The wine industry was facing a significant data gap. Consumers around the world were constantly sharing their thoughts and feelings about wine, how they buy it, and where they're drinking it, resulting in vast quantities of data. However, there wasn't a good way to track that digital trail to meet consumers where they are. The industry needed a way to harness this data and use it to their advantage. Additionally, there was a fear factor around data, partly due to privacy and security issues. Wine people can also be shy about their lack of knowledge and bandwidth to learn more. There was also a romanticized element of the wine lifestyle that seemed at odds with the concept of data.

Many organizations are either reluctant to fully embrace a data-driven culture, or simply unsure how to get started. One of the first hurdles blocking progress toward full information integration is the belief that data integrity requires extremely limited access. The legacy of this previously messy process is the reluctance of modern organizations to release access to data to the entire organization. Even where staff may want personal involvement, that ongoing fear of losing control is unrelenting. Leaders may believe the perfect solution is to designate a small group of database administrators and allow staff the opportunity to request extractions or factfinding projects. This solution almost always results in bottlenecks and a distancing from the concept of including data in decisions.

At UOB, the traditional approach to data discovery was a per-project process used for regular reporting purposes. Extracting data for these reports was often manual and time-consuming. The reports created were also often one-dimensional and not in real-time as there were limitations when analyzing historical data on Excel files. The bank wanted to make data discovery more accessible, insightful, and relevant to business real-time needs. They also wanted to create a culture driven by data analytics across the organization.

The University of Worcester was facing a challenge in meeting the global demand for data specialists through its existing data-driven decisions module. The university wanted to give its students a better understanding of data analysis and data mining by enabling them to visualize the results of their work. Additionally, the university wanted to increase student marketability by providing hands-on experience of commercial software. The challenge was further compounded by the Covid-19 pandemic, which forced the university to transition to distance teaching.

The challenge faced by mesur.io was to create a platform that could collect, analyze, and present meaningful data for small and mid-sized farms. The agricultural monitoring equipment available in the market was primarily designed for large-scale agriculture and did not provide actionable insights for smaller farms. The founder of mesur.io wanted to create a solution that was affordable and easy to use for the majority of farms worldwide. The solution needed to provide real-time data on soil conditions and offer recommendations based on historical trends. The challenge was to create a user interface that could present the data in a meaningful way and provide real insights rather than just displaying graphs.

DCH, a leading FMCG and Pharmaceutical company, operates across 12 Asian economies and a wide range of product categories. With such a widespread operation, DCH realized that it needed to sustain a deep understanding of both its customers and its business. Gaining such insights would help it work more efficiently today and plan more comprehensively for the future. Data was the key to obtaining this business intelligence and DCH realized that to create a firm basis for the business, it needed to update its Enterprise Resource Planning solution. DCH wanted to make positive use of its ERP data so, as part of the ERP upgrade project, it sought a new reporting and data analysis solution.

ENI’s upstream activities are complex with more than 160 natural gas and oil extraction plants located worldwide sending performance and operations data on a daily basis. Keeping track of the overall situation is essential for managing maintenance operations and ensuring that the company reaches its targets. Without a dedicated platform, the data sent by the plants used to be collected via email and analyzed manually, using standard spreadsheets and occupying vast amounts of time and resources. Managers were only able to see an overview of production towards the end of the working day, via a PDF sent by email, with limited possibility for in-depth analysis. ENI needed to improve the control and analysis of this information, not so much for operations but for managerial purposes. The objective was to improve the timeliness, quality and granularity of the data, seeking to create a platform that provided a good customer experience and also enabled the analysis of historical data to allow managers to monitor performance more effectively.

Radiall, a world leader in the electronic connectors industry, was facing challenges with its BI ecosystem. The company wanted to become a data-driven organization, but it was struggling with a number of tools and data quality issues. The company's objective was to reduce the number of tools and data quality issues and deploy a data culture within the group.

Puget Sound Energy, a Washington State-based company, supplies electrical and natural gas services to approximately four million Americans daily. The majority of the business operations are run on SAP, making it crucial to limit outages when implementing SAP changes. To ensure smooth transitions, data must be accurately placed in the right systems at the right time to prototype, test, and implement new SAP implementations. The company has 12 SAP instances and is constantly adding new products, making the process of updates and data synchronization a significant challenge.

Tasmania Health was facing a challenge where their entire data structure was reliant on a single person, creating a single point of failure. This was problematic as it created a risk of data loss or mismanagement if that person was unavailable. The organization was also separated into silos, with each structure having its own 'data guru'. This led to a disjointed system where insights into processes and outcomes were not possible. The organization realized the need for a more centralized data process and remove data confusion. However, the transition to a centralized system was met with resistance due to fears of losing the go-to person for data in each region.

