Christian Aid, an international development charity, has a large supporter database that records details of voluntary donations given by supporters in response to marketing and fundraising initiatives. The ability to easily access and report on this data is vital to ensure that the best use is made of investment in fundraising, and to assure supporters that effective use is being made of their generous gifts. However, until recently, Christian Aid had struggled to deliver comprehensive analysis of results and trends from its large and complex database.

The University of Bologna, one of the most prestigious universities in Italy and abroad, was seeking technological innovations to support its administration. The university had already developed a data warehouse system in collaboration with CINECA, a suite of business intelligence systems created to improve university management. However, the university recognized the need for a system that could simulate and anticipate the cost trend of its teaching and technical-administrative staff. Knowing and predicting how the staff will age and what kind of funds will be necessary is fundamental for the development of a rational plan of resources. The university contacted CINECA to develop and integrate a university data warehouse with the technological solution that would best meet this requirement.

Cisco, a worldwide leader in networking, was sitting on mountains of rich data that could empower individuals throughout the company. However, the company was facing challenges in transforming this data into actionable business intelligence. Cisco has a broad array of products, each with their own cadence of product releases. Additionally, Cisco customers also have different products in their deployments which create complexity with respect to support and maintenance for individual customers. With nearly 500 million lines of complex data, the company wanted an easy and efficient way to deliver quality data to the consumers of the information. Cisco launched a “business intelligence (BI) bake-off” over five years ago in search of a comprehensive BI solution that could help fuel business insights.

Before the implementation of QlikView, CMC Call Center faced several challenges. They had issues with viewing reports from different angles and the need to monitor departments separately. They experienced performance-related problems in terms of report queries, access to information in different applications, and version changes. The lack of a flexible platform led to delayed decision-making. Additionally, when users sent similar queries direct to the operating system, a heavy load built up on the system itself. When business units wanted to make advanced-level and value-added analyses, they needed to devote more time to preparing reports. Since the reports were not prepared in a standard format, the preparation of new reports suitable for each changing request exacerbated the workload of both the operating and IT teams.

In 2004, The Cocoa Trees found that its accounting system, which was designed for generating static reports and financial statements, and based on batch processing, became inadequate for the rapidly growing operations. They were unable to generate reports on inventory levels on-demand or in real-time. Twice a month, the warehouse supervisor had to physically inspect stocks to prepare an inventory expiry date report to monitor the shelf-life of these perishable items. It was time-consuming as each report took two days to complete, with inevitable errors. Service levels were unsatisfactory as the order fulfillment cycle took too long. Salespeople could not propose or confirm orders with customers immediately against inventory levels. On top of that, because of the lack of clarity on inventory, some salespeople circumvented the system by physically pre-packing stocks at the warehouse to reserve the stocks, leading to many internal conflicts.

In 2006, Coface Ibérica, the Spanish division of Coface, realised the need to come up with a business intelligence (BI) solution at a local level. The company needed to take better decisions quickly and to be able to monitor certain critical activities within the company, as a complement to the corporate tools used by the group. The systems department initiated a selection process in which different manufacturers’ products could be evaluated. QlikView was the solution chosen because of its ability to permit a gradual alignment with control frameworks and the ease with which it could be deployed and managed.

Colchester Hospital University NHS Trust (CHUFT) was struggling with managing big data and extracting valuable insights. The organization was dealing with over 2,000 reports per day and 140GB of data per week, which made timely and accurate reporting critical for their decision-making process. The existing system was limited in content, flexibility, and visibility across the organization. Reports were often out of date and reflected incorrect and inconsistent patient information. The hospital needed a solution to efficiently and accurately analyze data, particularly related to mortality rates and oncology treatment.

In 2005, Colonial Life's Business Intelligence and IT groups decided to provide improved analytic and reporting capabilities to its user community. However, it was imperative for user acceptance of any solution that it be as easy to use as possible at all skill levels. In addition, high transaction volumes among the company’s 60,000+ customer accounts meant that the chosen solution needed to aggregate information quickly and completely to facilitate decision-making. A visit to a data warehousing conference brought QlikView to the attention of Bryan Allen, the company’s Assistant Vice President of Business Intelligence. After an evaluation process put six tools through their paces, the Colonial Life team ultimately selected QlikView based on their capabilities, ease of use, and performance.

