The company, a global federation of autonomous DIY retailer networks, was facing challenges due to rapid year-over-year growth, disparate data systems, complex per-brand needs, and a transition from products to solutions. The market was being disrupted by large online retailers, changing international trade agreements, and customers who wanted the power of mobile and the web when they shop. The company needed to pivot from merely selling products to selling service-based solutions. This required preparing all of its businesses, operating in different countries and under differing regulatory regimes, to be agile enough to offer new capabilities, new products, and new service models for a changing type of consumer.

Kredi Kayıt Bürosu (KKB), Turkey’s first and only credit bureau, experienced rapid growth since its inception in 1995. The company expanded to 180 member institutions, serving over 2 million end customers. However, this success brought challenges. The company was overwhelmed by a deluge of data, both digital and on paper, and struggled to manage it efficiently. Manual processes, including updating some data by hand and manually searching documents, were time-consuming and inefficient. Additionally, Turkey's strict requirement for immediate implementation and enforcement of new regulations added to the pressure. KKB needed a major change to continue its growth and handle new regulations with agility.

Gardner Denver, a leading global provider of high-quality industrial equipment, technologies, and services, faced several challenges. The company lacked real-time fault detection and the ability to remotely configure equipment, leading to costly servicing and repairs. The company's customers rely on the continuous operation of their industrial equipment, and eliminating downtime was a primary goal. Gardner Denver sells its equipment through a strong, global set of partners and distributors. It needed a way to capture operational information from its machinery and provide it to the organizations best placed to support its customers. Each partner and distributor takes ownership in its customers and pride in the quality performance of its equipment. Delivery of secure and unique solutions by each partner and distributor is critical to ensure high-performing machinery.

Georgia-Pacific, a leading manufacturer and marketer of tissue, packaging, paper, pulp, building products and related chemicals, was in the process of transitioning its technology to SAP® and Microsoft®. However, the company needed to continue meeting ongoing user needs with cost-effective products that could extract more information from older systems. A major operational challenge at the company's Port Hudson Operations was managing rental expenses for large equipment that the mill used only periodically. The legacy system did not provide the kind of information about rentals that would ensure effective management of such expenses. The company needed to improve its reporting capabilities while finding a cost-effective way to maximize the value of its RMS files and to open Champs to PCs.

Allied Electronics, an electrocomponents distributor, wanted to increase sales at its 70 branch offices scattered throughout the U.S. & Canada. The idea was to create a quote system that could use Allied data stored in an RMS database running on a VMS server. The Allied Quote system would enable managers, salespersons, credit managers and product managers to communicate through web forms using ASP.NET technology. The system would allow them to produce new quotes for customers, get management approval on certain quotes, have a contact database, provide a way for the various users to register inventory checks, and create orders, among a long list of other activities. The main interest was to capture data that was getting lost during phone conversations with customers, and also to be more responsive to the changes in their entry process. Gathering all the data on their quotes would give them a lot more information and allow their salespeople to dispose of their need to keep voluminous files on all of their customers.

A leading credit card company was failing to meet its one-second Service Level Agreement (SLA) for identifying blacklisted credit cards approximately 0.3 percent of the time. This resulted in blacklisted cards being improperly accepted, costing the company an estimated $10 million annually. The causes were twofold. First, the company kept its list of seven million blacklisted card numbers and individuals in a disk-bound Oracle® database, which was slow to access. Second, the Java® garbage collector caused extended, unpredictable pauses. Each pause forced the company to “guess” on many transactions, exposing the company to losses.

The company, a Fortune 100 shipping company, was facing a challenge in presenting relevant cross-sell offers to its customers within the stipulated Service Level Agreements (SLAs). The company receives more than 32 million tracking requests daily, each of which presents an opportunity to increase sales and customer satisfaction by serving up relevant content and offers. However, deciding which offers to present required time-consuming calls to multiple disk-bound databases, resulting in data retrieval times at least four times slower than those mandated by SLAs. This lag was cutting into potential cross-sell revenues and putting the company at risk of upsetting customers with a subpar online experience.

