Coca-Cola Bottlers Japan Inc. (CCBJI) 是亚洲最大的可口可乐装瓶公司，在日本运营着一个由超过 700,000 台自动售货机组成的网络。该公司收集了大量有关每台机器的整体销售业绩以及每台机器和地点的单个产品的表现的数据。历史上，CCBJI 必须从核心系统中提取分析所需的数据，建立自己的机制，使用 ETL 工具创建数据仓库，并执行各种分析。所产生的数据规模之大给该公司带来了多项挑战。其中包括返回简单查询结果所需的时间长度以及此类遗留系统的复杂维护。

瑞士再保险作为全球领先的再保险和保险提供商，在保险市场面临着一系列挑战。该市场增长缓慢，很大一部分客户的行为类似于 booking.com，在加入保险产品之前阅读评论。此外，从 IT 到互联网再到隐私等法律法规的变化，使得向保险领域推出新产品变得极其困难。这就导致监管机构对保险公司、保险公司对老百姓、老百姓对保险公司缺乏信任。瑞士再保险需要找到一种方法来扩展其地理覆盖范围、地理启用其数据并监控其资产，以克服这些挑战。

Leroy Merlin, a global home improvement retailer, needed to sense changes in selling patterns and quickly translate that intelligence into a series of decisions that go up the supply chain. Most decisions were made from headquarters, including the analysis of market areas, zones of influence, and distribution areas. This required executives and managers to know when and how much to ramp up or cut back on production, and where to distribute. It also meant choosing the right combination of transport modes to balance the urgency of delivery costs. Leroy Merlin found aggregating the data for key decisions an arduous and time-consuming task. To unify these data sources into a coherent and complete picture, managers created a seamless real-time reporting visualization to introduce precise predictive demand planning capabilities with a goal to share geomarketing and geolocalized data among store managers, marketing and business development departments, and executives.

Following seismic demographic, economic, and technological shifts across the city of London, JLL and London & Partners realized a modern site planning tool was needed that advertised the advantages of working in this global business center. JLL wanted to provide commercial Real Estate clients determining where to start, relocate, or expand operations with a solution that would process large volumes of data into accurate, precise, and up-to-date insights for clients without GIS expertise and accessible through a centralized application.

Rilos, a consulting firm operating in 15 countries, provides retail location intelligence solutions. They gather, update, standardize, and analyze data to help clients minimize risk, make informed decisions, and optimize sales and networks. However, this process was complex, costly, and time-consuming. As their client base grew, Rilos needed a solution that would allow clients to perform their own analysis with site studies and reports on demand, without the need for additional employee resources.

Vodafone Business, the B2B division of Vodafone, was faced with the challenge of managing the rapidly increasing mobile data traffic and the growing demand for location-driven insights. The company wanted to leverage the big data generated across its mobile networks to better understand human mobility patterns. However, this presented two major obstacles. Firstly, to comply with privacy regulations, Vodafone needed to extract movement patterns on populations, not individuals, necessitating a robust anonymization and aggregation methodology. Secondly, to familiarize customers with working with mobile data, Vodafone needed an accessible interface capable of presenting the true value of these insights. In addition, the company saw a larger opportunity to deliver the first mobile data business solution by combining Vodafone’s data and Location Intelligence.

ConnectEast, the owner and operator of the 39km EastLink toll road in Melbourne, was facing challenges in managing its vast array of infrastructure assets. The company was using a paper-based method of asset management, which was inefficient and time-consuming. Documents were scanned and saved or transcribed into the system manually, or in the case of photos, uploaded. This process was not only cumbersome but also posed the risk of potential loss of information. Moreover, scanned documents (PDF’s) did not allow for spatial analysis or reporting capabilities. There was a lack of real-time visibility, and it was difficult to meet ongoing reporting demands, including KPI tracking for government reporting purposes.

Gloval's Data & Analytics team wanted to start using location analytics solutions to develop Valea, a web application that would allow its clients (professionals from real estate agencies and investment funds) to make spatially-informed decisions on residential property assets. They sought to provide its clients with a solution that would allow them to analyze and visualize large volumes of data on the Spanish real estate market. This included big data processing, need for faster insights, and going beyond traditional PDF formats. They needed to support business and sales strategies for their clients with asset closure data, available assets data, financial data on potential margins, and historic data on residential property assets. They also wanted to provide a faster and frictionless experience for clients, allowing them to understand the potential sale price of their property with an enriched market study, exhaustive & spatially-informed market analysis, supply and demand statistics, and socio-economic indicators to enrich existing data.

