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DOTLUX, a German LED manufacturer, was facing challenges in managing its logistics processes due to rapid company growth and a complex import process. The company was operating in a highly dynamic market environment and had a wide range of products, which were mostly manufactured in collaboration with production partners in China. This meant that a majority of the company’s logistics operations involved forwarding freight from the Far East. The logistics had to run separately for each product area, with product managers coordinating with external production partners in China, the internal DOTLUX sales team and warehouse departments, and the German and international customers. This resulted in a lack of an overarching view of freight transports and deliveries, and a significant amount of time was being invested in managing the supply chain, which was not in line with the company’s rapid growth goals.

EcoSense Lighting, a Los Angeles-based architectural lighting solutions company, faced a significant challenge in coordinating its global team. The company, which produces both made-for-stock and custom high-quality LED lighting for clients such as Marriott, Tesla, and Burberry, required a supply chain that consistently delivered on time. However, with team members spread across the United States, China, and Hong Kong, maintaining alignment on shipments was proving to be a daunting task. The strict deadlines of large architectural projects further compounded the issue, making efficient communication and collaboration crucial for the company's success. The company's Logistics & Fulfillment Manager, Andreas Andrea, was in search of a platform that could centralize all shipment communication, data, and documents to align his global team and suppliers.

Ergobaby, a leading consumer products company, was facing challenges with its complex supply chain. With over 10 global suppliers spread across China, India, and Vietnam, visibility into logistics milestones and other business-critical data was crucial for its growth and success. The company had outgrown its manual supply chain processes which primarily involved email threads and Excel spreadsheets. Furthermore, the company's product announcements on social media channels were tightly tied to cargo arrival dates, adding another layer of complexity. Ergobaby needed a logistics partner that could optimize their entire supply chain, increase visibility, and enhance collaboration at all points of the process, regardless of location.

Fairphone, a social enterprise that designs, produces, and sells smartphones built from sustainably sourced materials and fair labor practices, faced several challenges in its supply chain. The company needed a logistics partner that could provide visibility across its entire supply chain, help offset CO2 emissions to meet its sustainability goals, and provide a specialized team to manage shipments at every step. Prior to partnering with Flexport, Fairphone was dealing with stock shortages and lack of visibility of shipments from the moment of factory pickup. The supply chain team was spending a significant amount of time sourcing vital information about shipments, causing major product launches to be fraught with worry about stock availability and timely arrival.

GP Cellulose, a division of Georgia-Pacific, is a leading producer of paper pulp materials, operating four mills in the southeastern United States and serving customers in over 75 countries. Despite being the second-largest exporter in North America, GP Cellulose faced significant challenges in managing its international shipments. The company's logistics, production, and customer service teams were grappling with disparate systems, leading to an overwhelming volume of emails and spreadsheets. This lack of integration hampered productivity and provided little visibility to mitigate errors and improve supply chain performance. Furthermore, GP Cellulose needed clear, actionable data to optimize performance internally and with its ocean transportation partners. The company was also undergoing a digital transformation initiative, aiming to standardize technology systems and processes for its supply chain, eliminate manual and low-value tasks, and improve the customer experience.

Gerber, a leading manufacturer of commercial and residential plumbing fixtures, faced significant challenges in managing its supply chain. With the majority of its supply shipping over the ocean, maintaining visibility of the supply chain to manage customer expectations and warehouse staffing requirements was a constant issue. Gerber imports thousands of container shipments a year from its suppliers in China and Mexico into the United States, and the demand for its products fluctuates. The company also sought greater visibility into what was driving its accessorial costs to optimize performance on the road and in its warehouses. Gerber's U.S. Transportation Manager, RoxAnne Thomas, described operating the company’s supply chain as a continuous balancing act of supply and demand, with the goal of maintaining as little footprint as possible to keep costs low for buyers.

Horizn Studios, Europe’s leading smart luggage brand, faced significant challenges in its early stages. As the first vertical player in the luggage industry, the company struggled with end-to-end visibility and managing distribution due to scheduling and communication issues. These challenges were exacerbated by the need to build trust with partners and customers as a young, rapidly growing brand. To succeed, Horizn Studios required accuracy, control, and reliability from its supply chain. The lack of visibility and control over the shipping process was hindering the company's growth and its ability to maintain a consistent stock level.

