Nabtesco, a Japanese manufacturer of industrial robots and hydraulic equipment, was facing intense global competition. The demand for quality, cost, delivery, and service (QCDS) had increased, and Nabtesco needed to innovate its manufacturing processes to stay competitive. The company recognized the need for data-driven decision making to improve its marketing capabilities and anticipate client demands. However, they were not fully utilizing the data they collected as a management resource. Existing databases and spreadsheets were cumbersome and often crashed when handling large amounts of data. Some companies within the group had started using Business Intelligence (BI) tools, but they hadn't fully mastered their capabilities.

Allina Health, a not-for-profit healthcare system, is dedicated to the prevention and treatment of illness and enhancing the health of individuals, families, and communities throughout Minnesota and western Wisconsin. The organization has a comprehensive electronic medical record (EMR) system, Epic, which plays a key role in its success. However, Allina Health is also part of the Center for Medicare & Medicaid (CMS) Innovation’s Pioneer Accountable Care Organization (ACO) model, which requires a strong information infrastructure to manage and visualize the enormous amount of data that will eventually be reported to the government. The goal of this infrastructure is to bring all medical and patient information together, enabling Allina to evaluate its performance, identify areas for improvement, and discover ways for clinicians and care teams to deliver better care to patients.

Pharmaceutical companies are under increasing pressure to stand out from the crowd in an industry facing pricing pressures, promotional saturation, regulatory scrutiny, reduced product differentiation and increased customer and channel complexity. The healthcare market faces the dual paradox of being awash in data but often lacking in insight. Some of these companies are finding the means to pull ahead of the pack through leveraging analytics in broader and dramatically more effective ways. They are creating the organisational capability to develop and execute against differentiated insights. AsteRx was dealing with large data volumes, comprising millions of scripts from a national sample of hundreds of physicians to be analysed in a myriad of ways that would take weeks to manipulate for a single result. Customers were provided with raw research data, usually in Access or CSV format, making it difficult from which to draw insight. Furthermore, data contained lots of hierarchies, continually changing data frequency with varying levels of data aggregation. Multiple data sources also needed to be integrated with different formats, languages and data structures.

Centerstone Research Institute (CRI) faced increasing economic pressure as the global economic crisis affected state and local budgets. Funding cuts were proposed at a time when demand for the services Centerstone provides was rising – a “perfect storm” with serious business and clinical implications. To weather the financial pressures without severely cutting services, CRI sought a Business Intelligence/Data Warehousing (BI/DW) solution that would simultaneously improve the quality of care for patients while reducing revenue leaks. CRI’s strategy behind the BI/DW solution was to empower management and staff with easy access to actionable information related to business and clinical practices.

Children’s Healthcare Services, a leading non-profit organization caring for children in Nebraska, was facing challenges in gaining visibility into its operations to improve the quality of care. The organization was struggling to access, integrate, and analyze data across disparate systems including clinical, financial, and administrative systems. The organization supports a 142-bed facility and roughly 50,000 patients per year, making it crucial to have a streamlined and efficient system for data management and analysis.

Design Within Reach (DWR), a multichannel modern furnishings retailer, was struggling with its data management. The company’s sales and inventory data was often analyzed using Excel, and occasionally with custom built reports using SAP’s Crystal Reports. This led to inconsistencies in data analysis as different people used different processes to create reports. The IT team was also burdened with doing one-off pulls from the company’s databases. DWR needed a solution that was flexible enough to be used by all Area Managers, regardless of location, and easy enough that they could find answers on their own, despite their levels of technical ability.

Healthcare professionals, in both the public and the private sectors, experience problems with the operational display of information in their numerous clinical, financial, and enterprise resource planning systems. The inability to access, collect and process data efficiently often contributes to financial tensions, longer patient waiting times, constraints on resources, and the risk of clinical errors. The Fernando Fonseca Hospital needed to adopt business intelligence (BI) system that would integrate information and permit its speedy processing in a straightforward and flexible way. Another objective was to acquire a tool that would continually map out and control specific activities in each department, both clinical and non-clinical, allowing the monitoring of evaluation factors identified as critical for good practice.

Haworth, a global manufacturer of adaptable workspaces, was facing challenges in maintaining customer satisfaction throughout its supply chain. The company had over 100 gigabytes of data stored in disparate systems, which was continuously growing. This made it difficult for Haworth to quickly mine through the data to identify and resolve delivery issues. The company needed a streamlined approach to quickly identify delivery discrepancies and resolve them. They sought a comprehensive in-memory business intelligence (BI) solution that could provide meaningful business insights.

HDFC Life, a leading private life insurance company in India, was facing several challenges. The company was struggling with the proliferation of data and its existence in silos, which was impacting the senior management’s capability to make informed decisions. Every department had their own method of generating and storing information which lead to proliferation of silos and inadvertently raised the cost and time to accessing accurate information. The company also wanted to reduce response times to customers and improve satisfaction, provide a strategic decision-making model to senior management, and accelerate business growth and improve market standing.

