UBM, a leading global events business, was undergoing a significant strategic transformation named 'Events First'. As part of this transformation, the company was preparing to complete the largest acquisition in its history - Advanstar, a US-based events and marketing services business valued at more than USD970m. The company faced the risk of human capital flight if it was unable to effectively engage top talent with the new strategic direction. UBM needed to make significant structural, process and systems changes, uniting its previously autonomous regional businesses. The challenge was to ensure all of its employees were engaged and aligned with the new future vision.

Balluff, a world-leading manufacturer of sensor solutions, was experiencing slow access to finance and business reports which threatened productivity and potential growth. The company's SAP Business Warehouse solution serves around 500 concurrent users, and the aim was to transform personal productivity and enable real-time enterprise-wide information insight. The company needed to speed up information availability to support its sales and business development functions with real-time information for better insight into markets and customers. Without timely, accurate information, the company risked making poor investment decisions and was unable to deliver the best possible service to its customers.

Basin Electric Power Cooperative, one of the largest electric generation and transmission cooperatives in the United States, was struggling with data management. The company's data was held in dozens of systems, spreadsheets, and people’s heads, making it difficult to make informed decisions. The company recognized that its reliance on complex manual processes represented a serious risk to the business. In strategy meetings, staff were often unable to agree on the figures that they were meant to be analyzing. Too much time was spent trying to determine which system, spreadsheet or expert truly had the right information about a given issue – and this lack of visibility hampered the organization’s ability to make smart decisions.

Coherent Path, a personalization pioneer, aimed to help its retail clients leverage their customer data to deliver experiences and offers optimized for the entire customer journey, not just the next step. The company wanted to differentiate itself from rival firms by moving beyond simplistic ‘you may also like’ recommendations to a position where it can help its retail clients maximize both near-term revenue as well as the lifetime value of their customers. The extreme complexity in terms of the number of products and channels made it hard for retailers to understand their customers’ behavior and preferences, particularly if they were only using nearest-neighbor statistical analysis.

Columbia Sportswear was undergoing a large-scale ERP systems implementation and substantial business process transformation, which threatened the viability of its existing finance reporting and planning processes. The company was at risk of losing its ability to execute core financial processes without a significant level of time-consuming manual intervention combining data sets from the disparate ERP systems. The company needed a solution that would not only maintain the flow of information to key decision makers but also enhance it. In addition to streamlining information delivery, Columbia Sportswear wanted to find a solution that would provide deeper insight into the performance of various parts of its business, helping to enable better corporate decision-making.

Connio Inc., a Canadian tech startup, aimed to develop an end-to-end IoT platform, CONNIO, to help enterprises and entrepreneurs bring innovative Internet of Things (IoT) solutions to market rapidly. The challenge was to manage the volume and variety of its data cost-effectively. To ensure that the CONNIO platform could support an explosion of instrumented devices and networking technologies, the company looked for a database foundation with the flexibility to meet its enterprise-level requirements. They needed a high-performance data layer capable of storing and processing a huge variety of unstructured data models. Support for stream computing was essential, and they looked for a NoSQL database solution that would enable them to query JSON data in-flight efficiently and cost-effectively.

After the 2008 economic crisis, the construction market crashed, forcing established players like Consolidated Contractors Co. (CCC) to cut costs and boost revenues to maintain their market share against new competitors from the Far East. CCC recognized the need to become a flexible, highly dynamic business and set out a 2020 vision of operating smarter construction sites supported by cutting-edge Internet of Things technology. Specifically, it targeted improvements in the management and utilization of its equipment, since these factors have a major influence on the total costs of completing each construction project. To pinpoint areas for improvement, CCC needed a clear view of equipment availability, health, status, location, and maintenance costs, which its existing IT systems and paper-based processes were unable to provide.

Continental Tires, a major global tire manufacturer, was facing inefficiencies in its production landscape, which manufactures 10,000 different products. The company was using manual, spreadsheet-based allocation of products to production plants, which was extremely complex and time-consuming. The process was entirely dependent on the know-how and experience of the people driving it and used no form of computer-aided optimization. Since data could not be transferred between documents automatically, it was also easy to make mistakes. The company planned production budgets annually and at a fairly high level to lighten the burden this process placed on its planners. But since the company launches 1,000 new products every year, even this method was becoming unviable.

