Montgomery County Government in Maryland faced a significant challenge during the COVID-19 pandemic as it sought to support the increased demand for services, particularly in managing the COVID-19 vaccination registration process. The county needed an immediate solution to relieve the pressure on its human contact center agents and deliver better engagement and service delivery for its MC311 Customer Service Center and Department of Health and Human Services (HHS). The goal was to offer residents a fast, easy, comprehensive, and equitable COVID-19 vaccination registration process. The challenge was compounded by the need to quickly augment its contact centers with AI capabilities to handle the surge in demand without requiring extensive developer expertise.

With 350 front-line employees working on power lines across the province, injury prevention is an enormous priority for FortisAlberta. Thus, before any work commences at a site, an injury prevention plan (IPP) must be created to identify the risks and hazards staff need to be aware of and the actions they must take to stay safe. This plan must remain dynamic throughout the lifecycle of the project site, as any change to the job could introduce new risks, requiring new plans of action. Before adopting a digital approach, FortisAlberta used a paper-based system to complete and manage IPPs. Supervisors had to fill out paper forms and send them by email to the Safety department within 30 days of project initiation. Recordings of meetings were captured on handheld audio recorders and cross-referenced with the paper forms during random periodic checks or following an incident. To share the IPPs, employees took photos or made photocopies of the completed forms and sent them for site auditing. This made it challenging to pull information together in time to be reviewed at team safety meetings. The paper-based process created several challenges. Handwritten IPPs were not always legible, which made it difficult to record accurate information. The check boxes on the IPP form did not accurately reflect the job’s scope of work, its roles and responsibilities, or its hazards and barriers. The paper forms required double entry, necessitating additional administrative work. And it could take as long as two weeks before forms got to the head office, if they didn’t get lost along the way.

The San Francisco Municipal Transportation Agency (SFMTA) faced significant challenges in managing and analyzing the vast amounts of data generated by its operations. The agency's traditional reliance on relational databases and middleware was proving inefficient and resource-intensive. The existing systems required extensive manual processing, such as pulling data from CSV files into Excel for analysis, which was time-consuming and labor-intensive. Additionally, the on-premises infrastructure demanded costly engineering hours for maintenance and upgrades, making it difficult to scale and adapt to the growing data needs. The SFMTA recognized the need for a centralized data management solution that could streamline processes, reduce administrative bottlenecks, and enable data-driven decision-making to improve transportation services and optimize revenue.

Five years ago, Jacksonville University (JU) faced significant challenges in accessing and utilizing data effectively. The process was cumbersome, requiring leadership to fill out forms and wait for the analytics department to provide static reports. This reactive approach hindered timely decision-making and limited the ability to leverage data for strategic purposes. The arrival of President Tim Cost in 2013, with his extensive experience in Fortune 500 companies, brought a new expectation for technology and data accessibility. The need for a more dynamic and proactive data culture became evident, prompting JU to seek a solution that would democratize data access and empower leaders, faculty, and staff to make informed decisions. The existing data processes were siloed, with different departments owning separate data sets, leading to inconsistencies and inefficiencies. Meetings with deans often resulted in conflicting data interpretations, as each department relied on its own data sources. This lack of a unified and authoritative data set hindered meaningful discussions and strategic planning. The challenge was to create a centralized and accessible data platform that would streamline data access, improve data accuracy, and foster a culture of data-driven decision-making across the university.

Rolls-Royce, a leading British brand in the manufacturing industry, is facing the challenge of transitioning to a net zero carbon future. The company recognizes the need to decarbonize rapidly to ensure its longevity and continue delivering excellence in its engine manufacturing. The challenge is compounded by the vast amount of flight data that needs to be processed and analyzed to optimize carbon output. The existing on-premises infrastructure was insufficient to handle the data volume and processing power required for this task.

