example, AI tools may be able to answer a query in minutes that may have taken an employee several hours or days to find. More specifically, GenAI-powered automation can improve every step in the service optimization process. It can: Automate routine and repetitive tasks like data entry, document processing, and basic customer queries Analyze service workflows, identify bottlenecks, and suggest improvements Personalize customer and user interactions Ensure that data is accurate, standardized, and readily available Analyze historical data to predict future workloads Continually learn from data and user interactions, enabling service organizations to adapt and improve over time All of these factors together present great opportunities for organizations that choose to embrace the GBS model. Next-generation GBS models will be more able to bring process acceleration and visibility to the table, better connect the front and back office to enhance the customer experience, keep pushing the envelope in terms of efficiency, change processes quickly to respond to changing market and business dynamics, and remain resilient in the face of disruption. Over time, IDC expects the GBS model to mature further, with more intelligent and adaptive operating models; higher levels of process, inefficiency, and anomaly analysis; and more evolved end-to-end orchestration. Organizations considering the GBS model should keep in mind that going the GBS route is pretty much a one-way street; it’s very hard to reverse. Also, carefully evaluate up-front costs, which can be significant even though cost savings are a big driver for GBS. Learn more about IDC’s research for technology leaders OR subscribe today to receive industry-leading research directly to your inbox. International Data Corporation (IDC) is the premier global provider of market intelligence, advisory services, and events for the technology markets. IDC is a wholly owned subsidiary of International Data Group (IDG Inc.), the world’s leading tech media, data, and marketing services company. Recently voted Analyst Firm of the Year for the third consecutive time, IDC’s Technology Leader Solutions provide you with expert guidance backed by our industry-leading research and advisory services, robust leadership and development programs, and best-in-class benchmarking and sourcing intelligence data from the industry’s most experienced advisors. Contact us today to learn more. Karen D. Schwartz is an adjunct research advisor with IDC’s IT Executive Programs (IEP), focusing on IT

The question “Is the open web dying?” might evoke Betteridge’s law of headlines, which suggests that any headline ending in a question mark can be answered with “no.” But here, the answer is, unfortunately, closer to “yes.” To understand why the open web is faltering and to assess AI’s role in this decline, let’s first define what we mean by “open web.” For the purposes of this article, the open web is: Publicly accessible without barriers like paywalls or subscription fees Unfiltered by governmental censorship Free from platform-based algorithmic control, allowing content to be discovered through open browsing and linking Interoperable, meaning that it fosters connections between sites without restrictions The open web was once the backbone of online information, enabling anyone with an internet connection to freely share, link, and access content. But a combination of shifting business models, regulatory changes, and technological advancements — most recently AI — is reshaping the internet into a more closed, restrictive environment. The squeeze on small content providers and diversity A primary threat to the open web is the gradual exclusion of small content providers. Unlike large corporations with abundant resources, independent websites and niche creators often struggle to compete with the heavily promoted and easily accessible content hosted on major platforms. These smaller providers contribute significantly to the diversity of online information. When they’re squeezed out by competition or forced to hide behind paywalls to sustain themselves, it reduces the variety of voices and viewpoints available on the web. Algorithm-driven platforms are partly to blame for this problem. On platforms like TikTok, Instagram, and Facebook, what you see is largely determined by engagement-driven algorithms. These algorithms prioritize content that keeps users hooked, which tends to favor big brands, viral content, and sensationalized news over niche, independent content. Smaller creators who can’t afford to engage in paid promotion or optimize their content for these algorithms struggle to gain visibility, further eroding the diversity that once characterized the open web. Algorithmic search and the downfall of small organizations Algorithmic control is not limited to social media platforms; search engines are also shifting how they prioritize and display content. In a TheVerge.com article (“Google is getting even worse for independent sites”), a series of changes to Google’s search algorithm were shown to heavily impact small websites. In one example provided in the article, a website stated that its search traffic decreased 91% within a few months, devastating its business. Google’s Pandu Nayak was quoted during a Q&A at the most