Zoom Video Communications, Inc., a leading enterprise video communications platform, experienced significant growth during the first months of the COVID-19 pandemic. This rapid expansion required a scalable and secure identity solution that would also provide a seamless user experience. Zoom's legacy identity management environment was not equipped to scale easily with the public cloud or to the hundreds of thousands of systems in use. The company needed a solution that could handle the immense growth while maintaining security and compliance standards. The challenge was to find a solution that could secure server access, alleviate the pressure on Zoom's data center operations team, and provide a seamless user experience to the millions of customers who rely on Zoom for work, education, and personal use.

Betsson Group, a global leader in customer experience in the gaming industry, was motivated by a vision to provide the best customer experience in the industry. With over 600,000 active customers and a reputation for award-winning customer service, the company wanted to stay ahead of customer expectations by introducing an automated self-service solution. The goal was to extend support hours to 24/7 and introduce personalized support available in every customer language. The challenge was to strengthen its award-winning customer experience through digital transformation without hindering the customer experience.

Digicel, a leading mobile network and home entertainment provider in the Caribbean, Latin America, and South Pacific regions, was facing a significant challenge in maintaining a positive customer experience as they scaled. The company was dealing with 800,000 live chat interactions and approximately 5.5 million phone interactions per year, with 90% of brand interactions happening via voice. This model was not sustainable for their efficiency goals, especially as digital interactions became more commonplace in their customers' lives. Digicel had disparate regional call centres with different skill sets, making it difficult to provide a consistent customer experience. The company needed a solution that would not only be easy to adopt internally but also by the customers, supporting the 5 local languages and the nuanced local requirements of the 30+ regional markets they were serving.

Grab, a super-app company, was facing a significant challenge in managing the high volume of digital brand interactions. The customer service agents were unable to address the requests in a timely manner, leading to a backlog. The company needed a cost-effective solution to address customers' questions as quickly as possible and maintain customer satisfaction. The challenge was to build and launch a scalable automated experience on Facebook Messenger that could handle the high volume of customer interactions.

Dianthus, a leader in scaling Direct-to-Consumer (D2C) brands, faced a significant challenge in the creation of unique visual marketing assets for ecommerce product marketing. The process was cumbersome and manual, making it difficult to generate assets suitable for social sharing. The proposed solution was to develop a sophisticated AI computer-vision system capable of generating unique photographs, including computer-generated human or animal models against naturalistic backgrounds, that also incorporated the D2C product. However, creating believable AI-generated product shots with digital influencers required a unique machine learning and data pipeline that incorporated multiple processes such as background generation, identity generation, 3D rendering, human positioning, product positioning, and harmonization of all elements. The pipeline also needed to allow for results to progress through various stages of refinement to deliver a finished photo result that was attractive and natural-looking enough to share on social media.

Blue Bottle Coffee (BBC), a global coffee roaster and retailer, faced a significant challenge in managing the supply of pastries across its international network of cafes. The company was using a manual ordering system, where cafe leaders estimated the required quantity of pastries based on historical sales data, current inventory, and growth projections. This system was effective when BBC had a few cafes, but with over 70 cafes worldwide, it became inefficient and inaccurate. The inaccuracies led to either under-ordering, causing sell-outs and customer dissatisfaction, or over-ordering, resulting in food waste and profit loss. The suboptimal utilization of pastries was also affecting BBC's bottom line. Therefore, BBC needed a scalable, precise, and predictive ordering solution to improve pastry ordering accuracy, reduce food waste, and meet its sustainability goals.

Appen, a leading provider of high-quality training data for AI systems, was facing a significant challenge in scaling its fraud detection mechanism. The company was using a partially automated but mostly manual system to detect and prevent malicious activity on their platform. This system, which relied on SQL and Python scripts, was not efficient enough to handle the increasing volume of work. Appen was struggling to monitor more than 50 jobs per day manually and considered hiring 20+ data analysts to keep up with the platform’s growth. The company needed a solution that would allow them to scale their fraud detection, increase the efficiency of their crowd workers, and attract new enterprise clients. The existing system also posed a challenge in terms of data quality, as it was prone to human error and could not efficiently eliminate low-quality contributions.