Intermax, a technical outerwear manufacturer based in Seoul, South Korea, faced significant challenges in its supply chain operations. The company, which has offices and factories across Vietnam, prioritizes getting products to its customers quickly. This requires importing materials from various countries before production can commence. In this process, Intermax was constantly seeking ways to gain efficiencies and reduce logistical lead times. However, like many Asian manufacturers, Intermax relied on its customers to choose the freight forwarder for shipping, leading to concerns about new processes, uncertainty, and potential impacts on time and cost. In 2016, one of Intermax's customers faced shipping issues with a production line, prompting the customer to suggest using Flexport's services. Despite initial skepticism about partnering with a new freight forwarder, Intermax decided to give Flexport a try.

ASDA, one of the largest British supermarket chains, faced a challenge in expanding their 'toyou' parcel service. Initially, the service was available in 639 locations within their estate. However, ASDA aimed to grow this number to 5,000 locations by incorporating external drop boxes closer to their customers, rather than relying solely on their traditional estate, which was typically a 10-minute commute for consumers. To kickstart their expansion plan, ASDA needed location data and insights to understand the key drivers for the site selection of new click-and-collect locations before deployment. They also needed to understand the proximity to target demographic and socioeconomic segments, such as universities.

Avison Young, a global commercial real estate services firm, faced a significant challenge due to the Covid-19 pandemic. The widespread retail slowdown and permanent work-from-home policies led to a drastic reduction in the demand for commercial spaces. This situation greatly impacted the commercial real estate market, which Avison Young is a part of. However, with vaccines becoming increasingly available, the commercial real estate market was expected to experience a sharp rebound. Many people were anticipated to return to shopping, traveling, training, and enjoying spaces outside their homes. Avison Young needed a way to visualize and understand these movement trends across local authority districts over time to better strategize and plan for the expected rebound.

The team at Bumble was seeking opportunities to expand in under-penetrated markets. Traditionally, they gauged their market presence by looking at monthly and daily active users. While this gave them an idea of their user base size in a particular market, it did not provide a clear picture of their actual market penetration. For instance, markets with large populations like the US, China, and Brazil naturally have larger user bases. However, the number of active users does not necessarily reflect the company's market position. Therefore, Bumble needed a more accurate method to estimate their total addressable markets (TAM) and market penetration.

During the COVID-19 pandemic, the Center on Rural Innovation (CORI) was faced with the challenge of analyzing disparity levels across the United States to identify areas in greater need of support. The pandemic had a significant impact on rural communities, and there was a pressing need to understand the extent of this impact. The challenge was not only to gather relevant data but also to analyze and present it in a way that would provide clear insights into the situation. This included identifying school districts impacted by the lack of broadband availability and counties facing significant employment risks due to the pandemic.

Clear Channel Outdoor, one of the world's largest outdoor media companies, faced a significant challenge in their operations. They were using mobile location data to link the physical and digital worlds, identifying devices exposed to their Out-of-Home (OOH) panels and collecting these insights within their RADAR® product. However, they encountered a problem in making this data easily accessible to advertisers for campaign planning. The challenge was to create a solution that would allow advertisers to easily access and utilize the insights derived from the mobile location data collected by Clear Channel Outdoor. This was crucial for the advertisers to plan their campaigns more effectively and reach their target audience more efficiently.

The financial technology (fintech) sector faces a significant challenge in recognizing the existence and availability of location data and its potential benefits. The sector has a wealth of internal datasets and monitoring systems that could be enhanced with the integration of location data. Particularly in the field of anti-money laundering, the combination of location data with financial data could be instrumental in aiding law enforcement and identifying illegal activities. However, the awareness and understanding of how to incorporate this data into day-to-day operations remain a significant hurdle. Additionally, the potential of location data extends beyond anti-money laundering, offering opportunities in marketing and credit risk management by providing insights into where people live and the communities around them.