recent Google Web Creator Summit, when asked about the massive drop in traffic for smaller sites following a search algorithm change, “Our goal is to surface great content for users. I suspect there is a lot of great content you guys are creating that we are not surfacing to our users, but I can’t give you any guarantees, unfortunately” (“Google Algorithm Update Due Soon, But Don’t Expect Lost Ranking Recovery,” userp.io). The platform dependency problem: The case of Facebook and Zynga When platforms dominate traffic, they gain power over businesses that depend on them. Facebook’s relationship with game developer Zynga is a prime example. For a period, Zynga relied almost entirely on Facebook to drive users to its games. This dependency made Zynga vulnerable to Facebook’s policy shifts, and following one set of changes to Facebook’s policies, Zynga’s reach and revenue collapsed. This “platform dependency problem” is increasingly common. Businesses and content providers have become overly reliant on platforms, such as Facebook, Instagram, WeChat, TikTok, and YouTube, as gateways to their audiences. With fewer visitors discovering sites through open browsing, websites find themselves at the mercy of platform algorithms and policies. This trend harks back to the early days of the internet when AOL’s walled-garden approach reigned supreme; users were funneled through a closed environment rather than navigating the open web. It now often means users won’t even leave the platforms to experience the diversity of the open web. The rise of internet filtering and regional “internets” Countries around the world are exerting increasing control over their domestic web landscapes. Nations like China and Russia maintain tightly controlled “national internets” that restrict content accessible to their citizens. Countries like Turkey and India have also taken steps toward internet filtering, limiting content to align with governmental priorities or ideological positions. This segmentation of the web into national silos directly undermines the open web’s mission of universal accessibility. The trend threatens to balkanize the internet, creating isolated digital ecosystems where content is available only to specific audiences, subject to government oversight (“Internet Censorship: A Map of Internet Censorship and Restrictions,” comparitech.com). Even the United States has proposed a ban to TikTok (which seems to have died) that demonstrates how even in democracies there is a similar sentiment that leads to fragmentation of the internet. When the global web becomes partitioned by national borders, the open web becomes a casualty of political agendas. AI’s impact on the open web: Breaking the covenant AI, particularly generative AI, is also playing a role in the decline of the open web. Traditionally, web creators shared content with the implicit understanding that they’d receive traffic and recognition in return. Generative AI is disrupting this relationship by enabling users to access summarized or rephrased information without visiting the original source. For instance, Google’s AI-powered search features provide answers directly on the search results page, often synthesizing information from multiple sources without directing users to those sites. Similarly, services like OpenAI’s recent search technology license content from large sites and position links to the sites in the search results, but smaller organizations don’t have the power to enforce licensing fees or prominent placement, meaning they are denied both licensing revenue and advertising and traffic. These approaches are a departure from the web’s initial covenant: Creators provide content, and in return, they receive traffic and visibility. AI effectively decouples content creation from website traffic, depriving creators of the benefits they once enjoyed from direct engagement. When users can obtain comprehensive answers without clicking

How does a business stand out in a competitive market with AI? For some, it might be implementing a custom chatbot, or personalized recommendations built on advanced analytics and pushed out through a mobile app to customers. For others, it may simply be a matter of integrating AI into internal operations to improve decision-making and bolster security with stronger fraud detection. The transformative power of AI is already evident in the way it drives significant operational efficiencies, particularly when combined with technologies like robotic process automation (RPA). By eliminating time-consuming tasks such as data entry, document processing, and report generation, AI allows teams to focus on higher-value, strategic initiatives that fuel innovation. Unfortunately, implementing AI at scale is not without significant risks; whether it’s breaking down entrenched data siloes or ensuring data usage complies with evolving regulatory requirements. As AI adoption accelerates, it demands increasingly vast amounts of data, leading to more users accessing, transferring, and managing it across diverse environments. Each interaction amplifies the potential for errors, breaches, or misuse, underscoring the critical need for a strong governance framework to mitigate these risks. Above all, robust governance is essential. Failing to invest in data governance