Bohme, a retail boutique, was facing several challenges in its operations. The company lacked a centralized reporting solution, which made it difficult to assess the performance of individual stores. This lack of real-time data insights was also hindering their purchasing decisions. The fast-paced nature of their business, which involves designing, making, stocking, and selling merchandise within 30 days, necessitated a more efficient and streamlined approach to data management.

Torpedo7, a successful online retailer in New Zealand, was facing challenges with its data management. The company lacked reliable, up-to-date information, which was crucial for decision-making. The decision-makers within the company were unable to effectively communicate their data due to the lack of a suitable platform. Furthermore, they were constantly waiting on 'the data guys' to generate reports, which was a time-consuming process. The company was in need of a solution that could provide real-time updates and a collaborative platform for sharing data.

Federated Media Publishing, one of the largest owned and operated real-time ad exchanges in the world, was facing several challenges. The data they were dealing with was complex and inconsistent across different office locations. This led to an overloaded data management team that was struggling to keep up with the volume and complexity of the data. Additionally, the company needed custom Key Performance Indicators (KPIs) that could provide better insights for executives. The lack of a unified platform for sharing data and automating mundane tasks further exacerbated these challenges.

H&R Block, a global tax services provider, was facing several challenges related to data management and reporting. The company had many disparate sources of information, which made it difficult to consolidate and analyze data effectively. This resulted in a significant amount of time being spent on building reports. Furthermore, the company's leadership lacked critical data insights due to the fragmented nature of the data sources. The need for a solution that could provide a unified view of the disparate data sources and offer greater transparency across teams was evident.

Poste Italiane, the Italian postal service, has evolved into an online marketplace offering financial products, logistics, insurance services, and online payments. To maintain its central role in the ever-changing world, Poste Italiane prioritizes innovation to support new products, processes, and customer experiences. They saw an opportunity in the market to support companies within their supply chain with customer acquisition and retention. However, the traditional postal system is bound together by an expansive and complex supply chain, resulting in tech sprawl where there are too many programs that are not interoperable. This means the programs can’t communicate with each other and share data. With the plethora of programs and lack of interoperability between them, the management of the accounts and the rules on earning rewards are not clear.

Mindtree, a technology consulting and services company, identified two major challenges in the retail and banking sectors. In the retail sector, the decreasing rate of redemption in loyalty programs was a significant issue. Nearly $100 billion worth of points remain unused annually, which translates to missed opportunities to engage consumers and a balance sheet liability when compared to the cost of marketing and maintaining the program. In the banking sector, the merchant onboarding process was tedious and time-consuming, taking more than 20 days. The process involved high risks, sizable investment in external agencies for third-party verifications, and lacked a standardized system to ensure vendors comply with regulations such as anti-money laundering, Know Your Customer, and Know Your Customer’s Customer.

Dubai, under the vision of Dubai 10X, aims to stay 10 years ahead of other world cities in terms of technology. One of the initiatives under this vision is the Digital Silk Road, a platform to ease worldwide trade. The platform aims to solve the global trading system’s key issues–high costs, low trust, and lack of transparency–with blockchain technology. However, the process of registering to import or export goods in Dubai was neither smooth nor easy. It was a lengthy process that touched on many authorities. For export, the process took even more steps. All these processes were paper-based and time-consuming.

The U.S. insurance industry was facing a significant challenge in regulatory reporting. With 50 state regulators requesting data in various formats, often with short deadlines, insurers were struggling to keep up. The data they were able to submit was often outdated by the time it was reported, making it less useful for regulators. The industry needed a more efficient and secure system for data collection and sharing. The American Association of Insurance Services (AAIS) decided to tackle this problem by inviting carriers and regulators to brainstorm a solution using design thinking. The group came up with the idea of a blockchain network.

Abu Dhabi, one of the richest cities in the world, was facing a challenge with managing the land deeds for the 375 sq. miles on which the modern cityscape is built. The process of creating a land deed record involved multiple steps and could span up to six years to complete. There were multiple external stakeholders and internal municipal departments involved at any given stage of the land deed process, and they all leveraged disparate systems and applications. This led to friction in document sharing and potential for errors or confusion among the stakeholders in the current paper-based ecosystem.

Rwanda, the world's largest supplier of tantalum, a rare mineral used in devices like smartphones and laptops, faced a challenge in proving that every bag of tantalum ore was mined, transported, and processed under OECD-approved conditions, without any child or slave labor. The existing tracing methods involved tagging materials and filling in paper forms, which met the OECD rules but didn't provide actual traceability. It also generated a costly mountain of paper with room for errors or fraud. The challenge was to create a system that ensures tantalum is mined, transported, and processed under approved conditions with an unbroken chain of custody.

The process of onboarding B2B suppliers is slow, costly, and fraught with risks and errors. It involves a lot of paperwork and verification from various departments and third parties. This creates friction and delay between buyers and sellers. The process is also difficult to keep up with when any vendor undergoes a move, reorganization, merger, or acquisition. The whole process takes around 45 to 60 days to approve a new supplier. IBM and Chainyard saw this as a problem that blockchain could solve.

