The traditional undergraduate education in the US is facing a decline, and the competition is increasing, especially with the advent of Covid-19 which has forced many institutions to move online. Budgets are tight, particularly for on-the-ground organizations that face the additional cost of maintaining buildings. It is vital that colleges and universities maximize returns when they are making large investments like opening a new campus or satellite. They must be sure that the site is right and must know the demographics of the students they aim to recruit. They must also pinpoint the best focus for their marketing spend. Obtaining this information requires the analysis of millions of lines of data, billions of highly complex calculations and input from the latest machine learning technologies.

CSC ServiceWorks (CSCSW) services laundry locations and air services at gas stations across the United States. These services are often overlooked because when they’re working well, no one thinks twice about them. But these are historically coin-based industries. As currency has increasingly moved into the digital sphere, these services are less convenient for the general public. About a decade ago, the payment technology for laundromats and air machines started to shift so that people could pay with a swipe of a card. It was a nice leap forward. As the years rolled on, the rise of the Internet of Things (IoT) made smart payments with mobile devices possible, connecting information on these payments to a main network. Now, we can monitor all of our machines from a central location, provide convenient app based payment, and offer a higher level of service. Just as CSCSW served a traditional coin industry, we had a traditional on-premise data warehouse platform when I joined the company as Chief Digital Officer in 2019. We have developers for these warehouses, who would run and share reports with others when necessary. It was functional in the past, but as we gained more data this wasn’t a viable solution. With connected machines, our thirst for data and analytics within the company grew exponentially. We needed to have easier access to the data within the organization so people could get the information they needed on their own, and developers could focus on more important work besides pulling queries and running reports. We needed a more efficient way of dealing with data and driving value for our consumers, clients and employees.

Tenaga Nasional Berhad (TNB), the largest electricity utility in Malaysia, is aiming to become a leading provider of sustainable energy solutions by 2025. To support this goal, TNB's Group Finance Division initiated the creation of a centralized Business Performance Management (BPM) dashboard. The dashboard was designed to increase the focus on growth and profitability, transforming finance from process manager to value creator. However, the challenge was to ensure that the dashboard displayed accurate and timely information, provided the correct picture through data visualizations, and was delivered to the right stakeholders.

China’s rapid technological development has created a need for trained data analysts but there is a skills gap in the recruitment market for students with strong data literacy capabilities. One organization working to plug that gap is Xi’an Jiaotong-Liverpool University (XJTLU), an international joint university based in Suzhou, Jiangsu, China. The university recognized the need to provide hands-on data analytics experience to its students to prepare them for the job market.

J.B. Hunt, one of the largest transportation and logistics companies in North America, was seeking to increase efficiency and customer responsiveness by gaining real-time insights into its operations and assets. However, the company faced the challenge of not impacting production systems while doing so. They had implemented a Microsoft Azure Databricks data lake but needed to accelerate the flow of analytics-ready data into the lake.

Weber State University (WSU) began using Qlik AutoML in late Q1 2020, right as the pandemic took hold in the US. As Covid-19 wreaked havoc, the university had difficult decisions to make about where to allot resources in the midst of self-described “survival mode.” A combination of the right power at the right price made Qlik AutoML a viable choice even in uncertain times as a method to empower, support, and retain their students in a quickly-changing world. After a trial month with Qlik AutoML, decision-makers saw value thanks to Qlik AutoML’s ability to translate something complicated to something understandable, making it easier to share with stakeholders with and without technology backgrounds. With limited funding, Qlik AutoML was a more attractive option because of its affordability compared to competitors and consultants that can incur “astronomical expenses,” according to WSU’s Heather Chapman, Director, Academic Analytics.

CSC Financial Co., Ltd (China Securities) needed to better understand asset movements in real-time to maximize investment strategies. It also wanted to provide its clients with a real-time display that would clearly show the status of their portfolio from the China Securities application and other investment channels. The company had to deal with large data volumes and many databases which required up to 18 replication tasks. Frequent system upgrades also meant that replication environments had to be constantly rebuilt and replicating from heterogeneous databases was a cumbersome operation.

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.

Naylor Association Solutions was facing a challenge in their marketing-sales processes, particularly in lead scoring and qualification. The company was using a CMS that required account executives to fill out nearly 30 different data fields, which were then used by the marketing automation platform for scoring and qualification. This process was time-consuming and frustrating for the salespeople, who viewed many of the fields as unnecessary. On the other hand, the marketing team couldn't provide a better justification for the data other than they needed it for their processes.

Beyond 12, a technology-based services organization, aims to increase the number of low-income and first-generation students who graduate from U.S. colleges and universities. However, they lacked a data scientist on staff who could build a predictive analytics model. They needed a robust in-house tool managed by their existing engineering staff for a viable and scalable solution. The objective was to refine Beyond 12’s approach to addressing their analytics needs and to provide coaches with a bird’s-eye view of their students. This would enable them to provide the right assistance to the right students at the right time.