The company, a top loyalty program provider, was facing a challenge in meeting the aggressive end-to-end Service Level Agreement (SLA) of 500 milliseconds for every transaction, as demanded by large retail prospects. The company's data center took an average of 20 percent longer than that — 600 milliseconds — just to query upwards of 32GB of customer data in a central, disk-bound database. Furthermore, Java-related garbage collection pauses caused unexpected spikes in response times that would have resulted in financial penalties for failure to meet the SLA, and in unhappy customers. In order to win new business from larger retailers, the company realized it had to move its data into fast machine memory.

The company, a leading global producer of passive electronic components and interconnects, was facing several challenges. It was operating on a legacy mainframe infrastructure that was over 30 years old. The mainframe IBM environment, which included Software AG’s Adabas, Natural and EntireX, was still functional but was not equipped to handle the demands of the modern manufacturing world. The company was facing rising operational costs and was struggling to prepare for the green energy revolution and faster production cycles. By 2013, the company was in a critical situation. Backup hardware had become impossible to find, older users supporting the legacy system were retiring, software updates were non-existent, and adding new functionality was off the table. This meant that in the event of a disaster, there was nobody the company could call.

AVIC, a large-scale enterprise managed by the central government of China, was facing pressure from the aviation industry to improve its processes. The company had no top-level design and individualized processes with no collective strategy. The business and IT strategy were misaligned. AVIC had a number of complex, disparate systems and processes that needed to be streamlined if it was going to outshine its competition in terms of efficiency and agility and deliver on its strategy. Its approach was twofold: First, establish its AVIC Operation System (AOS) and get IT management in order and, second, conduct an in-depth process application analysis and smarten up.

The U.S. Army, one of the largest military forces in the world, faced several challenges. They needed to translate strategic business vision into effective enterprise change more efficiently, guide IT investment decisions to 'to-be' environments, enhance collaboration and support of core missions like HR, logistics, acquisitions and procurement, enable continuous process improvement, and manage rising costs in a constrained budgetary environment. The Army needed a robust strategy for its transformation, considering its 17 end-to-end processes, 1,600 operational activities, 700 systems in its IT portfolio, and four major ERPs.

The company, a leading marketing agency, was facing challenges due to the overwhelming volumes of data, the industry-wide revolution in digitalization, and a disruptive media and advertising environment. The company needed to deliver marketing messages to customers where they are, when they are receptive, and perfectly optimized for the right device or medium. They also needed to move beyond simple, post-campaign analysis to a set of analytic techniques that incorporated probability, statistics, algorithmic modeling, data mining, and machine learning. The volumes of data, computational resources, and technical knowhow required for this were tremendous.

Chevron, one of the top three integrated energy companies, wanted a centralized SAP® system with standardized process and master data design. The company was seeking to extract more value from its business processes. Additionally, Chevron identified the need for business process intelligence and a governance framework to ensure high quality and management of all material master data in SAP®. The challenge was to implement a system that could cover a wide range of processes, activities, and master data types across multiple countries.

The insurance company, despite its rapid growth and global presence, was facing challenges with its data integration platform. The legacy system was resource-intensive, expensive to maintain, and required specially trained personnel to operate. It was also not scalable, making it unfit for the company's growth trajectory. The insurance industry relies heavily on efficient data management for real-time business decisions, and the company's existing system was proving to be a significant barrier to growth. The company needed a solution that could integrate data from disparate systems, streamline operations, and scale with the company's growth.

As the company transitioned from a single market focus to becoming a digitalized global enterprise, rapidly growing data complexity became a major threat to the business. The company needed to manage complex product life cycles, control financial and human risks, and work with dozens of independent systems. Earlier attempts to solve these problems with a small data science team focusing on production had promising results. But the company quickly ran aground of business and technology liabilities, such as: human errors in manually coded models, scalability bottlenecks, burgeoning data volumes, and an inability to achieve real-time data processing goals.