Multipack LJM is a company that provides packaging services for a diverse range of products including food, pharma and FMCG, with major brands such as Nestle, Kellogg’s and Coca-Cola as their clients. The company faces the challenge of responding to changes in demand in real-time. This involves adjusting and optimizing production to meet the evolving needs of their clients. The challenge is further compounded by the need to manage the procurement of raw materials in line with the changing requirements of their clients.

Nationwide Building Society wanted to transition from a report-centric culture to a data-driven one. The goal was to make data accessible to all 19,000 employees, providing more visibility into business processes. The company aimed to create a 'Fit to Fly' data-enabled culture, where data is at the heart of decision-making and operations.

SML Group, a global branding and retail solution provider with production sites and sales networks in over 30 countries, faced the challenge of consolidating data from various sources. The company needed to provide timely reports that would support its operations and management. The vast geographical spread of the company's operations made it difficult to manage and monitor the levels, age, and condition of stocks at different production sites. Additionally, the company needed a comprehensive view of its global sales performance.

The Science Centre Singapore was facing challenges in forecasting and marketing due to the lack of a centralized data system. The data was stuck in Excel spreadsheets, making cross-company access cumbersome. The organization was striving towards being a data-driven organization as part of its digital transformation journey. The goal was to leverage various platforms to create targeted digital experiences and promote user adoption of data analytics among the staff. The organization was dealing with complex data due to different attractions, workshops, and ticketing platforms. The old setup had individual officers responsible for their own data, leading to siloed insights and cumbersome data access.

Monash IVF, a major presence in the highly regulated sector of assisted reproductive technologies, was facing a technical challenge due to the volume of data produced through a complexity of systems, many of which did not talk to each other. The resultant inconsistencies were making it difficult to get holistic, vigorously audited or accurately reported outcomes. The company had two strategic objectives. First, to simplify how the data was captured, handled and integrated before moving data from where it naturally lived in the IT function into the business operation. Second, to gain additional insight from a marketing perspective.

Energy Safe Victoria (ESV) is responsible for the safe generation, supply, and use of electricity, gas, and pipelines across the state, serving approximately seven million people living in Victoria. One of its priority areas is ensuring safety audits and inspections are thorough to meet its responsibility as a technical and safety regulator. However, ESV faced two key challenges: accurate data collection and the availability of resources for analysis to ensure compliance with expected safety standards. Teams often had to deal with a high volume of data across work sites in remote locations. Additionally, the efficient generation and quality of data analysis required to meet ESV’s safety audit goals were also a challenge. During an audit, field teams collected data manually, often on paper and across several devices and machines. These tasks were time-consuming, clunky, and onerous, and could lead to possible errors. Inaccuracies could then delay risk assessments and outcomes which affect the monitoring of trends, anomalies, and identifying systemic behavior and issues.

Burger King Russia, a leader in the Russian fast food market, has been rapidly expanding its operations, launching 100 new restaurants every year since 2015. The chain now consists of 760 outlets across 300 cities and six time zones. The main goal of Burger King Russia is to combine rapid regional expansion with profitability, which relies on making sound data-driven business decisions. It needs data to provide its 200 area managers and 760 restaurant managers with all the facts, figures, and market trends they need to run successful restaurants. In the other direction, it also needs to receive quick feedback from them on new initiatives because Burger King’s business development strategy is based on ‘quick wins’ with measurable results rapidly digitized as a basis for planning next steps. However, Burger King Russia needed to transform and streamline its approach to data and reporting and saw business intelligence (BI) as the way ahead.

The Alliance for Journalists’ Freedom (AJF), a Sydney-based public not-for-profit company, was looking to expand its advocacy into the Asia–Pacific (APAC) region in mid-2020. The organization realized that it needed to fully understand the press freedom landscape in the APAC region. Existing data was presented in different ways and AJF identified a gap in the market for a visual overview of the data. The organization wanted to develop a project that provided a visual overview of the data in the region it was trying to better understand. AJF's advocacy focuses on building trust and relationships, and the organization wanted to develop a tool that emulates that. The purpose of AJF’s work in the region is to support others to act independently to protect their own press freedom and transparency. This has positive civic and possibly even economic implications for those countries.

Kasikornbank (KBank), one of Thailand's largest banks, was facing challenges in serving its customers with personalized and secure products while expanding its client base using the latest technological advancements. The bank's current systems relied heavily on resources to marry data from a host of applications, which could result in mismatches or add to security risks. With growing demand for contactless transactions and efficient resource allocation, the bank needed a solution that could meet these challenges. The bank also wanted to improve its understanding of its customers to grow its lending business and avoid inconsistencies.

The University of Bath recognized the importance of data visualization skills for their MSc in Business Analytics students. They wanted the students to gain practical experience in an industry-leading tool. The challenge was to provide the students with real-life data and a platform where they could apply their theoretical knowledge and develop their data visualization skills.

