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Arawak Port Development (APD) is a critical enterprise for The Bahamian Government and its citizens, with all international ocean freight passing over their bulkhead at Nassau Container Port. After going public in 2012, APD needed to start producing a range of financial statements that would satisfy the quarterly and annual filing requirements of the Securities Commission of The Bahamas, provide sufficient information to external auditors, and enable the APD Board of Directors to better manage the growth of the organization. APD's CFO, Dion Bethell, also wanted to increase the level of detail in his planning, while concurrently weaning the management team away from budgeting for items that had a low likelihood of occurring. Because APD is a critical economic hub for the country of The Bahamas, there was no room for error.

Mike Wells, the Director of Software Development at Ameritas, a mutual life and health insurer with $35.6 billion in assets, was tasked with helping the company achieve competitive advantage in an increasingly digital marketplace. However, he faced a significant challenge. The majority of Wells’ software development experience was on distributed platforms; yet about 70% of his developer workforce at Ameritas was mainframe focused. Coming from a background where automation and visibility were at the forefront of every Java developer, he realized that this presented a challenge in the mainframe arena. Wells was skeptical about whether their tools and processes could provide the speed and agility Ameritas needed to thrive in a fast moving digital marketplace.

The IMT Group, a leading Midwestern P&C insurer, heavily relies on its mainframe for core applications. However, the mainframe application environment is in transition. The company's mainframe transition strategy has two key objectives. One is re-platforming select applications, a process that requires intensive analysis of current mainframe code. It requires complete and accurate identification of “dead code”—sections of applications that have lapsed into disuse over the years, but remain present in source code. The other key objective is converging mainframe and non-mainframe environments. This convergence is taking place because of how the company’s newer web- and mobile-based applications depend on back-end mainframe resources. Both of these strategic objectives require developers to have clear, complete visibility into the structure and runtime behaviors of highly complex mainframe applications that have undergone a lot of change over the years and are not always well-documented.

Physicians Mutual, an insurance company, was struggling with the management of millions of lines of complex mainframe code. The lack of documentation and tools to manage this code led to long development cycles, preventing the company from capitalizing on critical business opportunities. The complexity of the mainframe code and the absence of tools to manage it resulted in missed opportunities to capitalize on immediate business interests. The company needed a solution that would help them understand and manage their complex applications, speed up maintenance and development cycles, and attract and retain top developer talent.

Avvo, an online legal marketplace that connects consumers with lawyers and legal advice, was facing a disconnect between the pricing of sponsored advertising and the customer value it offered. The pricing was based on feeling rather than fact, making it difficult for the sales team to prove value to new prospects or implement demand-based price adjustments on existing accounts. The team needed to understand the number of impressions and clicks on sponsored advertising positions by region and legal specialty. If consumers in a particular region spent more time exploring content or clicking on ads for a particular specialty, then the value of advertising for that service in that region should be higher—and the price should be increased accordingly.

Global Tech LED, an LED lighting design and manufacturing company, was looking to increase the adoption of its Solstice® LED modules. These modules are universally compatible with HID fixtures, making them ideal for retrofits. The company had successfully used Google AdWords to increase the number of phone customers. However, it faced the challenge of keeping visitors engaged, bringing them back to its site, and moving them down the purchase funnel. The company wanted to focus on high-potential customers who were most likely to engage and make purchases.

Dafiti, a fashion retailer operating across Brazil, Argentina, Chile, Colombia, and Mexico, was facing challenges with managing tags across multiple sites. The company had to maintain more than 100 tags from media partners across a variety of tools. This led to two major issues: increased page load times and a significant dependency on IT staff to address tagging needs. Some tags were deployed within Dafiti's CMS platform, but many required a different rule to be 'fired,' necessitating implementation support from IT. The company was looking for a solution to manage tags efficiently, reduce dependence on IT, and decrease page load times.