GDELT 作为世界上最大、最全面的人类社会开放数据库，面临着重大挑战。全球地理图谱是 GDELT 的一部分，涵盖了自 2017 年以来全球英语新闻报道中超过 17 亿个地点提及的内容。该组织希望绘制全球新闻叙事的地理地图，但事实证明，这项任务非常复杂。所涉及的数据量之大。我们面临的挑战是找到一种方法，以一种既有意义又易于访问的方式有效地可视化大量数据。

The UNHCR’s Inter-Agency Coordination Unit based in Beirut, Lebanon’s capital and largest city, operates at the epicenter of a complex web of refugee support and response. They coordinate between over 200 organizations, governmental, NGO, and private sector. In order to effectively coordinate, they created 12 working groups, each with a distinct focus area. These working groups, supported by a unified IT infrastructure, create and execute on 4-year plans while also meeting unexpected challenges with rapid response. The refugee crisis, and the support system that has risen up to help refugees in Lebanon, is complex. Unofficial settlements pop-up regularly and the landscape is constantly shifting. Government policies impact refugee settlement status, environmental factors impact refugee safety, shifting populations require constant re-prioritization and resource allocation. While having this data is a great start, for the Inter-Agency Coordination Unit’s working groups to leverage the data towards their 4-year plans, and for emergency service and rapid response efforts, they also need a system that allows this data to be accessed, visualized, analyzed, and disseminated across their 200 partner organizations.

Allegro, a leading e-commerce platform in Central Europe, decided to invest in its own logistics and delivery services. Using its own fulfillment infrastructure, network of parcel lockers, and last-mile delivery services, the company aimed to improve consumer convenience and speed up deliveries. This meant that Allegro needed to have greater control over these services, to support their transition from an online to omnichannel player. The challenge in Allegro’s case was having the right analytics platform and tools in place to support their network expansion in 3 key areas: strategy, execution, and performance measurement. Specifically, the main goal was to drive an efficient and cost-effective growth strategy for its network of parcel lockers, a type of delivery that currently makes up a staggering 70% of deliveries in Poland.

领先的国际烟草公司菲利普·莫里斯国际公司 (Philip Morris International) 面临着烟头成为世界上乱扔垃圾最多的物品的挑战，每年丢弃 4.5 万亿个烟头。作为“我们的世界不是烟灰缸”全球倡议的一部分，他们的目标是扩大参与清洁活动的规模和范围。他们还希望提高人们对当地社区乱扔垃圾问题的认识，尤其是乱扔烟头的问题。挑战在于问题的严重性、对垃圾热点地区准确数据的需求以及有效监测反乱扔垃圾活动影响的要求。

Premier Utility Services 面临着管理现场作业的挑战，其中包括纽约州北部的大型燃气表检查和泄漏检测项目。该项目需要处理和管理大型数据集，其中包括超过 50 万个燃气表的数据。虽然 Premier 已向 Fulcrum 寻求数据处理和管理方面的帮助，但他们仍然需要一个能够大规模可视化和分析数据的解决方案。他们所需的应用程序非常复杂，因为它必须处理大量数据并为决策提供有用的见解。

Skyhook Wireless 最初是一家移动设备定位提供商，现在面临着管理和利用其定位服务生成的大量数据的挑战。这些数据用于提供基于位置的服务，例如在地图上精确定位设备的位置，随着该公司在全球范围内扩展其服务，这些数据呈指数级增长。挑战不仅在于管理这些数据，还在于将其划分为可用的部分以供分析。高时空精度的期望，曾经是一个县或一个城市的范围，现在是全球范围内的期望。此外，该公司还面临着满足企业日益增长的期望的挑战，这些期望需要详细的数据分析，例如一家麦当劳店与另一家店销售的汉堡数量。

伦敦大学学院高级空间分析中心 (CASA) 面临着识别、描述和定位最近经历高档化的伦敦社区的挑战。他们需要分解数据揭示的不同类型的变化。此外，他们的目的是预测哪些社区可能成为中产阶级化的下一个目标。最终目标是呈现并提供数据、代码和新颖的交互式可视化，作为支持城市政策和决策的综合工具。