and security practices risks not only regulatory lapses and internal governance violations, but also bad outputs from AI that can stunt growth, lead to biased outcomes and inaccurate insights, and waste an organization’s resources. Keeping Data Governance at the Core of Effective AI Data falling into the wrong hands should be a concern of any business—regardless of size or status in the market. Examples include the  2008 breach of Société Générale, one of France’s largest banks, when an employee bypassed internal controls to make unauthorized trades, leading to billions of dollars lost. Similarly, in 2017 Equifax suffered a data breach that exposed the personal data of nearly 150 million people. This type of data mismanagement not only results in financial loss but can damage a brand’s reputation. Data breaches are not the only concern. An evolving regulatory landscape presents significant challenges for enterprises, requiring them to stay ahead of complex, shifting requirements while managing compliance across jurisdictions. Organizations must navigate frameworks like the EU’s General Data Protection Regulation (GDPR), the California Consumer Privacy Act (CCPA), and sector-specific mandates such as the Health Insurance Portability and Accountability Act (HIPAA). With the rise of AI and data-driven decision-making, new regulations like the EU Artificial Intelligence Act and potential federal AI legislation in the U.S. are creating additional layers of accountability. To meet current and future requirements, enterprises must implement robust compliance frameworks that include real-time monitoring and proactive reporting mechanisms And business leaders know the risk of ineffective data governance strategies. According to a Cloudera survey, 72% of business leaders agree that data governance is an enabler of business value, underscoring the critical link between secure data and impactful AI. The analytics that drive AI and machine learning can quickly become compliance liabilities if security, governance, metadata management, and automation aren’t applied cohesively across every stage of the data lifecycle and across all environments. Ensuring these elements are at the forefront of your data strategy is essential to harnessing AI’s power responsibly and sustainably. As AI usage spreads, data frequently moves between different infrastructures, making it harder to keep track of and protect. Solutions like Cloudera’s platform address a variety of constraints—organizational, regulatory, or otherwise—through a federated service that consistently secures, governs, and tracks data across hybrid cloud environments. The platform also offers a deeply integrated set of security and governance technologies, ensuring comprehensive data management and reducing risk. As AI adoption expands across entire enterprises, organizations must implement strong defensive measures and continuously monitor for potential threats as AI is integrated into various environments. Learn more about how Cloudera can help your organization ensure data governance and security are equipped to keep pace with accelerating AI adoption. source

Jitender Durairajan, Head Cloud Engineering & Solutions at Sify Technologies, believes it is imperative for businesses to carefully consider who they partner with in their digital transformation journey. He points to IDC’s research on hybrid and multicloud management as a case in point. “IDC’s research found that organizations ‘need to work with professional cloud service providers that offer end-to-end capabilities of assessment, cloud migration, security, and managed services, and that can create integration and unified management tools for hybrid/multicloud, as well as provide cloud-adjacent data centers, latency-sensitive network, and cloud management services,’. This finding is particularly relevant to Sify because it describes the breadth of offerings and the extent of the capabilities and support, they provide to more than 10,000 businesses across India today. Sify believes strongly not only in providing enterprises with best-in-class enterprise multi-tenant cloud, private, public, and hybrid cloud offerings but also everything needed to realize the optimal, most secure cloud journey – one that enables them to realize their larger transformation goals. At the heart of Sify’s cloud portfolio is CloudInfinit, a high-performance, robust, and flexible cloud infrastructure based on proven VMware by Broadcom technologies that enable enterprises to monitor and manage their entire cloud estate with ease. Sify offers customers with a dedicated fully hosted private cloud , with an option of managed public hyperscale cloud – including AWS, Google Cloud, Microsoft Azure, and OCI and everything required to combine both effectively for a truly hybrid approach. “Our long relationship with VMware reflects our shared belief in providing a comprehensive platform that delivers the full array of hybrid cloud capabilities while integrating compute, storage, networking, and security,” he adds. “With VMware at its core, our customers not only retain the VMware solutions they know and trust but also tap into the state-of-the-art developments coming out of Broadcom’s significant investments in innovation, research, and development efforts, we are happy