Magazine Luiza, one of the largest retail chains in Brazil, was facing challenges in managing its Google AdWords campaigns. The company had a large number of tags on its website, which was making the tracking and management of its campaigns complex and inefficient. The company wanted to reduce the number of tags to a minimum and simplify the measurement and management of its campaigns. The company's IT team was handling all of the tag implementations, changes, and requests, which was time-consuming and inefficient.

Mumzworld, the Middle East’s largest shopping site for mother, baby, and child products, was facing a challenge in spending its ad dollars wisely. The company had ample user data but needed to make more sense of it. They wanted to increase online sales and repeat buyers, lower the cost for user acquisition and conversions, be more data-driven with its channel investments, and manage on-site inventory better to lower out-of-stock product views. For help, Mumzworld turned to InfoTrust, a Google Analytics Certified Partner that specializes in ecommerce data integration.

Philadelphia Media Network, which includes Philly.com and Pulitzer Prize-winning Philadelphia Inquirer and Philadelphia Daily News, was looking for innovative ways to monetize their digital platforms. They were operating under an old-school philosophy that separated direct sales and programmatic sales, which was limiting their revenue potential. They wanted to optimize their ad inventory and maximize revenue for every impression while strategically pricing their inventory. They were also interested in benchmarking their direct-sold and providing their sales staff with more flexibility.

ScanTrust, an enterprise SaaS platform that connects millions of products to the Internet by giving each of these products a unique digital identity in the cloud, wanted to enhance its offering in supply chain traceability. The company aimed to help their client, Cambio Coffee, bring more transparency to their ethical trade business. Cambio Coffee, a direct trade organic coffee company, wanted to provide their customers with a way to trace the journey of their coffee from harvest in Peru to shipment, to roasting in Shanghai and then to delivery to their home. Each stop on the journey needed to be recorded on a tamper-proof system to validate their claims of building a direct link from coffee farmers to consumers.

The National Association of REALTORS® (NAR) is America’s largest trade association, representing 1.3 million members involved in all aspects of the residential and commercial real estate transactions. Members belong to one or more of approximately 1,200 local associations/boards and 54 state and territory associations of realtors. All of these organizations are independent, even though they work together. NAR was looking for ways to better serve their members and felt that analyzing members’ engagement would help them achieve this goal. Unfortunately, member engagement events were only available to the association where the event occurred. Getting over 1200 CEOs to agree to give up control of their data and processes by switching to one common database sounded unlikely.

Deutsche Börse Group (DBG) is a leading global exchange organization with a track record of innovation in information technology in the financial sector. DBG started to engage in the blockchain subject during 2015 and identified more than 20 use cases across its business units. Given the fact that blockchain was – and still is – in its infancy, to quickly gain internal knowledge, DBG selected a few use cases, relevant for its core business, for deeper analysis and subsequent realization of Proof-of-Concepts (PoCs). For the time being, DBG does not expect its core securities and derivatives trading business will shift to blockchain based trading systems, due to their large throughput and ultra-low latency requirements. DBG concentrated instead on use cases in the post trade arena and identified potential for blockchain applications in the area of clearing and settlement of securities & cash. Blockchain can improve the operational efficiency in these areas, i.e., shorter settlement times, reduction of reconciliation efforts, more efficient asset servicing, etc. In the long run, certain clearing and settlement functionality will likely materialize via blockchain being supported by clearing houses and CSDs to manage credit and counterparty risks.

Sony Global Education identified the need to create a more comprehensive, open, and trusted system for recording the education and training credentials of Japanese citizens. The existing system had credentials sitting in silos, each requiring a different process for validation. Sony Global Education envisioned a system that accurately records how individuals perform in academic and training settings and then controls access to this recorded information. This would give businesses and educational institutions a more complete picture of candidates’ backgrounds and help them pick the most qualified individual for each job opportunity and program admission.