The financial services company was facing challenges due to the extreme complexity of data volumes as a result of product flexibility. The company's data science teams were hitting capacity ceilings, leading to external risk from financial fraud such as money laundering and corruption. The company was using a dedicated team of data scientists to create hand-coded fraud models, but with millions of customer accounts, a large service portfolio, and geographically dispersed operations, manual coding became a major liability. The process of converting algorithmic fraud models to operational form dramatically slowed the process of “operationalization.”

The company, a global leader in consumer health products, was facing several challenges. They wanted to 'win differently' with a digital business platform, improve access to information enterprise-wide, reduce manual work and standardize processes, increase visibility across the global supply chain, and become more customer-centric. They were dealing with painful processes like manually collecting data from disconnected systems. They had no way to detect issues in delivery flow, and customer interactions were reactive rather than proactive. Costs increased due to shipment escalations. The disjointed Approval for Product Release (APR) process required manually consolidating paper specs into binders across all R&D functions. Every region had a different framework with no way to monitor or share information. There was no workflow support, no integration to other systems.

The company provides insight into the watching and buying habits of an estimated 10 million global consumers. Ad agencies and brand marketers rely on the company’s online measurement tools to maximize the effectiveness of fast-moving Internet advertising campaigns, so it’s critical that the company deliver ad performance reports quickly. Customers retrieved campaign performance reports through a web portal, which in turn queried a diskbound database to compile reports from tens of terabytes of ad-tracking data. However, customer satisfaction took a hit when slowdowns in data access began to degrade system performance. In some cases, customers had to wait as long as 20 seconds for campaign reports — an eternity in today’s need-itnow world. Even more troubling, slow database access caused an internal security system to time out on more than 50% of queries, and the problem only got worse as data volumes grew.

The Fortune 500 company, a multinational medical device, pharmaceutical and consumer packaged goods manufacturer, was facing challenges with its Approval for Product Release (APR) process. The process was outdated, paper-based, and relied on disparate systems, making it difficult to streamline and benchmark across products and countries. The old process took up to two years to complete and required stakeholders to write thousands of emails back and forth for a single product approval. With email-based collaboration, it was nearly impossible to determine who was working on the document or if additional changes had been made since the last email was sent. When there are potentially 50 different people who might have to make adjustments to a single document, duplicate work was almost inevitable.

The Central Bottling Company (CBC) Group, which holds the Coca-Cola franchise for Israel, wanted to mobilize its retail portal as part of a broader initiative to speed up the ordering process. Smaller retailers were still placing orders with on-site sales people and through an online portal. By mobilizing the portal, the CBC Group aimed to create a convenient self-service channel for retailers. The Mobile Enterprise Application Platform (MEAP) needed to work with the largest variety of operating systems and offer superior time to market at minimal cost and with maximum internal support.

Coca-Cola Refreshments owns and manages Coca-Cola® branded refrigerators in retail establishments. If repairs are needed, equipment may end up at the Make Ready Center. If the equipment can’t be repaired, it may be scrapped. In the past, this meant logging onto legacy systems on multiple servers to locate equipment information, record repair actions and change equipment status. The process was manual, error-prone and took up to eight hours to update information on 30-40 units. The company had no overall visibility into equipment status or maintenance history.

Fabick Cat, a tractor dealer specializing in the distribution of Caterpillar® equipment, faced a challenge when it acquired a second Caterpillar dealership. The newly acquired dealership had its own custom-written order processing system running on OpenVMS with RMS files, different from Fabick Cat's IBM® AS/400 based system. Fabick Cat wanted a solution to provide a data warehouse for both systems to ensure uniform reporting and analytics for both companies. The initial plan was to FTP files from the OpenVMS server and load them into SQL Server. However, the amount of data downloaded every day and the manual nature of this approach raised concerns.

