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Audience Audit, a company that provides unique research to agencies, wanted to make its services more accessible to a wider range of clients. This required lowering the cost of its projects and delivering results more quickly without compromising the quality of the research. The company's projects involved designing and delivering targeted online surveys, performing statistical analysis of the data, and creating customer-facing presentations to communicate the findings. This process was time-intensive and manual, and any changes to the data required updating everything individually. Furthermore, the owner of Audience Audit, Susan Baier, had to work through the data herself to parse out key insights and share its story with her clients. The challenge was to find a way to make the work more accessible to agency clients, which would require major changes.

FINN.no, Norway's largest online marketplace, was struggling with a fragmented assortment of business intelligence (BI) tools, including spreadsheets. These tools provided a narrow view of intelligence into advertising sales, unique users, and other metrics, but couldn't provide a holistic view of the business. Reporting was primarily an IT department affair: business users would request reports and wait sometimes days for the results to arrive. The company needed a solution that would allow for ad hoc reports, standard, drill-through reporting on KPIs, and self-service reporting for their customers.

The French Red Cross, with its 54,000 volunteers and 18,112 employees, provides a range of services across more than 1870 locations in the country. However, the organization faced a significant challenge in terms of data analysis. They had no means of easily analyzing or making sense of all the data arriving in the organization. The focus had been on transactions and support, but the emphasis shifted to data analysis, leading to the launch of a new business intelligence architecture. The new model comprised a decision support system, data integration, and reporting. The organization needed an intuitive, user-friendly business intelligence tool that enables dynamic performance and results in real time.

Swedish Medical Center (Swedish) was facing challenges in understanding and communicating physician and hospital performance across various areas. Traditional reporting solutions were proving to be cumbersome to implement and expensive to maintain. The healthcare provider was looking for a way to drive improvements in quality care, improve patient experiences, and enjoy substantial savings through process improvements and improved efficiencies. The organization was also preparing for value-based reimbursement and wanted to improve other areas like operating room efficiency, physician engagement, and financial performance.

Pandora, the leading internet radio service, wanted to increase its use of data to drive business decisions. However, the company’s many silos of data storage created barriers. Only a few people knew how to write scripts to query the data, which meant most people couldn’t get the information they needed to make better decisions. Pandora had dozens of data analysts on staff, but their time was being used running reports instead of providing higher-value analysis. Pandora’s dramatic growth made enabling data-driven decision making a high-priority project.

Lucky Voice, a leading U.K. provider of karaoke services, was facing challenges with its outmoded booking system for reporting. The company was in need of a solution that could introduce live reporting on karaoke bars performance throughout the business. The developers were spending a significant amount of time on report generation, which was slowing down the company's progress. The company was looking for a solution that could provide real-time, detailed reporting to meet the increased demand due to the company's growth.

China Eastern Airlines, the second-largest carrier in China and the ninth-largest worldwide, was struggling with data analysis. The airline had a vast amount of data to share with management, sales, pricing, and other departments. However, the existing system, an Oracle database and IE browser, was slow and made it difficult to utilize the data effectively. The airline needed a tool that was not only easy for IT to use but also for business people.

HomeRepair, a company that repairs residential property damage claims on behalf of one of Australia’s largest general insurers, was facing increasing competition. The company needed to understand its performance metrics quickly to retain and build its market position. HomeRepair had the majority of its data stored in GClaim, a web-based repair administration and management solution. However, the company could not use that information in a timely manner due to the lack of an in-house IT department. HomeRepair management relied on IT vendors to run queries and reports from the SQL database, a process that was too slow for the company's needs. HomeRepair management was able to pull some data out of the SQL database and into Excel pivot tables, but the resulting reports were not very helpful. To truly understand productivity and cost-effectiveness, HomeRepair would need to look at data stored in other sources in concert with its GClaim data.