Enveritas, a non-profit organization, was founded in 2016 with the mission to eradicate global poverty in the coffee sector by 2030. A significant part of this mission involved tracing the journey of coffee from its source to the consumer. This process not only required identifying the geographical locations where the coffee was grown and processed, but also understanding the social, environmental, and economic conditions prevalent in those places. The challenge was to create a comprehensive and dynamic visualization of the complex types of coffee based on the ECX classification system. The organization needed a user-friendly solution that could provide a clear and accessible representation of the coffee supply chain.

The Valencia region in Spain, a popular destination for both local and international tourists, is home to over 340 beaches. During the de-escalation phase, the region was receiving a high number of visitors. The Generalitat Valenciana, the government of the autonomous region of Valencia, identified a challenge in managing the beach capacity to ensure the safety of the visitors. They needed a tool that could provide real-time information about the beach capacity to the visitors. The tool needed to be mobile-friendly as most visitors would likely access the information on their mobile devices.

Google's BigQuery was facing a challenge in the field of geospatial analysis. The traditional hardware and software used for geospatial analysis were limiting the potential of BigQuery. The constraints of the existing infrastructure were hindering the scalability and performance of geospatial analysis. Additionally, the process of integrating geospatial data was cumbersome and time-consuming. Users were often required to perform administrative tasks and reference tables, which were considered 'boring' but necessary. The challenge was to enhance the geospatial analysis capabilities of BigQuery and make the integration of geospatial data more efficient and user-friendly.

Spatial data analysis is at a critical juncture. Over the past decade or so, customers have had to manage their own infrastructure, including the installation and maintenance of their GIS software. This could be on a laptop, desktop, or even a mainframe, but the responsibility of determining the size of the computer, the CPU cycles needed, and the storage capacity required fell on the customer. This process was not only time-consuming but also required a significant amount of technical expertise. Additionally, customers had to find and prepare the datasets they needed for their analysis, which could be a challenging and costly process.

Hodges Ward Elliott, a commercial real estate investment company, was looking to leverage data science to gain a competitive edge in the real estate market. The company recognized the potential of data science in real estate, an industry that has traditionally been slow to adopt such technologies. The challenge was to find a way to effectively use data science to understand the preferences of groups of people and how these preferences change over time. This understanding is crucial to predicting trends in real estate, as it can provide insights into where people want to live, shop, and work. However, obtaining and analyzing relevant data was a significant challenge due to the lack of readily available data in the real estate industry.

Hodges Ward Elliott, a real estate company, was facing a significant challenge in creating data-driven maps, a fundamental aspect of their daily operations. The process was labor-intensive and time-consuming, often taking the graphics department 3-4 days to produce a single map. The introduction of the data science team and the use of open-source tools like Leaflet improved the situation, but it still took four hours to create a high-quality map. The company was looking for a solution that could further streamline this process, reduce the time taken, and make it easier to create and iterate on these maps.

i-sense, an Interdisciplinary Research Collaboration (IRC) funded by the Engineering and Physical Sciences Research Council (EPSRC), aims to build digital sensing systems to identify and prevent outbreaks of infectious diseases and antimicrobial resistance. However, they faced a challenge in interpreting the daily or weekly data related to the COVID-19 pandemic response published by Public Health England, National Health Service (NHS), and the Office of National Statistics (ONS). The data was often difficult to understand, making it challenging to evaluate the effectiveness of the system in place.

idealista, an online real estate platform, was faced with the challenge of understanding the trends and patterns in their web traffic. The company noticed that a significant 19% of their web traffic for Spanish coastal property listings was coming from foreigners, with the remaining 81% from a national audience. The popular Spanish slogan “sol y playa en España (sun and beach in Spain)” was attracting people from all over the world to invest in property in the Iberian Peninsula. idealista wanted to delve deeper into this data to identify interesting trends and gain a more visual understanding of their audience's preferences and behaviors.

Instacart, a grocery delivery and pick-up service, was facing a challenge in its business expansion strategy. The company's approach to connecting retailers with customers was conservative, limiting its growth potential. The company was not fully utilizing the potential of its app to connect customers with their preferred grocers, which was affecting customer engagement and spending. Furthermore, the company was not fully capitalizing on the opportunity to help its retail partners reach new customer bases. The challenge was to find a way to be more aggressive in their growth strategy, increase customer engagement and spending, and help retailers reach new customers.