The Customer, a pioneer in Autonomous Systems, was faced with the challenge of migrating its computer vision cloud platform to the Amazon cloud within a four-month timeframe. The migration was necessary to enable the platform to perform highly scalable, real-time weapon detection to identify firearms and suspects in high-security environments. The goal was to provide security and safety to essential businesses, communities, and schools through real-time human behavior recognition and weapon detection technologies, enabled by AI & Machine Learning. The Customer was also looking to protect communities by bringing AI-driven visual imaging and human behavior recognition technology to every school, public building, and business across the country. They wanted to develop a weapon detection solution that they could integrate with their apps in the AWS cloud, to be able to deter, detect, and defend against shooters quickly and efficiently.

MARS Incorporated, a multinational manufacturer, faced significant challenges in digitizing and standardizing processes across its mid-markets globally. The company's reliance on legacy solutions necessitated continuous, time-consuming upgrades and made data compilation and comparison across different regions and business units difficult. Excel spreadsheets were extensively used for forecasting in smaller markets, leading to disconnected processes, siloed working environments, and increased risk of data inconsistencies and inaccuracies in demand forecasting. MARS also struggled with a lack of visibility across its midmarket footprint, scattered critical data across various systems and spreadsheets, a low degree of automation, and insufficient statistical analytics for demand planning. The absence of a standard process for demand planning made it challenging to consolidate KPIs and gain a comprehensive view of demand trends and supply chain performance.

Antic Screen Printing, based in Austin, Texas, is a company that prioritizes customer experience. To ensure a smooth experience for their customers, they needed to streamline their own internal workflows. The challenge they faced was the manual and time-consuming process of transferring leads from their website and quoting forms into their marketing funnels. This process was not only tedious but also prone to errors and inconsistencies. The company was in need of a solution that could automate this process, thereby saving time and ensuring consistency.

Icebreaker, a clothing brand that uses merino wool from New Zealand, faced a significant challenge in managing and deciphering thousands of customer feedback forms. The company used Wufoo, a tool for creating customized forms, to collect feedback from customers about their shopping experience. However, the process of extracting, formatting, filtering, organizing, and sometimes translating the information from these forms was time-consuming and inefficient. As a result, the customer's voice was only being heard about once a month. The team needed a way to automate this process to ensure that customer feedback was promptly and efficiently addressed.

Brand24, a popular social listening platform, was facing a significant challenge with its conversion rates. The company's CEO, Mike Sadowski, noticed that the conversion rates were considerably lower than the industry standard. The primary issue was a high bounce rate on the sign-up form for Brand24’s free trial. The bounce rate was much larger than anticipated, indicating a leaky funnel. Two main culprits were identified as causing the high bounce rate. Firstly, a promo code field was confusing users, leading to a high abandonment rate. Secondly, the sign-up form had too many distractions, causing users to click around chaotically, visiting the blog, looking into pricing again, and hovering over links.

Trident Trust, a global leader in fund administration, faced significant challenges when it first ventured into the crypto space in 2017. The company had to collect its clients' crypto transactional data through mechanisms that were often cumbersome and unsustainable, such as manual input, files, and screenshots. Once the data was collected, Trident used spreadsheets to apply price and derive the trading activity value. This process was not only laborious but also required Trident to manually transform the data into a format that was easily consumable by traditional fund accounting systems. The lack of automation and the need for manual intervention made the process inefficient and prone to errors.

The case study revolves around an independent global asset management firm with prestigious corporate investors and banking partners. The firm is responsible for managing assets for a wide range of clients and is acutely aware of its responsibility to protect all related information. The firm had antivirus software and firewalls in place, which provided an essential first line of defense. However, if hackers or malware were to penetrate these barriers, it had no means of monitoring its IT infrastructure to detect unauthorized activity on its network. The firm also needed to ensure that there were no weaknesses in its own network that might be exploited by hackers as a means of infiltrating the networks of its many financial partners. The firm was comfortable that it complied with the IT security standards set out by the Financial Conduct Authority (FCA) in the UK, and other similar regulatory bodies around the world, but it anticipated that these industry requirements would soon become more stringent.

The Hamburg Port Authority (HPA), responsible for managing all harbor-related infrastructure for the city of Hamburg, faced significant challenges in securing its vast IT infrastructure. This infrastructure included 350 kilometers of fiber cable, 850 routers and switches, 500 servers in two data centers, and thousands of computers and smartphones running over 600 applications across 63 separate locations. The HPA IT managers identified several security challenges, including over 100 local administrators managing applications without support or follow-up, applications without a designated owner responsible for security or lifecycle management, and a flat network structure focused more on performance and flexibility than security. Additionally, HPA workers were not optimally aware of best security practices, leading to concerns about unidentified network exposures.