Roskilde Festival, the largest North European culture and music festival, faced the challenge of keeping 130,000 guests safely entertained, fed, watered and informed in a sustainable way. The festival generates huge volumes of real-time data, which if analyzed, could provide critical insights for planning and running the festival. The Copenhagen Business School (CBS) saw the festival as a potential real-world laboratory for improving sustainability issues. They wanted to understand the movement of people around the festival site, the sales of food and beverages over time, and the popularity of different musical events. However, the data types and data volumes were essentially unknown at the outset, requiring a highly flexible solution.

Tyréns, a leading multi-disciplinary consultancy in Sweden, wanted to gain a deeper understanding of how people experience and interact with the buildings they live and work in. The company wanted to move beyond intuition and guesswork and base its understanding on hard data. The goal was to answer questions such as 'Why is it too hot on this floor?' and 'How many people actually use this 12-person meeting room?' in order to help clients make smarter management and maintenance decisions. The company chose its Stockholm headquarters as the first project for creating a smarter building.

Ctac, an ICT solution provider and SAP Value Added Reseller, noticed a growing trend among its customers towards more flexibility, faster business processes, and real-time analytics. The company realized that if it could enable its customers to leverage rapid insights into business data cost-efficiently, it could help them gain a competitive advantage. However, Ctac wanted to build a solution that would allow its customers to optimize their business processes without high up-front investments in IT. The company decided to look for the right configuration for core customer workloads that would enable synergies among traditional and new real-time analytics SAP workloads in a single environment utilizing its resources as efficiently and flexible as possible.

DLF Ltd., one of India's largest commercial real estate developers, wanted to enhance the mobile shopping app of the DLF Promenade mall to deliver insights about customers that retailers could use both to enrich the shopping experience and to influence customer behavior. The mall, located in an upscale community of over 100,000 residents in the Delhi National Capital Region (NCR) of India, occupies more than 4.6 million square feet of real estate and features many high-end international brands. The challenge was to help retailers develop a higher conversion ratio of visitors to buyers by providing them with valuable insights about customer behavior.

Building steel mills and the related equipment is a highly complex process that requires orchestrating thousands of components, workers and machines. Lacking modern planning software, Italy-based Danieli & C. Officine Meccaniche S.p.A., a steel plant builder with factories in five countries in Europe and Asia, struggled to coordinate materials and resources, compromising efficiency and jeopardizing timelines.

Darwin Ecosystem was founded with a unique vision of harnessing chaos theory mathematics to uncover previously hidden connections in unstructured data. The company’s algorithms can look at all the data generated by any source (such as news, RSS feeds and Twitter), and analyze how a specific set of concepts within that data are evolving over time. This is particularly valuable in situations such as business and competitive intelligence, social research, brand monitoring, legal discovery, risk mitigation and even law enforcement. A common problem in these areas is that a regular web search will only turn up the all-time most popular answers to a given question – but what the expert researcher is actually interested in is the moment-tomoment evolution of the data available on that topic. Darwin’s algorithm is computationally intensive, and the sources of data it correlates can be vast. To bring its benefits to a larger commercial audience, Darwin needed to find a way to make it scale.

Desert Research Institute (DRI) is the environmental research arm of the Nevada System of Higher Education. With more than 550 scientists, engineers and technicians, and campuses in Reno and Las Vegas, DRI staff work to solve some of the world’s biggest environmental issues. One of the challenges that scientists have faced in recent years is analyzing an increasing volume, velocity and variety of data from field observations, lab systems, remote sensor networks and mathematical models. The amount of data collected is extraordinary. In fact, atmospheric scientists at DRI are working with NASA on planning for missions that will produce up to 24 terabytes of data per day. DRI faculty members have traditionally been responsible for acquiring the computing and storage technology they needed to support their research projects. Often, data collected from remote locations around the world is stored in flat files and managed by individual research teams. This decentralized approach increased IT costs and limited how the organization’s research data could be used.