Com Hem, a Swedish TV and broadband specialist, was facing challenges with its network infrastructure. The company's network services reach 40% of Swedish homes, with over 600,000 digital TV customers and almost 500,000 broadband customers. This massive infrastructure and complex technology, with thousands of miles of cables and innumerable exchanges, connection points, and modems, required real-time monitoring to quickly respond to any faults and correct problems. Each minute was crucial for the company. Until 2009, Com Hem’s network monitoring operator had been looking at various systems for acquiring an overall picture of what was going on in its network. They realized the potential for saving time and, as a result, solving network problems faster.

In 2008, the CUD‟s general management launched a project to assess the public body‟s spending efficiency. They had to look at predictable areas of spending on human resources, finance and energy. The team faced a daunting challenge. In order to assess spending efficiency, they had to obtain information on the relevant parts of the business including human resources and finance. They then had to provide management tools to the departments concerned, in order to carry out management analyses, and correlate public policy with the resources used. This was a typical business intelligence (BI) project, with a familiar challenge: the data was highly disparate, while there was a need for consolidate and cross-reference of data across very different areas of the organization.

Context, a leading technology research company in Europe, was in need of analytical tools that could improve upon spreadsheets and static reports for delivering research to customers. The company was looking for tools that did not have the complexity and delays of traditional OLAP cubes, which would impair the value of reporting. The challenge was to find a solution that could provide dynamic, unrestricted reporting on timely, actionable market intelligence.

Crown Worldwide Group, a global logistics company, was using a mix of BusinessObjects and home-grown software for business intelligence analysis and reporting. However, they needed to supplement BusinessObjects with a dashboard solution to make business intelligence more easily accessible to branch managers throughout the company. The solution needed to enable managers to easily explore information that is relevant to them visually. The company was finding that BusinessObjects required a lot of upfront work, new reports took a lot of IT time to produce and their business leaders were demanding dashboard business intelligence tools. They researched and considered Qlikview, BusinessObjects Crystal Exelsius dashboards and other available solutions in the market.

DAKOTACARE, a healthcare leader in South Dakota, manages hundreds of millions of records on subscribers and providers, from coverage to codes to claims. The company was data-rich but information-poor, with staff having to rely on IT for custom reports that would address internal reporting as well as questions from healthcare providers and clients. Their requests were placed in a queue, then prioritized, with the resulting reports coming days or even sometimes weeks later. Much of their information needs were time-sensitive, and by the time people got their questions answered, they no longer needed the information. Representatives would not even ask for data requests knowing that their information needs would not be met prior to a decision deadline. Or, intrepid representatives would try to extrapolate answers on their own, often with varying results.

Lundbeck A/S, an international medical concern, was facing challenges in providing a quick and effective overview of complex clinical and operational data. The company was working on a digital process for the collection of medical research data that was previously recorded on paper forms by doctors worldwide. The information was recorded digitally and stored in several different databases. The company needed to monitor and analyze the information collected during product development. An important link in the development phase was the ability to test the product's effect on a large number of people. These test results were collected in a set of databases. The company needed a solution to simplify reporting and optimize the planning of clinical studies.

Madrid Salud, an independent not-for-profit organisation within Madrid City Council, was in need of a business intelligence tool that would help them create a balanced scorecard and monitor the progress of departmental work. The organisation was dealing with all local authority responsibilities relating to public health and substance abuse. The department had a professional team of 1,306 staff, all fully committed to making Madrid a healthier city. Its mission was health promotion and disease prevention through comprehensive treatment of people suffering from addictions. The mandate included encouraging wellbeing, food safety, improvements in environmental health, and sustainable integration of animals in the city. The department was also responsible for managing the council’s prevention of occupational hazards service and other autonomous bodies.