to be directly involved in as a Broadcom Pinnacle Partner.” Private and hybrid cloud future Jitender notes that organizations in highly regulated industries like banking, financial services, government, healthcare, and insurance are increasingly adopting private cloud to ensure that they meet or exceed the most stringent data security, data sovereignty, and compliance requirements. He also points out that private cloud adoption is rightfully increasing in environments where latency and high performance are crucial factors, such as in financial trading platforms, and within sectors like manufacturing and logistics where the deep customization of IT infrastructure is often required to address unique application needs. “We have seen enterprises that originally pushed for a public cloud-first approach but realized that a more nuanced and application-specific focus is actually ideal,” he adds. “The full potential and value of an effective hybrid cloud strategy builds on that premise while delivering the numerous benefits a multi-cloud strategy enables.” Jitender notes that those include far more effective and robust disaster recovery and business continuity capabilities, greater flexibility and scalability, the ability to avoid vendor lock-in, and the ability to match the right workload to the right cloud. Notably, Sify’s hybrid cloud offerings provide all of these and more. “The enterprises that rely on CloudInfinit, from industry stalwarts in banking, government, healthcare, insurance, manufacturing, media, and retail to savvy startups, use it to match the right workloads with the right cloud based on performance, cost, and security needs,” says Jitender. “And our wider portfolio and extensive offerings further optimize the systems involved. In this way, the organizations we partner with know they will receive the full expertise, solutions, and support they need to migrate to the cloud, manage the cloud, and optimize the cloud.” AI Advancements Jitender says, “Looking at the future of AI, we have invested in our cloud infrastructure – CloudInfinit⁺ᴬᴵ capable to deliver high-performance GPU-as-a-Service, optimized for demanding AI workloads supporting deep learning, machine learning, model training, and high-performance analytics with unmatched scalability.” Delivering end-to-end capabilities Notably, Sify’s platform and full cloud portfolio – from assessment, advisory, migration services to multi-cloud environment and management – is enhanced by equally impressive offerings that encompass everything from cloud, network infrastructure, data centers and security solutions. These include 14, high-performance, data centers – each equipped with advanced AI/ML capabilities to deliver 100% uptime and ten layers of security for added resiliency. “Our holistic approach at Sify ensures that our customers have a trusted partner who will support them through their entire digital transformation journey,” says Jitender “That means providing the peace of mind to our customers that their needs will be addressed entirely and at all points in the future.” For more information on Sify Technologies visit here. Look to CIO.com for stories about the industry-leading providers in the Broadcom Advantage Program and insights on how they are helping enterprises succeed in their private, hybrid, and multi-cloud endeavors. source

You might lose signals in data as trends change, too. When contact numbers for customers shifted from landline to mobile phones, organizations lost the ability to extract the customer location from the number. “If you were using area codes to validate locality, you lost a lot of records,” Kashalikar adds. Two companies you work with might also merge, so deciding whether to treat them as the same entity or keep them separate in your golden master record of companies depends on the use case. Even without major changes, the underlying data itself might have drifted. “The relationships between the outcome variables of interest and your features may have changed,” Friedman says. “You can’t simply lock in and say, ‘This dataset is absolutely perfect’ and lift it off the shelf to use for a problem a year from now.” To avoid all these problems, you need to involve people with the expertise to differentiate between genuine errors and meaningful signals, document the decisions you make about data cleaning and the reasons for them, and regularly review the impact of data cleaning on both model performance and business outcomes. Rather than doing masses of data cleaning up front and only then starting development, take an iterative approach with incremental data cleaning and quick experiments. “What we’ve seen to be successful is onboard data incrementally,” says Yahav. “There’s a huge temptation to say let’s connect everything and trust that it works. But then when it hits you, you don’t know what’s broken, and then you have to start disconnecting things.” So start with small amounts of recent data, or data you trust, see how that works, and build more sources or volume of data from there and see where it breaks. “It’s going to eventually break because something you forgot is going to reach the main pipeline, and something’s going to surprise you,” he says. “You want this process to be gradual enough for you to understand what caused that.” source