Jefferies, a global investment banking firm, was grappling with the challenge of making informed investment decisions and advising their clients effectively. Traditional data strategy and research were not formally integrated into most of their research, often being treated as an afterthought. The firm was also struggling with the time-consuming process of assembling information, which could take months or even years. Furthermore, the firm was trying to shift from making assumptions to making decisions based on grounded fundamental observations. The challenge was to find a key question that drives the key variable that a human is deciding is incredibly important, and shift it from being something that was previously assumed, to something that probably still has some assumption around it but can at least be based on a grounded fundamental observation.

The challenge revolves around understanding the social segregation in cities, particularly in the United States. The traditional understanding of segregation is based on geographical locations, often characterized by the stark contrast between rich and poor areas within close proximity. However, this perspective fails to consider the 'why' behind segregation, focusing solely on the 'where'. The challenge is to challenge this traditional notion of segregation by using high-frequency location data to understand the reasons behind segregation. The data gathered from 11 of the most populated metropolitan areas in the US revealed that on average, around 75% of the people we interact with daily live more than 15 kilometers away. This suggests that to understand segregation, we need to go beyond geographical locations and start considering the reasons behind it.

In the aftermath of Hurricane Sandy, New York City (NYC) was faced with the challenge of scaling its ability to perform analytics immediately after a disaster and in preparation for future disasters. The city had a significant need to enhance its geospatial analytics capabilities, particularly in terms of map-making. The primary challenge was finding a tool that was user-friendly enough to be used by any analyst, regardless of their level of expertise in geospatial analytics. The goal was to quickly visualize data and use it to inform response efforts. The city was also looking to move away from segmenting analysis by a specific type of tool, which limited the ability of analysts to fully utilize and visualize the data.

Philip Morris International, a leading international tobacco company, is faced with the challenge of cigarette butts being the most littered item in the world, with 4.5 trillion discarded each year. As part of their global initiative 'Our World Is Not an Ashtray', they aim to increase the scale and reach of their participation in clean-up activities. They also want to raise awareness of the issues of littering, and cigarette butt littering particularly, in local communities. The challenge lies in the sheer scale of the problem, the need for accurate data on litter hotspots, and the requirement to monitor the impact of anti-littering activities effectively.

Posterscope, a location-based marketing agency of Dentsu Aegis Group, was faced with the challenge of innovating the way brands are built by leveraging location intelligence. The agency aimed to connect brands with Out-of-home (OOH) audiences at the right moment, making communication more personal, contextual, and relevant. The challenge was to understand the location of these moments and use this information to develop efficient communication solutions. The retail industry was evolving beyond transactions, with activation, engagement, and transactions becoming closer than ever at any touch point. Posterscope needed to adapt to this change and make retail more experiential using location and data. Despite the rapid growth of ecommerce, physical retail was still a significant contributor to the global industry. The challenge was to apply the concepts that made ecommerce grow so fast, such as contextuality and data analysis, to physical retail.

The challenge faced by Postmates, a leader in on-demand delivery in the US, was to efficiently connect consumers with merchants and deliver goods from any merchant to the customer's door in minutes. The company had to deal with the complexities of location data, as location carries weight and meaning. The company had to understand the preferences of customers which varied throughout the year, the week, and within a city itself. They also had to deal with the challenge of delivering a wide variety of items, from furniture to late-night medicine runs and diapers, across 300 cities in the US and Mexico.

The Sociedad Municipal de Aparcamientos de Las Palmas de Gran Canaria (SAGULPA), a public transport company, was facing a challenge of managing and optimizing their mobility resources. They had access to multiple location data sources but lacked a unified platform to organize and analyze this information. The company wanted to better understand the mobility patterns in the city, including the distribution of journeys, the profile of the travelers, and the usage of their services. The goal was to use this information to improve their services, reduce traffic congestion, and promote sustainable transport solutions.