The company, a global leader in consumer health products, was facing several challenges. They wanted to 'win differently' with a digital business platform, improve access to information across the enterprise, reduce manual work and standardize processes, increase visibility across the global supply chain, and become more customer-centric. They were dealing with painful processes like manually collecting data from disconnected systems. The company had no way to detect issues in delivery flow, and customer interactions were reactive rather than proactive. Costs increased due to shipment escalations. The Approval for Product Release (APR) process was disjointed and required manually consolidating paper specs into binders across all R&D functions. Every region had a different framework with no way to monitor or share information. There was no workflow support, no integration to other systems.

The company, a leading marketing agency, was facing challenges due to the overwhelming volumes of data, the industry-wide revolution in digitalization, and a disruptive media and advertising environment. The company needed to deliver marketing messages to customers where they are, when they are receptive, and perfectly optimized for the right device or medium. They also needed to move beyond simple, post-campaign analysis to a set of analytic techniques that incorporated probability, statistics, algorithmic modeling, data mining, and machine learning. The volumes of data, computational resources, and technical knowhow required for this were tremendous.

Coca-Cola Erfrischungsgetraenke AG (CCEAG), the sole German bottler of The Coca-Cola Company and the largest beverage company in Germany, was chosen as a pilot center for the Coke One global template deployment. The project would ultimately impact more than 75 percent of CCEAG’s existing applications in a highly interdependent IT landscape. Close to 1,000 business processes had to be reviewed and aligned across seven key areas: market-to-order, order-to-cash, forecast-to-deploy, procure-to-pay, record-to-report, master data management and human resource management. This corresponded to roughly 120 enterprise applications, 300 operational interfaces, 900 BI interfaces and 150 business objects that were impacted. CCEAG’s decision to use Enterprise Architecture Management (EAM) to facilitate its Coke One deployment was a clear project success factor.

Equens SE, one of Europe's largest providers of payment services, needed a way to provide proof of compliance with Service Level Agreements (SLAs) in payment processing to its customers. The company also wanted to utilize process measurements for internal analyses. The challenge was to monitor the SLAs without negatively impacting the operation of back-end systems. Additionally, Equens did not want to pursue a traditional data warehouse approach due to the several million transactions needing to be monitored every day.

The Department of the Registrar of Companies and Official Receiver (DRCOR) in Cyprus faced several challenges. The national financial crisis in 2013 had a significant impact on DRCOR's operations. The department had to deal with outdated information systems, paper-based processes, inefficient workflows, and a cumbersome user experience. Additionally, the department had to align with EU-wide best practices as part of the EU memorandum agreement. The department also had to deal with data overlaps and gaps, which further slowed down their operations.

The Chinese automobile manufacturer was facing pressure for improved sales forecasting, better manufacturing logistics and after-sales service, and a necessity to centralize data from multiple systems. The company was also dealing with growing customer expectations relating to specifications and services. The company planned to bring in a new Distributor Management System (DMS) to better manage its sales, logistics, and after-sales claims. However, the company faced challenges with data validity and timeliness from distributors. Data was also spread across numerous disparate platforms, creating data management headaches. In March 2017, the company faced the monumental challenge of integrating all of the old DMS’s whopping 744 modules into the new-generation DMS.

The multinational conglomerate corporation, a multibillion-dollar global manufacturer producing industrial, safety and consumer products, faced several challenges. The company decided to globally deploy SAP in 2010. However, the complexity of local legacy configurations strangled the SAP initiative. Millions of dollars were spent monthly on consultants to make changes at the plants and their legacy Manufacturing Execution Systems (MES). Four years into a five-year project, the company’s global SAP deployment was only 10 percent complete. The company needed a solution to accelerate SAP integrations at plants across the enterprise—making SAP deployment faster, simpler and safer while leveraging and extending legacy investments.

The regional subsidiary of a multinational power distributor was facing several challenges. The company needed to accommodate renewable energy on the grid, but had no visibility into medium- and low-power network issues. This resulted in high transformer maintenance costs and poor grid reliability in remote locations. The company also needed to monitor assets in locations with low or no internet connectivity. The utility had to find an economical and reliable way to reduce transformer loss and downtime, and fast!