As the United Arab Emirates celebrates its 53rd National Day, it reflects on an extraordinary journey of transformation. Over the last few years, the UAE has rapidly positioned itself as a global hub for technology and innovation, with a strong focus on artificial intelligence (AI), cybersecurity, and digital infrastructure. The country’s vision is not just to keep pace with technological advancements but to lead the way in shaping the future. Sheikh Hamdan bin Mohammed bin Rashid Al Maktoum, Crown Prince of Dubai and Chairman of The Executive Council of Dubai, has consistently emphasized Dubai’s ambition to be a global leader in digital transformation. “Dubai and the UAE are committed to being at the forefront of global digital transformation and become an international centre of excellence for future industries,” Sheikh Hamdan noted. This vision is backed by robust infrastructure, a growth-friendly environment, and an open-door policy to attract top global technology firms. Dubai, in particular, has become a magnet for entrepreneurs, tech giants, and industry leaders from across the world, eager to collaborate and build cutting-edge solutions. In line with this vision, Dubai has also set ambitious goals for the integration of AI across all sectors, aiming to position itself as one of the top three global digital cities. Under the leadership of H.H. Sheikh Mohammed bin Rashid Al Maktoum, Dubai has launched initiatives such as the Dubai 10X Program and Smart Dubai, which are designed to accelerate the adoption of AI technologies across government and business sectors. These forward-thinking programs focus on leveraging AI to enhance public services, streamline government operations, and foster innovation within the private sector. source

As digitisation gathers pace, manufacturers, energy companies, and transportation businesses are among the sectors increasingly turning to private 5G to connect their operational technology (OT) environments.  With its ultra-low latency and reliable coverage, 5G enables more seamless and reliable connectivity than Wi-Fi. Additionally, 5G promises to accelerate IT-OT convergence and thereby help improve efficiency, enhance decision making, and drive new revenue streams.   Yet with this progress comes new opportunities for hackers. OT can be at the heart of critical infrastructure, meaning disruption could cause major problems and even endanger people. The threat is widespread. According to research by Palo Alto, three-quarters of industrial organisations globally have detected malicious cyber activity in their OT environments.i  The cybersecurity dividend  However, cybersecurity is also viewed as a key driver for the uptake of 5G. With 5G, the OT network is encrypted end-to-end, which enables completely secure communication between devices and systems.   The technology also facilitates network slicing, which allows organisations to create wireless virtual networks for specific applications or departments. Businesses can thereby isolate data and reduce the risk of security breaches in the wireless domain, mirroring what they can do today in the wired domain.   These security benefits are important for two reasons. First, given the high costs and significant brand damage associated with operational disruption, organisations cannot afford unplanned downtime to their OT systems. Second, enterprises must increasingly be on their guard against the threat of industrial espionage and data leakage.    Andre Ferreira, Director of Enterprise 5G Customer Solutions at NTT DATA, explains: “Increasing IT-OT convergence exposes OT networks to a broader range of external threats. More than ever, businesses are concerned that threat actors could place malware on their OT networks and syphon valuable data over an extended period. Network visibility is therefore critical.”  The network visibility challenge  Paradoxically, it’s the high levels of security enabled by 5G networks that makes it difficult for businesses to achieve the visibility required.   End-to-end encryption means that it’s not possible to use network probes, so private 5G effectively blinds security teams using traditional techniques to what devices are connected to the network and how they are communicating.   Owing to this lack of visibility, individual devices cannot easily be identified and profiled, meaning that security teams are unable to apply device profiles or traffic management policies.   Consequently, since networked devices are unknown and traffic cannot be monitored, security teams are unable to apply threat detection or automated remediation, potentially leaving them exposed to data exfiltration.  Shining a light on the OT network  NTT DATA has teamed up with Palo Alto Networks (PAN) to solve this challenge. The companies’ “P5G + Cybersecurity Bundle” embeds a next-generation firewall (NGFW) from Palo Alto into the Private 5G network to deliver inline visibility.    The NGFW draws on unencrypted data from the network, the 5G core, and the 5G management platform and enables manufacturers to identify devices, profile traffic flows, and quickly identify suspicious communications.   Ferreira explains: “By integrating Palo Alto’s industry-leading firewalls into the private 5G OT network, manufacturers can continue to benefit from the protection provided by end-to-end encryption while simultaneously unlocking the visibility needed to monitor for potential data exfiltration, apply device-level policies, and enable automated threat detection and remediation.”  NTT DATA believes that this approach to gaining visibility into 5G private networks is crucial for any business with an OT network and includes the solution as standard in all new private 5G deployments.   Ferreira concludes: “5G is already a highly secure solution for OT and IT networks. Now, with Palo Alto, we are making the technology even more secure, so organisations can connect their OT systems and accelerate IT-OT convergence with complete confidence.”  Learn more about the NTT and PAN partnership.   source