Mercedes-Benz India was facing challenges in empowering its users to access and analyze data in near real-time. The company was struggling with an ineffective reporting process to senior management, which was time-consuming and inefficient. The reports were pre-defined and static, which made it difficult for the company to make informed decisions. The company was using Siebel as its foundation for dealer management system (DMS), but the internal teams were required to extract data from DMS manually to create reports for the central management team. This was a time-consuming and ineffective process. The company needed a robust, flexible CRM/DMS and business intelligence solution as its foundation.

The Office for Computing, Geography and Statistics of the Autonomous Province of Bolzano manages the entire information system and serves 6,000 workstations. Its main client is the Provincial Statistics Institute, which runs provincial statistics analyses. The Office needed to find a user-friendly tool that presents detailed findings and a system that does not require complex technological infrastructures. They also needed to analyze highly complex data combinations efficiently. The Office conducted a study to find the tool that best suits the Provincial Administration’s environment – an agile, customizable tool that would not require complex technological infrastructure and that guarantees good performance.

Sahlgrenska University Hospital faced the challenge of integrating data from Siemens Melior patient journal system with five other hospital systems. The hospital needed to provide medical professionals with faster access to critical information to identify and treat any complications from cranial surgery. The existing system was not efficient in measuring patient flows, groupings, and costs. The information about the patient was spread in different places, making it extremely difficult to get the basic data for decision making fast enough.

Sathya Agencies, a fast-growing electronics retailer with over 33 stores in Tamil Nadu, India, was facing several challenges. The company was experiencing duplication in reporting and delayed response times across departments due to the use of SAP B1 ERP for their operations and the development of numerous custom reports to meet every department’s needs. This led to duplication of information and delayed responses. The company also lacked visibility into excess and non-performing stock at all times, which caused logistic issues. There was also a lack of access to a variety of information required for effective sales campaign executions. Furthermore, the lack of mobile access to information for travelling senior management was a significant challenge.

SEB Group, a North European financial group, was facing challenges in gaining a better understanding of its insurance customers and portfolio. The company wanted to improve cross-selling of products and increase customer share of wallet. Additionally, SEB was looking to improve IT project management within its merchant banking division. The company spans four divisions of merchant banking, retail banking, wealth management, and life insurance for 400,000 corporate customers and institutions, and 5 million private customers. With ~300 billion in assets, SEB achieved ~$6 billion in revenue with 20,000 employees.

Subaru Italia, the official importer of Subaru for Italy, Slovenia, and Croatia, faced several challenges. The company needed to improve sales, dealer and garage management with the flow of vehicle orders. They also needed to manage credits and invoicing processes more efficiently. The company was looking for an easy-to-use business analysis system that could adapt with the company’s growth. Subaru Italia had been using business intelligence software since 1996, but as the company grew and the database evolved, they needed a tool with faster and simpler development capabilities. The company also needed an easy-to-deploy, dynamic and flexible tool to improve the sales area and management of its several dealers and garages.

De Swinhove Groep, a healthcare provider for senior citizens in the Netherlands, was facing major challenges due to the rising costs in the care sector. The Dutch government was promoting homecare and shifting the responsibility for the use of budgets towards care institutions. This meant that care providers like De Swinhove Groep had to minimize building operation costs and optimize Total Cost of Ownership. The group wanted to develop a high-grade information organization and quickly integrate changes in management control information. They needed a business partner that was familiar with complex healthcare processes as well as business intelligence.

Verdecora, a leader in “green” home and garden supplies, was facing challenges in providing improved and streamlined access to information, optimizing management of information, and developing new indicators for tracking. The company's expansion in available sales space translated into an increase in the quantity of products and information generated. One of Verdecora’s main concerns was how it could process and optimally manage all of this information, and, perhaps most importantly, provide agile access to that information – which was strategic for the company. Consequently, they began searching for a tool that would meet these needs, one that would ensure continued growth by correcting anomalies and offering real solutions.

VSE Corporation, a diversified government contractor, was facing challenges in managing the business side of its large-scale projects. The company was struggling with real-time data gathering for current project analysis, which hindered its understanding of the financial status of ongoing projects. This delay in data gathering and analysis led to incorrect invoicing and backlog tracking, causing payment delays from customers. If a project stalled and did not complete on time and on budget, it could have significant consequences for VSE and other government contractors. The company also needed to effectively handle labor utilization and risk assessment to ensure employees were as chargeable as possible and there was financial support for unplanned projects. VSE's previous Business Intelligence capabilities were complex, inflexible, and failed to provide a standardized view of data.

Yamaha Music Europe, a subsidiary of Yamaha Corporation of Japan, is responsible for selling Yamaha musical instruments and audio-visual equipment across Europe. The company faced the challenge of harmonizing sales logistics and other data from six European sales divisions. They needed to unify all information into a single BI tool to facilitate cross-selling and upselling across Europe. The company also wanted to offer managers tools for immediate ad hoc query and analysis of data. Prior to the consolidation, the six subsidiaries held business critical information in disparate databases. From a business perspective, Yamaha was keen to improve the potential for cross selling and upselling across the region to take advantage of the growing integration of European markets and the growth of sales via internet.