EDEKA Northern Bavaria-Saxony-Thuringia, a regional group of the EDEKA network, was facing challenges with its legacy planning systems. The company, which supplies around 900 retail stores, was dealing with increasing data volumes and growing requirements that its existing systems could not handle. The company's Excel-based planning processes were also proving to be inadequate, with employees spending more time preparing the data than analyzing the information it contained. The company's legacy planning system was unable to handle demands such as displaying tour utilization or logistics packing densities, and performance was no longer sufficient for smooth operation. The company was also facing issues with data loading times, which could take up to 24 hours for larger amounts of data from SAP. These challenges led the company to seek a new, more powerful solution for planning, reporting, and analysis.

Anorbank, the first fully digital bank in Uzbekistan, faced the challenge of implementing a comprehensive digital banking system during the pandemic. The bank needed to provide services without requiring customers to visit physical offices, aligning with the modern lifestyle of increased mobility and preference for digital technologies. The bank's strategy required a unique platform that could process requests quickly while maintaining an individual approach to each client and guaranteeing data security. The bank's team, 70% of which consisted of IT employees, was tasked with the continuous development of this platform. The challenge was not just to describe procedures in Word documents, but to create complete digital processes. This required integration with various IT systems, making the project complex due to the number of users, different groups of bank users, and the large number of required integrations.

Keller Williams, the world's largest real estate technology franchise, was driven by a desire to foster meaningful relationships and provide a seamless user experience for agents and customers. They wanted to create a platform that would allow agents and customers to navigate the real estate market with ease. However, they faced the challenge of finding a solution that was highly flexible and customizable, as opposed to a Software as a Service (SaaS) suite that did not allow for customization. The company needed a solution that would enable them to manage contacts, marketing profiles, campaigns, and listings effectively.

Israel is currently undergoing the largest infrastructure development in its history, with projects ranging from lite-trains and underground trains to cross-country highways and heavy railways. However, coordinating these large-scale projects in a small country like Israel, where resources are limited, is a significant challenge. Each project requires multiple approvals from various entities, including the Israel Water Company, the Israel Electric Corporation, and several federal bodies. This process was previously handled manually, leading to inefficient paperwork, misunderstandings, and delays in the coordination process, which in turn delayed project delivery. The Israeli government recognized the need for a more efficient system to manage the coordination of these infrastructure projects.

Lumen, an automotive manufacturer, was grappling with several operational challenges. The company was heavily reliant on manual processes, with the exception of their purchase order requests. They were also struggling with a hard-to-use legacy system, which was so cumbersome that they had only managed to launch one form in three years. Additionally, their data was dispersed across various locations, making it difficult for stakeholders to access and analyze it in a consolidated manner. Lumen also desired to connect applications and kick off sub-processes using information gained from other processes, a capability their existing system did not offer.

The British Broadcasting Corporation (BBC) faced several challenges with its legacy systems. For the BBC iPlayer, the legacy system was slowing productivity, innovation, and content delivery. The growing content required massive scalability and faster response times. For the BBC Sport website, the challenges were the integration of diverse data, such as statistics and videos, rapid application development to meet game deadlines, scalability to support tens of thousands of transactions per second, and the utilization of open standards for mobile delivery. The BBC needed to upgrade the iPlayer to support a growing user base, deliver content that could be viewed on multiple devices, and personalize that content. The BBC also wanted to deliver real-time, customizable, and interactive online content for the Summer Olympics.

Kittitas Valley Healthcare (KVH), a small regional rural health system in Washington State, was grappling with the challenge of excessive administrative burdens on its clinicians. Studies have shown that clinicians in medium-sized hospitals spend about 44% of their time on documentation and only 24% on direct patient contact. This was largely due to the Medicare Physician Fee Schedule (MPFS), which required clinicians to document a wide range of data for billing verification. This system turned clinicians into data-entry clerks, documenting not only diagnoses, clinician orders, and patient visit notes, but also an increasing amount of low-value administrative data. KVH was using scribes to assist providers with documentation and data entry into the Electronic Medical Records (EMR). However, due to its rural location, KVH was struggling to recruit and retain high-performing scribes. The training for these scribes could take six to eight months and was not very effective in reducing high scribe turnover rates.

Qrypt Inc., a leading data-security company, was facing a challenge in managing an increasing number of high-value assets such as desktop computers, laptops, printers, televisions, electronics testing equipment, portable media devices, and phones. With the company's growth, the need for a more efficient and accurate inventory tracking system became essential. The company was also looking to eliminate the use of outdated manual spreadsheets for inventory management. The challenge was to find a solution that could effectively manage all their assets and efficiently track inventory.