MAF Carrefour Hypermarkets, a rapidly expanding retail industry player in the Middle East region, faced challenges in gaining rapid access to massive amounts of data and reducing time for analysis and reporting. The senior executives needed meaningful answers at their fingertips as operational decision making is key to driving performance in highly competitive and growing markets. The challenge was not only to deliver a tool that can fill the gap of a managerial dashboard but also provide an in-depth view into the data below as and when needed. With existing business intelligence (BI) reporting tools, managers were able to get reports and analysis. However, they were unable to gain insights into growing volumes of ‘big data’ and have a bird’s eye view over the full operations.

Maler-Einkauf Rhein-Ruhr, a buying association with 15 branches in the Rhine/Ruhr region, was facing challenges in evaluating its business data due to the large number of customers and listed articles. The company's reporting system consisted of endless lists of printed paper, which was laborious and time-consuming to navigate. The options for questions and analysis were very limited, preventing the management from dynamically and flexibly controlling their sales and purchasing processes. The primary challenge for MEG Rhein-Ruhr was to better cultivate their customer base specifically through a customer-oriented approach, which required highly efficient analysis of data from business processes to improve performance.

Malmö University Hospital was facing challenges in managing patient waiting times and deviations. The hospital needed to gain increased control of the flow of patients. There was a need to find a cost-effective and powerful solution that allowed analysis of information from the many different systems. The Eye Clinic at Malmö University Hospital was working on how to correctly prioritize patients in terms of referral management and thereby increase accessibility. Their goal was to make a patient’s path through the healthcare process as quick and easy as possible. The clinic had problems with managing waiting times and deviations and the management needed to gain increased control of the flow of patients.

Marienhospital Gelsenkirchen, a leading academic training hospital in Germany, was facing challenges in amplifying transparency within the clinic to achieve greater efficiency and prepare for the statutory demands of Diagnosis Related Groups (DRG). The hospital was struggling with the efficient evaluation of patient data from diverse information systems. The introduction of the DRG-System for service related accounting in 2003 made it clear to the hospital that they needed to create more transparency within the clinic to achieve greater efficiency in the administration of internal services and to be prepared for the DRGs during annual budget negotiations with the Health Insurance Funds. The limitations of the existing system were reached extremely quickly. The standard evaluation software (Excel) was not capable of effectively analyzing the extensive amounts of data created from 27,000 patients per year.

MarktSelect, a leading database-marketing specialist in the Dutch business-to-business market, was facing several challenges. They needed to provide their customers with 'readable' up-to-date management information. They also needed to measure the results and enhance the effectiveness of their marketing and sales efforts. Another challenge was to make links between data from very diverse databases. During a visit to a large Direct Marketing exhibition in San Francisco, they noticed that needs were changing worldwide. Analysis and segmentation were becoming hot topics. They needed a flexible Business Intelligence (BI) analysis tool that would enable their customers to raise the effectiveness of their marketing and sales departments.

Masoutis Supermarkets, the fastest growing supermarket chain in Greece, was facing challenges due to its rapid organic growth. The demand for ad hoc reports and analyses of various business parameters had increased exponentially. Business users ranging from buyers to store area managers, controllers, and C-level managers were pushing the capacity and capability of the existing IT infrastructure to its limits. The existing reporting tools were struggling to handle the flood of data from POS, ERP, CRM, WMS systems all lying on different databases from DB2 to MS SQL and Excel. 600 million records queries were common practice, which often resulted in a wait time of 1-3 hours for a report to run. Apart from increasing performance, Masoutis was also looking to improve the quality of decision making by providing users with valuable business insight, allowing them to freely navigate in the ocean of company data anywhere, anytime, securely.

MassMutual Asia was facing challenges with their previous Business Intelligence Systems (BIS). The systems were inflexible, had poor performance, and were unable to meet users’ requirements or provide on-time reports. This was affecting the efficiency of decision making and the competitiveness of their products and services. The company had tried to switch to another traditional BIS, but this also presented problems. The development tools lacked flexibility, many user requirements could not be fulfilled, and developers had to do extra programming and settings because of its architecture. The system also utilized tremendous resources and required many servers to run effectively, making maintenance costs high and increasing overall IT expenditure.