Mercedes-Benz USA implemented SAP Finance and Controlling in 2000, followed by Parts Logistics, Materials Management, Sales and Distribution, and Production Planning in recent years. With five business units running on two instances of SAP, the environment has become progressively more complex. The total SAP system now houses two terabytes of data, with pricing tables alone adding up to 400 million records. The primary issue caused by the refreshes was that they took the non-production systems offline for several workdays in the middle of the week, which would negatively affect ongoing projects. Mercedes-Benz wanted to be able to provide developers with the data they needed for testing on an as-needed basis while reducing the number of full refreshes required per year. The company also wanted to be able to protect version information.

Tagetik, a leader in innovation, was looking to differentiate itself and deepen its competitive advantage in a crowded market. The company wanted to embed visualization, analysis, reporting and dashboards, and an associative in-memory analytics engine directly in its solution. The challenge was to integrate these features into their existing platform in a way that would provide their customers with visibility into all financial processes.

Amadeus, a leader in SaaS solutions for the airline industry, generates large volumes of data across its various applications. The company faced the challenge of reconciling and analyzing all of this data to produce attractive KPIs. They needed a solution that could handle the large data volumes and provide valuable insights for their operations.

Nationwide Building Society wanted to transition from a report-centric culture to a data-driven one. The goal was to make data accessible to all 19,000 employees, providing more visibility into business processes. The company aimed to create a 'Fit to Fly' data-enabled culture, where data is at the heart of decision-making and operations.

AECOM, a premier infrastructure firm, was facing challenges in managing the complex and dynamic market of coal combustion residuals (CCRs), also known as coal ash. The regulatory status of each coal ash unit was not centrally recorded, with each owner/operator maintaining its own website with all required regulatory reports. Manually gathering, analyzing, and summarizing this discrete data was complicated and arduous. Prior to 2019, AECOM was managing U.S. coal ash market data for customers in a series of spreadsheets, which had limited dimensionality and were challenging to quickly get results. The total amount of CCR material exceeds 2 billion cubic yards, making the management of this data a significant task.

Benjamin Moore, a renowned paint company, was looking to transition from being a product-centric enterprise to a customer-centric one. The company wanted to improve its customer experience and needed a solution that would enable it to do so effectively.

Urban Outfitters, a lifestyle retailer with 650 stores across the USA, Europe, and the UK, was struggling with siloed data across different systems and technologies. This made it difficult to gain daily visibility of actionable data, a problem further complicated by different time zones and the varying operating styles of the three business brands. The Covid-19 pandemic added another layer of complexity as the company had to manage store closures and differing pandemic strategies. The company's biggest roadblock was the inability to easily explore information to gain the necessary insights, resulting in reports that had to be manually compiled, consuming a significant amount of administrative time.

The Department of Education, Skills and Employment (DESE) in Australia is tasked with a broad undertaking that impacts the lives of every Australian citizen. It accumulates huge amounts of data from multiple sources, including early childhood care providers, schools, universities, registered training organizations and employment services providers. Understanding this data is essential for delivering a world-class education, skills and training and employment support infrastructure. However, DESE faced challenges with its data analytics approach. It needed to future-proof its approach with a scalable SaaS platform. The department also needed to eliminate data time lags to understand the current reality and provide data in an accessible, digestible and engaging format to end users.

The University Hospitals of Morecambe Bay NHS Foundation Trust (UHMBT) was facing the challenge of maintaining high-level patient service during the winter months when hospitals are typically overwhelmed by a patient surge. The operational staff were concerned about how they would cope with the rising demand for urgent care services. The challenge was to find effective and practical innovations to improve support for workers and overall patient care. The goal was to develop a solution that was business- and customer-led, tackled the big issues, and was focused on customer and business solutions.

The personal lines insurance industry is a highly competitive and price-sensitive marketplace. With more than two-thirds of UK insurance transacted online, the ability to compete on price comparison sites is key to success. As millions of quotes are generated each day, real-time analysis of vast volumes of data is fundamental for organizations targeting growth and needing insight into ‘live’ sales performance. Whether it’s pricing, a technical issue or variations in the market, alerts can prompt decisions that will avert substantial revenue losses. In this fast-moving industry, waiting 24 hours for access to data is not an option.

Bakkavör, a leading provider of fresh prepared foods and produce, was facing challenges with its sales data analysis due to the presence of more than 20 business units in the UK, each having a different Enterprise Resource Planning system and a different process for the analysis of their sales data. This resulted in too many bespoke applications or manual processes and not enough simplicity and consistency. The complexity of the system made it difficult and time-consuming to provide data accurately, leaving little time for actual analysis.