该案例研究围绕一家私募股权公司美国证券公司进行，该公司正在考虑收购一家零售连锁店。在做出投资决定之前需要回答的首要问题是零售连锁店是否可以通过开设更多商店来继续盈利。该公司对两种扩张战略感兴趣：空白，零售连锁店将扩展到目前没有品牌存在的新市场；以及填充，即在零售连锁店现有的市场上开设更多商店。鉴于投标过程的竞争性和时间密集性，面临的挑战是在短时间内了解这些策略的潜在盈利能力。该公司还需要了解可能影响商店业绩的因素，例如距核心市场距离的影响以及其他潜在的混杂因素。

全球商业房地产服务公司 Avison Young 由于 Covid-19 大流行而面临重大挑战。零售业普遍放缓和永久在家工作政策导致对商业空间的需求急剧减少。这种情况极大地影响了Avison Young所属的商业房地产市场。然而，随着疫苗的普及，商业地产市场有望大幅反弹。预计许多人将返回购物、旅行、训练和享受家外的空间。 Avison Young 需要一种方法来可视化并了解当地政府辖区随时间推移的这些流动趋势，以便更好地针对预期反弹制定策略和计划。

Idealista 是一个在线房地产平台，面临着了解其网络流量趋势和模式的挑战。该公司注意到，西班牙沿海房产列表的网络流量中有 19% 来自外国人，其余 81% 来自国内受众。西班牙流行的口号“sol y playa en España（西班牙的阳光和海滩）”吸引着世界各地的人们到伊比利亚半岛投资房地产。 Idealista 希望更深入地研究这些数据，以识别有趣的趋势，并更直观地了解受众的偏好和行为。

Kroton, one of the largest private educational organizations in Brazil, was struggling with the processing and analysis of millions of records of government information regarding population segments and demographics. The lack of a visualization tool made it difficult for them to make fast and accurate insights, which was critical for efficient market analysis. They needed a platform that could provide specific information on educational branches and geomarketing resources, and could be integrated with their business intelligence dashboard, Qlikview. Previous software they tried had difficulty handling the large amounts of data.

BBVA Data & Analytics identified a gap in the market to provide location-based insights to small to medium enterprises (SMEs) in Spain, which drive a large percentage of the country's economic activity. They wanted to develop a solution that could answer questions related to Performance Management and Site Planning. Point of Sale (POS) card payment terminals provided a wealth of historical sales data, which was then aggregated and anonymized to ensure statistics on retail activity could not be traced back to individual merchants or transactions of specific customers.

The 7.1 magnitude earthquake that struck central Mexico on September 19, 2017, caused significant damage to the infrastructure of Ciudad de México (CDMX), posing unprecedented obstacles to response efforts. The earthquake destroyed 228 buildings in the city, with many more at risk of collapse, putting even more residents at risk. The immediate aim of the Commission for the Reconstruction, Recuperation, and Transformation of the City of Mexico was to rescue people trapped by the rubble and evacuate others in areas at risk of further collapses. However, the damaged infrastructure posed obstacles in terms of assessing citywide damage. The Commission needed a two-way digital resource where citizens could file property damage reports that provided local officials with crowdsourced data on where to allocate emergency resources.

Telefónica’s Smart Cities and IoT team needed to build a Smart Cities dashboard that could process and analyze data from thousands of Internet of Thing (IoT) sensors as actionable insights to enable their public sector customers to run their cities more efficiently and sustainably. They needed an integrated, FIWARE compliant platform to make large amounts of real-time data accessible to the general public and public administrators through data visualizations, interactive maps, and customized reports. The dashboard would focus on verticals most suited to optimization using IoT technologies: parking, street lighting, waste management, environment, transportation, and service monitoring.

Sistema.bio faced several challenges as they expanded their operations globally. They needed to visualize all existing and pending biodigester installations, over 15,000 existing digester locations on one map (and over 30,000 yet to come by 2023), to empower the staff to make informed decisions on their team resourcing and activities. They also needed to conduct market research and site selection for expansion plans. They needed to know where they currently have a strong market presence, and where they could be expanding. Exploring their existing customer base - such as through heatmaps - is a fantastic way to quickly build location into strategy. Lastly, they needed to connect their existing data pipelines and algorithms to optimize the activities of their field staff, whether that’s their credit, installation, sales or training teams. Most of these processes are currently managed in Salesforce.