Stardoll, a Swedish online community for girls who love fashion, faced a significant challenge with data management as its user base grew. The company had a wealth of data about its users, their preferences, and their behaviors, but extracting meaningful insights from this data was a slow and labor-intensive process. Traditional reporting methods, such as spreadsheets or HTML tables, took up to three days to produce and were often outdated by the time they reached the decision-makers. This delay in data reporting hindered the company's ability to make accurate and timely decisions, adapt its services, target new audiences, and increase revenues.

Unilever’s IT team faced numerous challenges, due to their infrastructure size, which encompasses 1,000 applications, 10,000 interfaces, and 500 IT projects per year. Unilever had multiple global teams and was looking to find more efficient solutions to deploy new products and services.

HSBC, one of the world's largest banks, was facing the challenge of technological disruption in the financial services space. This disruption brought new regulations, higher customer expectations, and increased competition. To stay ahead, HSBC needed to become the disruptor, which required the use of APIs to securely unlock data from thousands of applications and make core banking services available to internal and third-party developers. The bank aimed to improve the customer experience and open new revenue channels by launching an API developer portal, increasing customer loyalty, and partnering with third-party platforms to deliver new HSBC products and services.

BP, one of the largest energy companies in the world, is facing the dual challenge of meeting the increasing global demand for energy while reducing emissions. The key to achieving these goals is to leverage digital solutions, big data, and advanced technologies. The BP IT&S team is tasked with accelerating the pace of technology delivery, securing data access, and reducing dependencies on costly and time-consuming legacy systems. The team needed to modernize legacy systems to speed up access to applications and data, shift the role of IT from simply delivering technology solutions to enabling the business to take advantage of digital technology, and develop a Center for Enablement (C4E) to drive the adoption of BP’s API strategy.

Legal & General (L&G) is the United Kingdom’s largest provider of individual life assurance products and a top 20 global asset manager. The insurance industry has changed dramatically with increasing pressure to reduce costs and engage customers through digital channels. To remain competitive, L&G’s insurance arm, General Insurance (GI), has a goal to become a market leader in providing digital access to insurance. However, developing digital experiences for customers and advisers requires connectivity between various systems, surfacing claims, policy, billing, and other data in a quick and scalable manner. But behind the scenes, the company’s IT systems were connected via point-to-point integrations, which exacerbated operational inefficiencies and forced teams to reinvent the wheel each time they needed to develop a digital experience or release a new product or service.

Australian workers' compensation insurance company, icare, protects 3.6 million people across 326,000 businesses and 193 government agencies. The company needed to improve its customer experience by delivering a digital, machine learning-driven system that makes submitting and processing claims quick and easy. However, icare's customer data were siloed in SaaS and legacy systems, creating a disjointed, slow process in which customers had to fill out paperwork and visit multiple websites to submit claims, choose a policy, and more.

Tic:Toc, an Australian fintech company, was launched with the aim of transforming the traditional home loan process. The company wanted to eliminate the inefficiencies in the home loan approval and fulfillment process, allowing customers to easily submit loan applications online and receive instant decisions. However, the challenge lay in the complexity of the traditional process. For instance, validating a property purchased via a home loan involved multiple steps and parties, making it a time-consuming process. To provide customers with a seamless, instant home loan application experience, Tic:Toc needed to integrate data from various sources, offer real-time document generation and home loan decisions, and deliver their new product to market quickly to gain a competitive advantage.

New South Wales Health Pathology (NSWHP) is an Australian statewide health organization that provides services to various local government bodies. The organization operates more than 60 laboratories, 150 pathology collection services, and conducts over 100,000 clinical tests per day. However, NSWHP's IT systems were siloed, making it difficult to deliver on key initiatives that would improve patient outcomes, maximize taxpayer benefits, and build a foundation for change. The organization sought to efficiently integrate data to deliver time-critical initiatives, including digitizing pathology results to speed up access to patient data and make clinical decisions faster, reducing cost and effort associated with transportation and testing, and building a foundation to rapidly respond to change and emerging, urgent demands, including COVID-19.