Gone are the days when companies used a single database and had a straightforward cost structure, including hardware and software costs and number of users. Today’s cost equation is far more complicated, with IT leaders facing Albert Einstein levels of mathematics to unravel their cost picture, topped off by large, convoluted maintenance fees. How did IT leaders find themselves here? When you look at the cost equation, it’s not simply one reason. A host of factors are contributing to the hike in costs and blurring the picture. They include: Multiple databases. Today companies are likely to have multiple databases that serve different functions or applications, and house different data. Expansion of license types. These different databases have varying licensing mechanisms, including traditional, cloud, full open source, and commercial open source. Additionally, dealing with multiple vendors, support structures, integrations, performance tuning, and more can directly and indirectly increase operational costs. Complex licensing structures. Many database vendors tout a flexible licensing structure. In practice, that can mean multiple tiers of support, varying pricing models with product complexity and deployment size factoring in. Use cases can be complex, with no two contracts alike. Increasing use of the cloud.  Use of the cloud is growing sharply. In just the second quarter of 2024, enterprise spending on cloud infrastructure rose by $14.1 billion to $79.1 billion, an increase of 22 percent compared with a year ago.[1] Between storage, compute, and data transfer costs, plus backups and snapshots, use of the cloud can drive up database costs if not properly managed. Rising support and maintenance costs. Support from the likes of Oracle has never been cheap. Its support fees sit around 22% of original licensing agreements, on top of an 8% inflationary annual rate (IAR) for software support, enacted beginning December 2022. [2] IT teams can quickly find themselves dealing with ever-rising support costs, all of which are spelled out in rigid contracts that carry penalties for non-compliance – yet another financial risk. “The reality is it’s a convoluted cost picture where enterprise IT teams are swimming in support and maintenance costs,” says Robert Freeman, Rimini Street’s Oracle Enterprise Architect.“ Many are paying more than they are even aware of, while Oracle takes in a 90 percent profit margin on maintenance. It’s time to evaluate whether the cost and benefits are there, what to do about it, and how to take control of the cost picture.” The third-party support alternative There is a proven solution to the challenge, offered through third parties like Rimini Street. With third-party support services, enterprises can consolidate support contracts, avoid complex structures and inflationary price hikes, saving money that can be invested in innovation. Rimini Street provides comprehensive support and services to extend the useful life of existing, stable enterprise software applications, including databases, at half the price of the vendor. This allows organizations to focus their IT resources on innovation and transformation investments instead of support contracts. For renewable energy leader Doosan Enerbility, the savings unlocked by switching from vendor support to Rimini Street for its Oracle Database allowed for the funding of innovations such as robotics process automation (RPA) and other new technologies to help support the company’s mission to bring forth eco-friendly energy alternatives to consumers. With its recently announced expansion of support offerings, Rimini Street’s third-party support coverage extends from mature Oracle database instances to open source offerings and more than 100 other enterprise software products. As vendor prices continue to complicate the database cost picture and take larger bites of the IT budget, companies have a greater responsibility to explore what options they have for IT support and services beyond the vendor, protecting the profitability of the business and the resources needed to compete and grow. To learn more about how Rimini Street can help businesses decrease costs while increasing coverage, go here. [1] The Register, “Enterprise spend on cloud up sharply as world biz splashes $80B in Q2,” August 5, 2024, https://www.theregister.com/2024/08/05/cloud_market_grows_22_percent/ [2] The Register, “Oracle to hike support fees in line with inflation,” July 25, 2022, https://www.theregister.com/2022/07/25/oracle_set_to_impose_inflationary/   source