Al-Ikhsan Sports, the leading sports retailer in Malaysia, was in need of a robust business intelligence platform to aid in intelligent decision-making and support future growth. With a network of 135 stores across Malaysia and a burgeoning ecommerce platform, the company sought deeper insights into the performance of individual store locations and the best-selling products at each store.

Healthcare is a complex and disconnected environment where innovation and breakthroughs rely on navigating vast quantities of data from disparate stakeholders. IQVIA, a leading global provider of advanced analytics, technology solutions and clinical research services to the healthcare sector, specializes in meeting this challenge. In the UK, IQVIA works across eight key areas that include patient experience and outcome measures, costing, benchmarking, clinical coding and population health. It also runs one of the world’s largest life sciences laboratories supporting widescale clinical trials. Principal customers of IQVIA’s healthcare team are hospitals of the UK’s National Health Service (NHS). They use IQVIA’s insights to learn how to fund increasingly complex patient pathways and drugs, how to better manage resources and how to maximize the use of data to improve their services with a view to improving patient outcomes.

Grip, a London-based company, developed an AI-based event matchmaking platform to solve the problem of inefficient networking at events. The platform uses a self-learning matchmaking engine that uses natural language processing, advanced algorithms, and deep neural networks to learn about the professional goals and interests of visitors, exhibitors, and sponsors. To remain competitive, Grip needed to integrate with other systems such as event registration and CRMs like HubSpot, Microsoft Dynamics, and Salesforce. However, building these integrations was a time-consuming process that required the expertise of developers.

Ocean & Earth, an Australian surf accessory company, has grown organically over the last 40 years and now uses many channels to sell its wide product range to more than 15 countries. This generates a wealth of data, but the company could not display it in a clear and usable format. The company was struggling with data visualization and needed a solution that could help them make sense of their data and use it to drive strategic decisions.

The IT sector in India has thrived during the COVID-19 pandemic, with a surge in demand for data scientists. However, there is a shortage of students skilled in analytics. ICT Academy, created by the Government of India, aims to bridge the industry-academia skill gap and create a new generation of industry-ready talent. The academy partners with technology companies to train teachers and graduating students in new technologies. One of its key collaborations is with Qlik, which offers the Qlik Academic Program focusing on up-skilling educators and students in data analytics.

Borealis, a global chemical company, was struggling with the efficient management of its procurement process due to the vast amount of data originating from different sources. The company used standard tools for business analysis, but these could only produce static and pre-defined reports. With data volumes growing and new data sources constantly coming on stream, Borealis found it difficult to obtain actionable insights from its analysis. It needed a new analytical platform that would support informed decision-making across the global procurement organization.

Universal Business School Sydney (UBSS), one of Australia’s major independent higher education providers, faced two key challenges. Internally, it aimed to support students on their journey to a successful academic conclusion of their studies. Externally, it had to satisfy the high standards of compliance expected of the country’s registered higher education providers set by the Tertiary Education Quality and Standards Agency (TESQA). UBSS had to access multiple internal and external data sources to meet its mission of providing a richer and deeper understanding of the teaching and learning process, as well as enriching its students’ experience. The complexity involved six different academic management systems the organization uses while interacting in real-time with various departments for academic data, visa and immigration data, and international student intelligence.

The University Hospitals of Morecambe Bay NHS Foundation Trust (UHMBT) was facing the challenge of maintaining high-level patient service during the winter months when hospitals are typically overwhelmed by a patient surge. The operational staff were concerned about how they would cope with the rising demand for urgent care services. The challenge was to find effective and practical innovations to improve support for workers and overall patient care. The goal was to develop a solution that was business- and customer-led, tackled the big issues, and was focused on customer and business solutions.

The personal lines insurance industry is a highly competitive and price-sensitive marketplace. With more than two-thirds of UK insurance transacted online, the ability to compete on price comparison sites is key to success. As millions of quotes are generated each day, real-time analysis of vast volumes of data is fundamental for organizations targeting growth and needing insight into ‘live’ sales performance. Whether it’s pricing, a technical issue or variations in the market, alerts can prompt decisions that will avert substantial revenue losses. In this fast-moving industry, waiting 24 hours for access to data is not an option.

Riocard Mais, the biggest ticketing system in Brazil and Latin America, was facing challenges with the increasing volume and complexity of data due to the increased functionalities and technical requirements of their system. Each year, the system records two billion operations and 60 million financial transactions. The company needed a tool that could provide consistency in information and agility in accessing and analyzing data. Consultations had to be done on the mainframe, which generated conflicts between normal credit sales and business area reports. The IT department was limited to running in small time slots and a request would take on average 48 hours to fulfill.