The Indiana Department of Child Services (INDCS) manages over a quarter million child cases per year, requiring the collaboration of over 4,000 staff members. The department needed to digitize its processes to scale with the case volume, streamline staff member collaboration, and improve the entire child services journey. The objectives were to modernize legacy systems, implement a national electronic system to exchange case data with courts, families, and other state agencies, create a single view of the over 20,000 children in its care, and ensure caseworker and child health safety by creating a comprehensive view of health data in response to COVID-19.

RBC Wealth Management, a division of RBC Capital Markets, was facing challenges in delivering a world-class customer experience. The company, which has over $379 billion in total client assets and more than 2,000 financial advisors operating in 179 locations across 42 states in the US, needed to further embrace digital to remain competitive. However, achieving these goals proved difficult as RBC needed to unlock critical customer and financial data in siloed legacy systems and integrate that data with modern cloud and on-premises applications across the organization for a single customer view. The company's objectives included automating and connecting siloed legacy systems to digitize paper-based onboarding processes, building a single customer view and improving financial advisor productivity by integrating legacy data with cloud and on-premise systems, and launching a client service portal that streamlines the customer experience.

Revolution Beauty, one of the fastest-growing beauty brands in the UK, was facing challenges with its eCommerce platform. The website could not keep up with the brand’s pace of continuous innovation and new product releases. It was difficult and time-consuming to update and add pricing, images, product descriptions, and other critical information. To maintain market leadership, Revolution Beauty also needed to integrate its eCommerce platform with on-premises applications for a single customer view — enabling customer service reps to resolve inquiries faster and deliver a seamless customer experience.

AXA Luxembourg, part of the AXA Group, aimed to become the #1 preferred insurance company by embracing digital transformation to outpace competition and better serve their policyholders. However, the company faced challenges in leveraging their data due to the need to connect different homemade systems on-premises and external systems in the cloud. The custom-coded integrations made it costly and slow to connect systems, apps, and data. The company aimed to reduce operational costs, eliminate manual labor by automating key business processes such as claims management, create a single customer view of policyholders to resolve their queries faster, and build an architectural foundation that enables the team to launch future customer innovations more quickly through reuse.

Ahold Delhaize, a global food retail group, is striving to stay ahead of the competition in the rapidly evolving retail world. The company is implementing an omnichannel strategy, blending the best of brick-and-mortar, delivery, and pick-up. However, to future-proof its business, Ahold Delhaize needed a way to quickly incorporate new technologies and respond to changing consumer demands.

Salesforce, a global leader in CRM, has grown rapidly over the years, acquiring over 70 companies. This growth has resulted in thousands of systems and massive amounts of data. The company had leveraged MuleSoft's Anypoint Platform well before acquiring the company. After the acquisition, Salesforce initiated an effort to adopt API-led connectivity to better integrate systems and data, aiming to provide connected experiences to their 150,000 customers and 49,000 employees. The company wanted to move away from point-to-point connectivity to unlock and integrate critical data across the enterprise, create a single view of their employees, automate manual HR processes, and integrate Salesforce customer accounts with the accounts of acquired companies to build a 360-degree customer view for sales teams.

WatchBox, a leading company for buying, selling, and trading pre-owned luxury watches, wanted to scale its business internationally via eCommerce. The company's success relied on exposing its inventory to as many customers as possible for quick resale. This required creating a powerful eCommerce experience that not only allows for rapid expansion but also pulls critical inventory data from legacy and homegrown systems. The objectives were to create an eCommerce platform that allows for rapid expansion into new regions, unlock and unify data from legacy and homegrown systems, and build standardized eCommerce processes that support quick inventory turnover.