Chef Works, a supplier for hospitality businesses, was impacted by the economic climate driven by the global Covid-19 pandemic. The company experienced a reduction in bandwidth and a growing need to effectively practice data science with a lower time commitment. The pandemic left many businesses in the hospitality industry on uncertain ground, and Chef Works needed to make the best use of their time and resources to not only sustain themselves through these changes, but to continue to innovate in ways their customers have come to expect at a price point that would be agreeable to once-lucrative businesses now strained for cash. Chef Works understood the grim reality that, while many of their customers would see the other side of the pandemic with business in-tact, many would not. To better support those that would survive, and to understand which businesses those were most likely to be, Chef Works turned to the power of data science.

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.

Yellow Brick Road (YBR) was struggling with their existing business intelligence (BI) tool. The company was initially using Excel for data analysis and reporting, which led to significant delays in data delivery. The sales teams needed timely information to make decisions regarding sales targets and strategies, but the company didn’t have insights into loans until they received the commission statements from the banks—a delay of around eight weeks from the time of the actual sale. The delayed insights were always a challenge in making informed decisions to improve the sales KPIs, and the stacks of Excel sheets received from the lenders in different formats didn’t help with a timely and meaningful presentation. The company then implemented an emerging reporting software, which was a step up from Excel and a step in the right direction. However, not having local technical support and the tool's exorbitant pricing made them lean towards a more established tool with a local presence.

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.

Systemair, a leading ventilation company with operations mainly in Europe and North America, faced several challenges. The company needed to share valuable business data locked in its Movex ERP system with more than 25 subsidiaries throughout Europe. The goal was to simplify and speed up data analysis enterprise-wide for improved decision-making. Additionally, Systemair wanted tighter control over business processes and operations to ensure 24x7 product availability for customers. As the business complexity grew, the existing system of analyzing data with simple SQL queries and Excel became unworkable.

Target Express, the largest independent express delivery company in the UK, was looking to enhance its industry-leading image as an open, proactive business partner. The company wanted to quickly unlock data stored in various systems to provide superior service and share detailed logistical information with customers beyond standard industry KPIs. A key account recognized that a huge repository of information residing in Target Express’ systems would be valuable for conducting their business more effectively. The customer requested access to the data which would disclose what it cost them to operate in a specific area, move specific products, during a specific time of year, and numerous other operational insights.

TEAM Computers, a leading IT Infrastructure Solution provider in India, was looking to leverage its vast pool of data to support its ambitious growth plans. The company wanted to proactively manage its day-to-day business operations to maximize revenue. The challenge was to find a solution that could provide a unified view of data pulled from multiple sources, improve performance, and offer better control over productivity.

ThedaCare, the largest healthcare provider and employer in Northeast Wisconsin, was facing challenges with its existing reporting systems. The systems were becoming cumbersome and not user-friendly. Ad hoc requests required end users to have IT develop the report. The process could take days to answer business and clinical questions—a situation worsening with increasing data volume. With 43 customer sites, 5400 employees and a commitment to improve healthcare value for its employer plan purchasers and 225,000 patients annually, ThedaCare needed to upgrade its reporting tools—but not at the high capital investment in server hardware and software licenses that its existing dependence on SAP Crystal Reports would require.

ThiemeMeulenhoff, one of the three largest educational publishers in the Netherlands, was facing several challenges. The company needed to allow management access to the latest information to gauge performance and allow staff to select and interpret data without the requirement for IT. They also needed to upgrade their reporting to comply with International Financial Reporting Standards (IFRS) and transition from a paper-based to a digital information flow. The company was also implementing a timesheet system that still needed a report module. They had the option of choosing between a traditional system, which produced reams of paper lists on a daily, weekly and monthly basis – heavily supported by their IT department – or a more modern Business Intelligence (BI) solution.

Tommy Hilfiger's head office databases are periodically updated with data that’s necessary for the work of all group companies and partners. The Russian representative office receives these updates in the form of Excel files from the head office. Head office uses the Oracle and SAP software, and the Russian partners use several different configurations of 1С:Enteprise business management software and other vendor systems. Another challenge was the timely receipt of sales reports from the Russian partners. The supervision system requires partners to provide weekly sales reports to the Moscow office and each of the 12 partner companies keeps daily accounting of sales in spreadsheets or in various accounting systems. At the end of each week, the data is emailed to Moscow, where it is manually consolidated into a report. As the data gathering and consolidation process was lengthy, the Moscow office would often experience delays in receiving information. Moreover, all reports consisted of ‘raw’ figures, which had to be processed and analyzed for a long time before any decision could be made.