Large organizations have always struggled to get visibility into their data. Frequently, data comes in many sources and formats while also being siloed across the organization. DLTs add ledger data and metadata to the mix. Similarly, consortiums need to interoperate with each other. Yet organizations often use disparate tools for logs, metrics and tracing. All these are deployed on different clouds or on-prem. Then they build their own tools to take data from the ledgers and put it into a SQL database. Consortiums may include competitors who don’t trust one another, so they don’t want to share data. But, if no one shares data, it can be challenging to determine if an organization has a problem or if it lies in the network.

In Cambodia, 78% of the population does not have a bank account, yet over half own a smartphone. Despite the stability of the native currency, the Khmer riel, most transactions are conducted in American dollars. The National Bank of Cambodia (NBC) wanted to modernize the country's retail payments system, promote the use of the national currency, and reach the unbanked population. The existing banking systems used by various banks and third parties often had compatibility issues, leading to inefficiencies. The NBC was interested in exploring whether a blockchain-based system could handle transactions faster and at a lower cost, thereby promoting wider use of the riel.

Honeywell Aerospace, a global provider of avionics, engines, systems, and services, wanted to create an Amazon-like marketplace for used aircraft parts. The existing process of purchasing used aircraft parts was outdated and time-consuming, often taking days or even weeks to complete a transaction. The websites put up by vendors were basic and lacked crucial information such as a part’s condition, pricing, and availability. The main challenge was the lack of trust in online transactions due to the heavily regulated nature of the aviation industry. Each part sold required certification from the U.S. Federal Aviation Administration and other agencies, and each part must be documented with a complete history of its ownership, use, and repairs. The goal was to cut purchasing time from days or weeks down to seconds and to connect each physical part to its digital pedigree.

Credit unions are increasingly being targeted by fraudsters, particularly through the call center channel. Traditional knowledge-based authentication questions have become vulnerable, leading to a rise in account takeover attacks. The process of member identity authentication across various touch points, including the call center, drive-up, and lobby, is fragmented and time-consuming, creating easy targets for fraudsters and causing frustration for consumers. The challenge was to find a more secure anti-fraud solution that could streamline the authentication process, reduce operational costs, and improve the member experience.

Bosch Research was exploring the Economy of Things, where IoT devices will need to buy and sell to one another. The first challenge was creating a secure platform to support automated micropayments between 'things'. This suggested distributed ledger technologies (DLTs) such as blockchain. However, blockchains don't scale well. Reaching consensus on a transaction takes time. And tiny IoT devices have limited power, memory, processing, and connectivity. They certainly can't run heavy code. The question was how any blockchain could possibly work around all these constraints and how Bosch could help pioneer the standards needed for IoT devices to buy and sell among themselves.

Change Healthcare, one of the largest independent healthcare technology companies in the United States, operates one of the largest healthcare networks in the country, linking 900,000 doctors and 5,500 hospitals to 2,200 payers. In 2017/18, the network handled nearly 14 billion healthcare transactions and claims worth $1 trillion. However, the American healthcare system, which Change Healthcare is a part of, is plagued by inefficiency, fraud, and waste. Patients, providers, and payers seldom see complete, up-to-date healthcare records. Incompatible file formats, data silos, and privacy concerns all hamper the free flow of information. Consulting firm McKinsey estimates that U.S. healthcare could save up to $450 billion a year by using updated processes and technology. Change Healthcare wanted to play a leading role in this transformation, by extending its Intelligent Healthcare Network with blockchain technology to provide a faster, better experience for all.

The Philippines is a rapidly emerging economy with a population of over 100 million. However, one third of its population lives on less than $2 a day and remains unbanked. This means that 35 million Filipinos have severely limited access to both the domestic and global financial ecosystems. This is a significant problem when up to 10% of the Philippines’ GDP is made up of international remittances sent from overseas workers to family members across the country. Unionbank of the Philippines, one of the largest banking institutions in the country, sought to tackle this challenge by partnering with ConsenSys Solutions, Microsoft Azure, Kaleido, Amazon AWS, ConsenSys Diligence and seven rural Philippine banks to create an inter-rural bank payment platform using Enterprise Ethereum. The challenge of facilitating financial inclusion was to encourage the financially excluded, traditionally located in rural areas, to begin and to continue to engage with financial systems. The key to this engagement was determined to be a partnership with the existing 492 rural banks located amid small rural communities across the country.

Greenfence Consumer, a company that creates blockchain-based mobile platforms for brands and retailers, was struggling to build a scalable, easy-to-use blockchain platform. The company wanted to change the way brands engage with consumers by using blockchain technology. However, their initial attempts to deploy a blockchain solution proved challenging. They had limited options: they could deploy on the public chain, which presented several problems when looking at transaction costs and speed, or they could deploy a private version of the Ethereum blockchain. They chose to deploy on a public Ethereum test network for their first test, but they were looking for a solution that could provide a simple, secure, stable, scalable, and cost-effective platform on which to deploy their solution.