Invesco, a global asset management firm, was facing challenges due to the existence of over 200 siloed IT systems. These systems were preventing business users from quickly accessing valuable customer and market data. The lack of data access was also impeding the development process at Invesco, as teams had little transparency into other team’s work or projects currently in development, leading to inefficient and repetitive processes. Invesco needed to enable data sharing between multiple business units and 1,700 tech employees worldwide.

SMCP Group, a French luxury retailer, aimed to build a single view of the customer across its in-store and online channels to better understand shopping habits, increase touchpoints with customers, and provide a more personalized experience. The company also wanted to deepen relations with wholesalers by allowing real-time data exchange. However, SMCP's aging IT infrastructure, underpinned by legacy systems, made it difficult to unlock critical data, preventing them from building a single view of the customer and sharing data across different functions and with partners. The team was forced to manually batch upload information such as orders to disparate systems of record at regular intervals throughout the day. These manual uploads were not only time-intensive but led to data duplications.

Liberty Holdings, a South Africa-based financial services and insurance group, was facing a challenge due to its outdated and inefficient claims process. The company had its claims, customer, and underwriting data information stored in multiple monolithic back-end systems. This resulted in a suboptimal insurance claims process that required claims processors to manually extract data from seven different systems and enter it into a spreadsheet. They then had to log into several other systems in order to process a claim. The operation was slow, prone to human error, and did not provide the level of support that Liberty’s customers expected. Liberty needed to digitally transform its operations, modernizing legacy systems to streamline the claims process and provide a better customer experience.

The Brain Imaging Data Generation and Education Center (BRIDGE) at Carnegie Mellon University (CMU) and the University of Pittsburgh (Pitt) has been an early adopter of BIDS' (Brain Imaging Data Structure). BIDS is an increasingly adopted standard of data organization that allows researchers to more easily share neuroimaging data and software tools across the broad range of research conducted by users scanning at their facilities. The BRIDGE Center leadership sees this technology for standardizing (i.e. organizing, annotating, and describing) data as an important facilitator for replicable analyses and advancing research collaboration to speed discovery. The need for efficient data practices became more evident when the Center decided to purchase another 3-Tesla MRI system in 2019, a decision that would greatly increase the amount of data acquired at the Center.

The Dana and David Dornsife Cognitive Neuroimaging Center (DNI) at the University of Southern California (USC) was facing challenges in distributing data to researchers across the university community. The data from scans conducted at the center had to be transferred to DVDs and delivered to individual researchers or pushed onto the researcher's own DICOM server. These manual processes often resulted in delays and quality concerns. Additionally, Dr. Jonas Kaplan, Assistant Research Professor of Psychology at USC's Brain and Creativity Institute and Co-Director of the DNI, was seeking a new platform to manage his lab's data. He wanted a solution that would allow him to access and curate his data quickly and accurately, while also providing a secure mechanism for sharing data with collaborators and students.

The Yassa Lab at the University of California, Irvine (UCI), led by Dr. Michael Yassa, was facing several challenges. They were struggling with managing multi-center collaboration involving the collection of large data sets, quality control, analysis, and submission to NIH databases. The growing data and analytic complexity were impeding data reuse and scientific reproducibility. They were also looking for ways to best support and collaborate with other labs in the UC Irvine community. The lab was involved in a multicenter collaboration studying biomarkers of Alzheimer's disease in Down syndrome, which required secure sharing and processing of a variety of data.

Stanford Medicine’s Brain Stimulation Lab is working on solutions for treatment-resistant depression, a condition that affects 5% of adults worldwide. The lab is studying the use of Repetitive Transcranial Magnetic Stimulation (rTMS), a therapy that involves activating or inhibiting the brain directly with electromagnetic fields. The lab's work is growing, and so is their need for smart data management. The lab originally used the Flywheel platform to store raw and reconstructed data and applied its basic tools for reconstruction and quality control. However, when they wanted to perform analysis, researchers were still downloading data to a static lab PC. This process was time-consuming and made it difficult to track data provenance.