VF Corporation, a highly diversified, branded lifestyle apparel, footwear, and related products company, wanted to improve corporate profitability, support retail expansion, and maximize the performance of the company’s more than 100,000 SKUs at more than 10,000 retail locations. In 2009, the company's RFSM organization assumed responsibility for the company’s customer relationship management (CRM) efforts with its retailers. While the company already had an internal CRM database, it also needed to correlate and analyze this data along with huge volumes of data from a number of other disparate internal and external sources. The company’s existing solution was not scalable or reliable enough for a company the size of VF Corporation. The existing solution did not allow VF Corporation to include spatial information, which was becoming increasingly important to the company and its retail expansion efforts.

Chipotle’s real estate managers were spending a significant amount of time interacting with static datasets to analyze potential revenue and targeted markets for prospective restaurant sites. The company needed a more efficient way to deploy timely sales forecasting data and its complex site-location selection model to its brokers. The existing system was time-consuming and the relevant up-to-date data was not always readily accessible to all employees. The key to securing prime real estate for restaurants is the speed at which new locations are targeted and developed. Chipotle was seeking a system that could more efficiently deploy sales forecasting tools and its complex site location selection model in a browser instead of requiring employees in the field to search, select, and input data into multiple laptop programs.

DatabaseUSA, a leading provider of business and personal mailing lists, email lists, sales leads, and related database products, was facing a challenge in maintaining the quality and accuracy of its data. The company was dealing with raw data from hundreds of different sources and multiple directories, including data from utility companies and call data from its call center. To manage this, the company had to hire individuals with high-level data expertise, which was costly. Moreover, every time new data was introduced, the company had to develop a significant amount of new, low-level code to get the data into its database successfully and accurately. This process was not only expensive but also difficult to scale.

Rosenblatt Securities, a premier independent institutional brokerage and investment banking boutique firm, was facing a challenge in performing sophisticated data analyses for its clients. The firm was dealing with millions of rows of execution records and market tick data, which often took days or even weeks to process. The firm was using Tableau visualization software since 2006, but many processes included blending different heterogeneous datasets and running multiple analytic models, which could take days or even weeks of preprocessing time and still required manual error-sampling. The firm was faced with a decision: to spend thousands of dollars on a specialized ETL tool to interact with its structured and unstructured data sources, or to build such a tool internally.

The University of Dayton needed to quickly process thousands of pieces of student data from different systems across the university, enabling it to recruit, enroll, and retain the students most likely to succeed at the institution. Rising costs and increasing government involvement in higher education are bringing a greater focus on student outcomes. At the same time, data is available from an increasing variety of sources and departments—internal and external, structured and unstructured. University of Dayton is leveraging publicly available census data, high school academic records, college entrance exams, student activity and transcript data, and postgraduation information.

Brookson faced several challenges in their operations. They had no visibility across departments, which led to a high amount of time being spent on creating spreadsheets. They also had a high volume of internal work orders and a siloed customer experience. These challenges were hindering their ability to deliver customer experience excellence. They needed to improve accuracy and timeliness, reduce investment in administration, ensure tasks were done right the first time, and become less reactive and more proactive.

7-Eleven, a multinational convenience store chain, was seeking a solution that could be used by business users on a daily basis without much technical support. They needed to get results quickly to share with external business associates, and provide multiple capabilities at a marginal cost. The company wanted to bring all of their vendor data sources together into one output to get deeper insights into their promotions to see what’s working and what’s not.

Ryohin Keikaku Co., Ltd. operates retail stores centered on MUJI, and moreover, product planning, development, manufacturing, wholesaling and merchandising. The company administers 1,029 stores worldwide, in breakdown 479 stores in Japan and 550 stores in overseas respectively (as of August 2020). In 2017, the company introduced Tableau as a BI (Business Intelligence) tool to visualize and analyze various kinds of data, including customer information and sales results, for the purpose of sales metric analysis. As everything continued going to plan in 2018, the desire to utilize the reports that were being used in Japan overseas became more entrenched. However, when Ryohin Keikaku created intermediate data for Tableau on the core system program, only the developers can perform maintenance. So, it is difficult to respond to requests from users to make improvements quickly. They also lacked of people who had the required specialist knowledge to participate in the global roll-out of Tableau report creation during the project to reconstruct the global system.