In the knowledge economy, speed of insight is a key competitive differentiator. Established organizations must be prepared to move as fast as their new competitors—but the critical first step is to see the right opportunities and identify the competitive threats in a timely fashion. However, existing approaches to analysis and reporting are often stuck in the age of the spreadsheet. Even where organizations have adopted data warehouses and enterprise analytics tools, the usual heavy reliance on IT specialists leaves business users frustrated at the lack of flexibility and speed in getting answers to critical business questions. Many of the clients who engage with Destiny Corporation are struggling to identify and respond appropriately to new competitive pressures because it takes them too long to gain a clear insight into opportunities and issues.

Deutsche Lufthansa AG, a leading airline, was looking to improve its online customer experience. The company wanted to launch a web reengineering initiative to enhance its online service delivery. Additionally, to support a new content management system with enhanced functionality, the airline needed to extend its hosting infrastructure with a platform running a Linux operating system.

Dow Benelux, a branch of the Dow Chemical Company, recognized the importance of employee wellbeing for the productivity and efficiency of the organization. The company wanted to monitor workplace stress at individual, departmental, and organizational levels. The challenge was to develop an analytics solution that could effectively measure and monitor these stress levels. The company also needed to comply with Dutch government legislation requiring employers to quantify potential occupational health risks. Dow Benelux wanted to go beyond mere compliance and embed occupational health management into its core business processes.

The Dow Chemical Company, a USD60 billion enterprise composed of a worldwide network of 13 business units, faced challenges in setting and achieving enterprise-wide goals due to its decentralized business structure. The company needed to meet the differing facility needs of its various businesses while also increasing office and lab space capacity use to 90 percent and improving capital planning, real estate lease management, operations, maintenance, and energy consumption on a global basis. The Lab and Office Facilities Management (LOFM) group at Dow, which provides facilities management services and solutions that support more than 20 million square feet of lab and administrative office space worldwide, was tasked with driving these initiatives. However, reporting in all of these areas was manual, disconnected, and spreadsheet-driven, making it difficult to leverage data effectively.

EF Education First (EF) provides language tuition around the world, often by immersing students in another culture. As student numbers fluctuate in different markets and destinations, the company must manage a dizzying array of costs relating to staffing, accommodation and educational materials, and price its offerings to maintain healthy profits while also maximizing sales. With thousands of employees influencing its budgets and financial plans, the company had difficulty ensuring a consistent approach to calculating costs and collecting data. Historically, EF had relied on spreadsheets to collect and compile financial and operational planning data from employees. As a highly decentralized organization, this was no easy task, and it was difficult to ensure a standardized approach to calculating figures and creating accurate budgets.

EY's clients are increasingly seeking growth in markets with higher perceived levels of fraud, bribery, and corruption risk. Regulators and law enforcement bodies are intensifying their activities, leading to significant corporate investment in employee training, policy development, and internal audit procedures designed to raise awareness of anti-fraud or anti-corruption policies. Many companies have also increased the use of more sophisticated, proactive uses of forensic data analytics (FDA) capabilities designed to prevent and detect areas of fraud, waste, and abuse. However, traditional rules-based tests and spreadsheet tools are not effective in managing these risks. EY needed a solution that could help them get ahead of the curve and squash potential threats before they escalate.

The Electricity Supply Board (ESB) in Ireland was facing a challenge with its large-scale electric vehicle (EV) program. The increased demand for electricity due to EV charging was potentially destabilizing the grid. ESB needed a solution to optimize the charging load without negatively impacting the consumer experience. Additionally, they wanted to provide customers with a way to optimize their consumption by aligning their usage patterns with energy pricing fluctuations.

The Emirates National Oil Company (ENOC) was facing challenges due to the increasing complexity of operations. The process of collecting, consolidating and analyzing financial data from different legal entities within different systems had become time-consuming. The central finance team at ENOC was losing days each month manually inputting and checking financial data from 31 subsidiaries. The real challenge for the central finance team was ensuring data consistency and accuracy. Manual input inevitably results in a high risk of error, and painstakingly validating data from over thirty entities each month was becoming unsustainable.