McAfee, the world’s largest dedicated security technology company, was facing challenges around its financial reporting and operational processes. The company found that its Business Intelligence (BI) solutions were limited and employees were unable to aggregate reports in an efficient way. In fact, approximately 50 percent of the finance group spent 50 percent of their time gathering reports, which left very little time to analyze the data and make the appropriate business decisions. Only select employees were actually able to access, view and analyze forecast, bookings and renewals data, which prevented upper management from receiving timely and accurate business insights. Additionally, these challenges greatly increased IT dependency. McAfee needed a BI tool that could standardize reporting, reduce the amount of manual work required to aggregate reports, increase data visibility and empower business users from all over the company to pull reports with little to no IT involvement.

Mediocredito, a leading Italian bank specializing in consulting, advanced finance, leasing and merchant banking to small and medium-sized enterprises, was in need of a system to provide targeted corporate analysis and consultation. The bank wanted to monitor financial risk and view and interpret such data in a simple, easy-to-manipulate manner. The bank embarked on an ambitious project, X-Match, to identify a system that would provide targeted consulting of strategic corporate data and analyze and monitor financial risks. The project took approximately two years to create the model, with the greatest effort placed on analyzing and structuring the underlying database.

Meilleurtaux, a leading mortgage loan financing broker in France, was facing challenges in managing its rapid growth and gaining insights into client profiles, loan files, and scoring to identify the right business to undertake. The company was working with more than 80 reports, created in Excel, each requiring access to 2 million records stored in an Oracle database. This overloaded the database and indicated that new investments in servers would have to be made. In addition, the creation and maintenance of these reports required the work of 10 IT department employees, who were spending a great deal of their time building up the reports and were also confronted with major issues of inconsistency. The implementation of a more adequate and scalable platform solution was becoming crucial.

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.

Merck Sharp & Dohme B.V. (MSD), the Dutch subsidiary of the US corporation Merck & Co., was using JD Edwards World, a worldwide financial system with limited scope for analysis and reporting. The parent company uses the data from this system to make consolidations and draw up the annual financial statements. It applies a complex set of rules which determine what costs are allocated to what items in the balance sheet and the profit and loss account. MSD Netherlands has to account for any differences in balance sheet items by conducting a detailed analysis. The challenge was to find a solution that would allow them to analyze the data from their financial system quickly and easily, and also take account of their specific set of rules.

META, a data consultancy created by Kinetic, aimed to build highly visual applications to sell data consultancy services and bring together disparate data sets for customers to gain competitive advantage. The company wanted to convert customers’ own data into actionable business insight. The challenge was to build innovative and highly visual applications to sell data consultancy services to third parties with a fast time to market. META needed a solution that bridged the gap between traditional business intelligence (BI) solutions and standalone office productivity applications. Previously, this was achieved at Kinetic using spreadsheet software, IBM Cognos, and manual processes. META needed a flexible, scalable, and agile BI solution to simplify multiple data sets and do the heavy lifting of aggregating data from multiple sources.

Mitsubishi Electric Cooling and Heating Solutions (MEUS) faced a significant challenge in reporting due to the scattered source data across multiple systems and sub-systems. These systems included SAP, SalesLogix, the company’s website CMS, and a homegrown training management system. The process of compiling a basic sales report took 20 to 40 hours a month, involving the exportation of SAP reports to Excel and manual consolidation of fragmented data from various other systems. This not only resulted in lost time but also a lack of visibility into sales, training, and customer service opportunities. MEUS needed a solution that could consolidate data from all its enterprise software and homegrown systems and run powerful reports in a fraction of the time currently required for reporting.

The 1. Obermurtaler Brauereigenossenschaft, a leading brewery in Austria, was facing several challenges. The company had no accompanying cost accounting, no mobile access to current data for staff working offsite, and no ad-hoc analyses were possible. The company was keen to have a simultaneous costings program designed as well. This was to provide the executive management team more quickly with the information it needed for decision making on, for instance, compiling the product range, manufacturing, sales or marketing. The new solution needed to answer queries on sales, such as, for example, sales of total and individual products as well as by region. Another requirement concerned the mobility of the business intelligence (BI) application to give off-site staff the opportunity of working with daily data updates.