In 2014, Sears Auto Center was facing declining sales and margins. The company had useful operations data, but it was inconsistent, difficult to analyze, and open to misinterpretation. The operations performance, particularly at the regional retail level, was difficult to analyze. Different management layers had different reports, and even shared data was open to misinterpretation. In a competitive business environment, static monthly reporting was not dynamic enough to enable Sears Auto Center to respond to in-market regional trends. When a location’s business was struggling, it was tough to fix things when you couldn’t agree on what the data tells you.

Weitz & Luxenberg, a legal services firm, was in need of a business intelligence solution that could deliver more than just data. They needed a solution that could easily fix and connect data, provide self-service for users, offer an easy-to-use interface, integrate data sources without limitations, and turn data into actionable insights. They were looking for a solution that could help them make data-driven decisions, identify bottlenecks, and determine the most effective means of customer acquisition. They also faced challenges with disparate systems and ineffective communication with partner law firms.

Driva, an Australian car financing platform, was struggling with managing and leveraging its data as the company expanded into new product lines and markets. They were collecting data through various sources such as consumer application info, their CRM system, Google Analytics, and their product-based analytics software. However, it became too difficult to reconcile data across different sources or create reports using multiple data sources. They needed a solution that could bring all its business data together into a single source of truth.

NLC Mutual, a member-owned insurance provider serving the reinsurance needs of 28 states, was facing challenges due to the lack of a central business intelligence system. This hindered its ability to leverage data when processing claims and underwriting coverage. Each state has its own systems for claims and underwriting management, making it difficult to collect data in a timely manner. The company was also struggling with collaboration issues with its members due to the lack of a unified data platform. The municipal reinsurance industry is highly competitive, with larger cities often looking for private options to see if they can find better rates compared to the coverage provided by their state. NLC Mutual needed a solution that could help them prove their value to customers and engage in proactive conversations.

North American Properties, a real estate company, was facing challenges in managing its expansive portfolio and planning future projects due to the lack of a unified data system. The company was using its data primarily for reporting purposes, which only provided insights into past performance and did not allow for future projections. The company's properties were using disconnected ERP systems and other siloed data sources, making it difficult to consolidate and analyze data. To address this, North American Properties created a new business intelligence team tasked with leveraging the company’s data across projects and making it actionable.

WKS Restaurant Group, which operates five different restaurant brands across 400 locations, faced the challenge of managing data from disparate sources due to the different operational metrics of each brand. The company needed a solution that could integrate data from various legacy technologies and make it usable for business leaders to understand the commonalities and differences in the business. The company also needed to track its sales and revenue across each brand, regional district, and location. Additionally, WKS wanted to improve its visibility into its costs, such as repair and maintenance budgets, and track the speed and uptime of its internet at each of its locations.

Penola Catholic College, a co-educational secondary school in Melbourne, Australia, serves a diverse student population of approximately 1,500 students. The school's educators struggled to leverage all the student data at their disposal due to the data being scattered across multiple locations. This made it difficult and time-consuming for educators to collect and synthesize the data in a way that could produce meaningful insights. Without the ability to visualize data and put it in context, educators couldn’t quickly determine which step to take next, which meant at-risk students would fall further behind before they got the help they needed.

Equicapita, a private equity firm with over $300 million in assets under its management, was facing challenges in tracking the success of its diverse portfolio of 13 companies. Each company measured success differently and delivered its reporting in significantly different formats. This resulted in each company spending about three days each month on a manual reporting process that involved collecting data, normalizing it, consolidating it, and then creating reports for the board. The firm was also looking for ways to use data to help the companies under its umbrella work smarter.