Energy Saving Trust (EST) needed a high-performance analytics solution to support carbon reduction initiatives in the United Kingdom. The company had pioneered a solution that brought together large datasets with advanced statistical models to identify optimal opportunities for energy efficiency measures. However, with massive amounts of detailed information spread across numerous sources, EST required a high-performance analytics solution to make the data comprehensible and actionable. Additionally, with a large number of government organizations hoping to use the information, EST required an easily accessible, highly available hosting platform for the analytics application.

Erhvervsstyrelsen, the Danish Business Authority, supports businesses across Denmark. It runs 450 projects across 27 offices, employs 600 people, and is responsible for an annual budget of DKK 600 million (USD 89.8 million), as well as a number of national and EU grants. Each of these projects manages its own budget – but Erhvervsstyrelsen needs to maintain control of overall expenditure, report back to the Danish parliament, and demonstrate the value it delivers for taxpayers’ money. For this reason, it is very important for the organization to have a robust, reliable budgeting process. Erhvervsstyrelsen was formed by a merger of three former agencies, each of which had its own separate budgeting system. Since none of these systems could be adapted to meet the needs of the new organization, Erhvervsstyrelsen set up a new budgeting process based on spreadsheets. This process involved sending out spreadsheets to each project manager, and manually collecting and consolidating the data they sent back.

The German Federal Employment Agency (BA) was struggling to manage claims for statutory benefits using its primarily paper-based processes. The agency had to transport and store around 3.5 billion physical documents, which was time-consuming and inefficient. The onset of the global financial crisis in 2007 led to a rapid increase in demand for the BA's services, with the agency receiving 700,000 claims and enquiries per day. This put a strain on the BA's existing processes and made it difficult for the agency to meet the needs of its citizens efficiently.

Fingrid, the company that manages Finland's high-voltage transmission network, wanted to find smarter ways to manage its 14,000 km transmission network to boost reliability and service levels, control costs, and support better investment decisions. The company needed a more comprehensive overview of its assets and network status in real time. The challenge was to quickly analyze the entire power system when a fault occurs. In the past, it took days, if not weeks, to get all the information required for root cause analysis of a fault.

As First National Bank (FNB) expanded its business activities within South Africa and in neighboring countries, it found that its decision-support systems were not running optimally in the face of increasing demands from internal users, customers, and regulators. The inflexibility of existing systems was making it slow and costly to adapt rules to meet new requirements, hindering business agility. The existing solution could not support different sets of rules for each country, so FNB was forced to construct multiple instances of the rules engine. This implied the costly replication of rules and associated redevelopment and testing work, and also meant that changes made by head office took too long to propagate out to the subsidiary countries. With up to 40 changes to shared central rules each month, each of which had to be separately tested and deployed across ten countries, the existing approach at FNB was clearly inefficient in development terms.

Floyd, a healthcare organization serving over 350,000 patients across six counties in northern Georgia and Alabama, was on a journey towards population health management. As part of this journey, Floyd wanted to obtain National Committee for Quality Assurance (NCQA) Patient-Centered Medical Home (PCMH) recognition, a widely recognized model for transforming primary care practices. To achieve PCMH recognition, organizations must demonstrate improvement in six process measures. Floyd was already using IBM Phytel Outreach and IBM Phytel Remind from the IBM Watson Health Patient Engagement solution. However, the Floyd team knew that the IBM Phytel portfolio could also play an important role in its journey toward PCMH recognition.

Fresenius Medical Care wanted to optimize its reporting process, particularly in light of the increased demands made by regulatory authorities on external financial reporting. The preparation of financial reports in accordance with international accounting standards (IFRS and US-GAAP [Generally Accepted Account Principles]) as well as in different currencies (Euro and US dollars) is a very complex and expensive process. The legal importance and reputational value of these standardized quarterly and annual reports for listed companies require the financial reports to be of a consistently high quality. However, the requirements for the structure and content of these reports are constantly increasing, while the submission deadlines get tighter.