Managed care organizations, health systems, physicians, diagnostic information service providers and other healthcare stakeholders typically collect provider demographic data in separate IT systems maintained by each organization independently. This promotes vast inefficiencies and duplication of efforts, while also potentially reducing data quality. Industry estimates indicate that $2.1 billion is spent annually across the industry chasing and maintaining provider data.

Experian Marketing Services was facing challenges in providing its clients with high-quality, highly customized reports in short time frames. The company was dealing with large, inconsistent client data files that spanned terabytes of data and contained a variety of data formats. The legacy system used for processing the data often required intervention from engineering and delivery resources to meet customer requirements. This process was lengthy and involved custom coding, multiple and complex analytical tools, and expensive data transformation resources. Experian wanted to lower processing and analysis costs, produce final products for clients more quickly, and improve overall customer satisfaction.

Great Clips, the world’s largest and fastest-growing salon brand, was facing challenges in its growth strategy. The company's success is based on rapidly opening new stores in the right locations and markets. However, the process of identifying these locations based on potential customer base, demographic trends, and sales impact on existing franchises was taking too long and was expensive. The process required analyst resources to manually access, integrate, and analyze multiple sources of data to produce a report for a single location. This delay was risking the loss of prime sites to competitors and alternative real estate interests. Additionally, costly external contractors were being used to deal with the backlog.

Southern States Cooperative, a large farmer-owned cooperative in the United States, wanted to optimize its marketing efforts, particularly its high-value direct marketing activities. However, the company faced significant challenges. It lacked a way to consolidate customer and marketing data from multiple sources across the company for analysis. It also lacked sophisticated tools to drive marketing analytics, relying instead on generic productivity tools like Microsoft Excel. This lack of access to relevant data meant that direct mailings were not targeted effectively, leading to unnecessary expenditure.

TargetSmart Communications, a political data firm, was tasked with building voter propensity models and scoring national files for political fundraising campaigns for the Obama for America Campaign. The company needed to process millions of records of data from dozens of data sources, including national, state, county, and city records, to identify voters, track their tendencies, and accurately count and call upon unregistered voters prior to an election. The company was using open source software solutions to merge multiple databases, two of which consisted of 200 million voters each. However, the lack of a universal format for government data for various voter categories and the need for continuous data aggregation, updating, cleansing, and enhancement with demographic profiling data presented significant challenges. The company's choice of data processing tools was leading to a troubling lack of efficiency, accuracy, and reliability.

AAA National wanted to better support its member clubs in selling additional products to existing members, finding new members in each of their territories, and ensuring that brick-and-mortar office locations were optimally located based on club member demographics and drive-times. The process of gathering and analyzing the necessary data was time-consuming and complex, often taking up to three days to generate a complete and accurate data set for analysis. The data was sourced from different systems, making it difficult to match and blend with third-party demographic and census data. The use of multiple tools to work with the data further complicated the process and increased the potential for errors.

Rent-A-Center, a leading retail company in North America, was facing challenges in creating maps for their 3,000 stores. The process was manual, involving a lot of clicking, joining, queries, and sub-queries. This was time-consuming and inefficient, taking up to 12-1/2 weeks to complete. The company needed a solution that could streamline this process and make it more efficient.

Schneider Electric, a global specialist in energy management, was facing a challenge in identifying its high-potential customers and deploying sales resources efficiently. The company's manual approach to determining how and where to deploy its sales resources was time-consuming and inefficient. Sales operations and more than 20 sales managers would collaborate with the analysis team to collect data and evaluate numerous factors related to each customer account, including account size, vertical market, and growth and purchase history. This process was not only slow but also resulted in the sales team waiting for the information it needed to start the new year, often not receiving it until February.

Novus, a leading advertising agency, has been experiencing significant growth, expanding both its client base and the range of services it offers. As a result, the complexity of data usage and reporting has increased, both internally and externally. The company was seeking a fast and efficient way to process the hundreds of variables involved in planning and measuring effective media campaigns. The continuous evaluation of success and application of optimization techniques across a universe of potentially more than 3,000 publishers for each client became cumbersome. It was increasingly important to be able to track progress and outcomes in an automated way.

The rise of e-commerce has led to the closure of many brick-and-mortar stores, with Americans spending over $400 billion a year online. However, the online shopping experience is largely transactional, lacking the human interaction and emotion that comes with physical shopping. Hush, a top social commerce app in the United States, aims to bring the social aspect of shopping to the digital world. The company believes that shopping is a social experience and that many purchases are experiential and emotional. This is particularly true for beauty products, Hush's focus, where people want to interact and talk with like-minded individuals about what they're buying.

Amaysim, Australia's largest MVNO with over 600k customers, was dealing with a massive amount of data. They had over 10 billion call data records to be analyzed, with 20-30 million call data records added daily. The velocity and complexity of data were high, with multiple data sources including Livechat, Zendesk, call data records, Google analytics/Website data, Point of sale data, and Exact target. The company had a small analytics team of three people covering a wide span of functions. They needed a solution that would enable line of business users to quickly build on a baseline of analytics, solve their own specific business problems quickly, and not have to wait on Business intelligence teams.