SIL International and Ethnologue are adapting to a global landscape that is adopting new technologies and growing more interconnected by the day. As Ethnologue looks to be a more powerful resource across sectors, they need to keep pace with rapid technology growth and the need for more dynamic language intelligence. Given the spatial nature of language, where it is spoken and how it either shrinks or proliferates, the ability to visualize these 7,117 living languages was paramount to the educational component of Ethnologue’s mission. Historically, they had been using more static maps as a resource, which is natural given their literary roots. They would subsequently publish the maps online. And while this is certainly useful, especially at the more granular country level, it doesn’t provide a complete and living resource on where languages are spoken EXACTLY. It also lacks a level of interactivity which helps the project to transcend to the goal of language intelligence.

The Australian Football League (AFL) aims for around 3-4 percent growth in community engagement each year. Ensuring facilities are right in each area is an important aspect in attracting new players and retaining current players around Australia. Organisational effectiveness is important to ensure resources go to the right places. In each region, clubs and leagues make requests to the state and then to the national body for funding and the AFL must assess each application based on its merits. Local region managers are also required to make their case to local councils to obtain investment. Communicating the status of a region’s participation gives people on the ground the right starting information so they can take the right actions to improve participation. In the world of data driven decision making, the AFL needed a way to communicate quickly to local and state governments about their local needs. Communicating with local authorities using a standardised report that wasn’t tailored to a region made it more difficult to convey the AFL’s message.

国家可再生能源实验室 (NREL) 是美国唯一一家专注于可再生能源、商业化、开发和研究的联邦实验室。 NREL 面临的挑战是如何实现可再生能源的高渗透率，同时实现可靠性、弹性和可负担性的广泛目标。能源网的复杂性及其众多的发电机和可变负载，需要复杂的工具和可视化来理解和管理。可再生能源的一个根本挑战是其在空间和时间上的可变性和连续性，这对传统模型提出了挑战。问题是如何采用本质上连续且可变的现象，并将其拟合到离散模型空间中，无论是节点的还是区域的。最大的问题是如何确保资源得到正确的描述和保存。

桑迪飓风过后，纽约市 (NYC) 面临着扩展其在灾难发生后立即执行分析并为未来灾难做好准备的能力的挑战。该市迫切需要增强其地理空间分析能力，特别是在地图制作方面。主要挑战是找到一种用户友好性足以供任何分析师使用的工具，无论他们在地理空间分析方面的专业知识水平如何。目标是快速可视化数据并用它来为响应工作提供信息。该市还希望摆脱通过特定类型的工具进行分段分析，这限制了分析师充分利用和可视化数据的能力。

Posterscope 是电通安吉斯集团旗下的一家基于位置的营销机构，面临着利用位置智能创新品牌建设方式的挑战。该机构的目标是在适当的时机将品牌与户外 (OOH) 受众联系起来，使沟通更加个性化、情境化和相关性。面临的挑战是了解这些时刻的位置并使用这些信息来开发有效的通信解决方案。零售行业的发展超越了交易，任何接触点的激活、参与和交易都变得比以往任何时候都更加紧密。 Posterscope 需要适应这种变化，并利用位置和数据让零售业更具体验感。尽管电子商务快速增长，实体零售仍然是全球行业的重要贡献者。我们面临的挑战是将电子商务快速发展的概念（例如情境性和数据分析）应用到实体零售中。

美国按需配送领域的领导者 Postmates 面临的挑战是如何有效地将消费者与商家联系起来，并在几分钟内将任何商家的货物送到顾客家门口。该公司必须处理位置数据的复杂性，因为位置具有分量和意义。该公司必须了解客户的偏好在一年中、每周以及同一城市内不断变化。他们还必须应对在美国和墨西哥 300 个城市运送各种物品的挑战，从家具到深夜药品和尿布。

大加那利岛拉斯帕尔马斯市政公用事业公司 (SAGULPA) 是一家公共交通公司，面临着管理和优化其交通资源的挑战。他们可以访问多个位置数据源，但缺乏统一的平台来组织和分析这些信息。该公司希望更好地了解城市的出行模式，包括行程分布、旅行者的概况及其服务的使用情况。目标是利用这些信息来改善服务、减少交通拥堵并推广可持续的交通解决方案。