Kinleigh Folkard & Hayward (KFH) faced the challenge of modernizing their IT infrastructure while ensuring robust security and mobility. With sensitive information across ten business divisions, the leadership was initially hesitant about cloud adoption. However, by 2018, their on-premises infrastructure was nearing end-of-life, prompting a reevaluation. The COVID-19 pandemic further disrupted their plans, necessitating a rapid pivot to remote work solutions. The need for effective communication and collaboration tools became paramount as lockdowns were announced, pushing KFH to fast-track their digital transformation efforts.

Most businesses generate a lot of data, but that data isn’t valuable for decision making if it’s not structured and analyzed. Analytics aren’t as effective if they are slow and expensive to produce. Inlitix was founded to offer a timely, easy-to-use, affordable BI as a service for small and medium-size businesses. They focused on interoperability across different ERP systems with different datasets and offered out-of-the-box reporting and analytics solutions. However, Inlitix found that it only needed more compute power at certain times, such as when it spins up development and QA environments or when production data is refreshed. It didn’t make sense to pay for a constant high level of compute resources during the times when they weren’t needed. To minimize the company’s compute requirements and maintain affordability, staff would manually adjust and optimize queries, which took time away from focusing on more strategic tasks and adding value to their application. Inlitix wanted to optimize the balance between cost and performance of its databases while ensuring it could quickly process data from customer ERP systems and refresh Power BI reports more frequently.

Intesa Sanpaolo Group, Italy's leading banking group, faced the challenge of improving its real estate operations and facility management to cut waste and reduce its environmental footprint. The bank manages thousands of buildings and is one of the largest real estate owners in Italy, with more than 40 million square feet of assets. The challenge was to reduce energy consumption, improve comfort, and optimize operational efficiency across its vast real estate portfolio. The bank needed a solution that would provide real-time visibility into HVAC and other systems in its buildings, enabling data-driven actions to be taken. The complexity of the bank's environment required a robust and secure solution, as data protection is a critical concern for the bank.

West Marine 在管理和分析客户数据方面面临挑战。他们依赖第三方供应商和外部数据库，这些数据库成本高昂且不互连。他们希望收回对客户数据的控制权并充满信心地信任它。

每五年，澳大利亚墨尔本港（PoM）就需要跟踪所有进出的集装箱。了解货运流向对于确保正确的基础设施、工业用地、规划控制和政策设置到位以支持高效的供应链至关重要。 PoM 利用超过 57 个独立组来跟踪 60 多种不同格式的数据。此过程通常需要数百小时的手动时间和资源，而且从历史上看，预测率低于 30%。此外，直到最近他们才能够成功完成比赛分析。

一家拉丁美洲银行的运营部门面临手动数据处理的挑战，包括数据捕获、整合、处理和输出。他们还处理非结构化数据和重复的错误和工作。

由于迟到的费率变化、手动错误和错误编码调整，计费系统会在承保历史记录和现金分配数据之间产生差异。数据源和业务规则的复杂性使问题进一步复杂化。通过报告来发现问题既昂贵又耗时。

自 1980 年以来，美国已发生 246 起严重天气事件，每次造成的损失超过 10 亿美元。在此期间，天气事件造成的总损失总计达 8,460 亿美元，造成 5,500 多人丧生。面临的挑战是向受自然灾害影响的医疗保健公司成员提供及时的支持和沟通，确保获得保险、药物和医疗设备。

Lilly 拥有复杂的手动流程，使用 SQL、MS Access 和 XLS 在 S3 中集成 20 个不同的数据集以进行一项研究。由于孤立的流程，他们每天手动执行 8 次 SQL 查询来更新报告和仪表板，而协作程度极低。行动号召是简化和自动化下游数据流，以支持业务分析师，同时控制所有临床站点的成本和效率。

由于资产数量众多且数据复杂，Merlin Properties 需要一种有效分析和审计其财务和非财务信息的方法。

美国人口普查局依靠手动流程和过时的工具来收集、分析和报告数据，导致成本高昂且效率低下。

面临的挑战是创建一个完全自动化的解决方案，可以从数据库中提取最新数据，生成预测模型，并在实时加密货币市场上执行真实交易。

罗素家族基金会的目标是到 2030 年实现净零投资组合，需要计算其碳足迹并制定临时减排目标。