Toshiba Europe, a subsidiary of Toshiba Corporation, was seeking to improve its service quality, measure the performance of its outsourcing partners, and optimize its spare parts procedures. The company's customer service is supported in eight European countries by external customer contact centres that handle around 60,000 calls a month. The company wanted an analysis solution that could check whether the agreed service levels were being met by monitoring various key performance indicators (KPIs). In the repairs department, the aim was to analyse turn-round times on individual orders, so as to manage more efficiently the repairs and necessary logistics processes. The company was looking for an analysis solution that could be installed simply and quickly and then flexibly operated by the European specialist operations department itself. The system should avoid taking a toll on internal IT resources or incurring cost-intensive days spent on site by external consultants, as well as being capable of collating and analysing data without needing a special data warehouse.

Tulikivi Corporation, the world’s largest manufacturer of heat-retaining fireplaces, adopted a new, product group-based strategy. In line with the new strategy, the company wanted to analyse business information more efficiently. Previously, meetings dragged on while waiting for information, and in many cases the information received was not the information that was agreed on. Further challenges included slow reporting and software, which resulted in waiting for analyses. In the old days, it was a challenge to compile reports manually quickly enough. The software was too slow and they had to wait for analyses. Meetings dragged on and the reports that were produced did not always meet the actual need. Distribution of reports was another problem.

TVH experienced rapid growth due to several successful takeovers, leading to a significant increase in data volume. Their existing reporting system, which relied heavily on Excel, was unable to handle the increased data load, resulting in slow processing times and a lack of clear overview. The company was using multiple data sources, including AS400, Oracle, and Progress, which further complicated the situation. The old system lacked flexibility and was unable to make necessary links, leading to insufficient collection of sales, customer, and item-related information. There was an urgent need for a new reporting system.

UWV, a governmental organization in the Netherlands, was facing the challenge of replacing all paper and static reporting with dynamic models for reporting and analysis, directly tuned to the information requirements of the users. The volume of paper reports within the HRM department was growing continuously, with each report being created manually with data from the personnel information management system. The departmental management team wanted to replace these reports, which were already dated the day they were distributed, with automated, 24/7, dynamic reports presented in an easy to use dashboard environment with slice and dice and drill down functionality.

Van Oirschot, a supplier of heating and installation materials for professional installers in Flanders, was facing the challenge of implementing a reporting and analysis tool that ensures consistent information provision and provides easier insight into Microsoft Navision data. The company operates five branches and a central distribution centre in Flanders. It creates added value by handling additional aspects for its customers, such as transport, stocking, provision of credit, collection and splitting, packaging and repackaging, services, guarantees, returns, information provision and training. However, it was crucial for the company to remain competitive and innovative in the face of increasing competition, chain integration and cost pressure. Moreover, their customers were expecting greater flexibility, longer opening hours and automated ordering processes.

Vellinge Municipality was facing a challenge of analyzing information residing in disparate source systems. They needed stronger controls in order to reduce overall operating costs. The solution required was one that could be used by employees lacking formal finance training and background. The municipality had a policy of keeping the income tax rates low, which meant that everyone in the organization needed to review all costs associated with every departmental decision. This involved approximately 10 controllers and 60 managers with budget responsibility sitting in different locations. Before implementing QlikView, they had to compare printouts from different systems manually to compile the information. In many cases, they even had to manage without the necessary information.

VIP Parts, Tires & Service, the largest privately owned US automotive aftermarket retail chain, was facing several challenges. The company wanted to replace its one-dimensional merchandising hierarchy reporting with multilevel merchandising and business unit views. They were also struggling with integrating disparate data from multiple systems. The company was seeking to increase the visibility of operational KPIs throughout the organization. The company's sophisticated business footprint spans retail, wholesale, fleet, and commercial divisions, making it crucial to have a comprehensive and integrated view of all operations.

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.

Wanbury, a rapidly expanding pharmaceutical company in India, was facing challenges in accessing and analyzing its 'big data'. The company's business was growing and it needed to improve its business discovery capacity to cater to an increasingly mobile executive team and enable complex analysis of large data sets. The company was previously using a system of exporting data from various standalone applications into Microsoft Excel spreadsheets to generate largely static BI reports. This system had several drawbacks, including reduced accountability for, and visibility of, organizational and individual performance. This often delayed decision making by senior management and heads of departments. The reporting solution was also unable to provide analysis trending capabilities to executives who were on the move or away from the office.

WD-40, a global consumer products organization, was facing challenges in analyzing reported data and gaining insights into customer behavior. The company was relying on hard copy weekly reports to provide crucial business detail, which was putting increasing pressure on the IT department to produce more meaningful sales information in a user-friendly, real-time application. The traditional reports created by the company’s previous ERP system were both costly to produce and lacked important detail. A data analysis tool was needed to support WD-40’s growing business and to ease the pressure on IT resources. The company also needed applications that would support, speed up and simplify financial reporting to its parent in the US, a logistics application for better order-to-delivery efficiency and pan-European sales analysis for proactive management.