The Covid-19 pandemic has acted as a catalyst for the FinTech sector, accelerating investments and technological progress. However, data and technology remain significant challenges, hindering further progress for FinTechs and their partnering traditional financial institutions. Among FinTechs globally, 81 percent have reported data to be their biggest technical challenge. These data issues are split between leveraging data for AI-ML (faced by 41 percent) and connecting to customer applications and data systems (faced by 40 percent). Other data issues faced by FinTechs include security (40 percent) and deployment in multiple clouds (39 percent). The consequences of these data issues include trouble innovating further due to a lack of clear picture about the type of products and services that customers require and about the businesses themselves. The inability to connect to customer applications directly impacts the user experience and the ability to offer their present products to the wider customer base. These issues also hinder securing partnerships with incumbent banks, and more seriously, regulatory compliance.

Enpro Inc.'s customers, primarily beverage companies, rely on automated, high-speed filling lines that produce up to 2,500 items per minute per line. A key component of these lines is the vent tube, which is used to fill cans and bottles and vent out the carbonation-related gas. However, due to wear and tear, these vent tubes can occasionally fall off and into the cans and bottles, leading to safety and quality issues. The loss or damage of a vent tube during the filling process can result in large amounts of finished packaged product being discarded, as locating the missing vent tube is a costly and time-consuming process. Therefore, Enpro Inc.'s customers needed a reliable way to detect the presence or absence of a vent tube, eliminating the need for manual checks and potential line halts.

The Angolan government agency was seeking to upgrade its voter ID system ahead of the elections in Q3 2017. The aim was to increase the number of citizens eligible to vote by issuing voter IDs in a short time frame. The existing voter ID printing system needed to be replaced with a solution that reduced costs significantly by providing mobility and streamlining operational processes. The key selection criteria included a faster throughput secure issuance printer solution, a de-centralized secure issuance solution to increase the number of citizens enrolled, a Wi-Fi based secure issuance printing solution for increased convenience, improved reliability of the printing solution, a lightweight, easy-to-use portable solution for collecting citizens’ data and issuing voter IDs for citizens residing in remote areas, and high levels of security to combat fraud and minimize the number of counterfeit voter IDs.

Raiffeisen Bank Aval, one of the top five commercial banks in Ukraine, faced a significant challenge in modernizing their private cloud infrastructure. The bank was struggling with validating hardware requirements against purchase recommendations made by the hardware vendor. This resulted in an expected additional 33% in hardware costs for the transformation project. The existing cloud environment had a VM-to-host ratio of 24:1, and it consisted of 38 VMware hosts and 923 virtual machines. The bank needed a solution that would help them avoid these additional expenses and ensure that their private cloud resources were perfectly aligned to workload demand patterns and business cycles.

Xenit, a renowned IT services provider based in Sweden, assists companies in executing their digital transformation initiatives, with a primary focus on modernizing application deployment and delivery infrastructure. However, the Xenit DevOps team faced challenges in application delivery at scale. The team was manually configuring the application delivery infrastructure, which was not only time-consuming but also prone to errors. They had to constantly balance between scaling up to ensure enough capacity for estimated demand and scaling down when demand decreased. The tools they were using were not always delivering as promised, leading to inefficiencies. Xenit needed an automated and consistent way to provide services to its customers and to scale its own service deployment and delivery.

Challenges as follows:Struggled to determine: which tax (CGST/SGST/IGST) and how much tax was applicable on goods for import & export; tax based on Point of Supply (POS) mapping; certain businesses that are exempted under GST lawFaced issues of duplication of invoicesIdentified risks related to the unavailability of the mandatory data as per GSTN format

Transition Technologies, a Poland-based provider of advanced solutions for the energy, gas, industry 4.0, and bioinformatics markets, faced a significant challenge when a customer requested to use their flagship product, LUXtrade, in the cloud. The company had been implementing LUXtrade on-premises in Europe for almost 20 years and had recently started delivering it as software-as-a-service. However, the request for a cloud-based solution required Transition Technologies to deploy a cloud solution in just six months. This was a daunting task given the complex nature of LUXtrade, which includes features for RES management, algo-trading, forecasting, and data analytics. The company was confident in its ability to meet these targets with Oracle technology, but the short timeline for cloud deployment presented a significant challenge.