IDC European Data Strategy Awards
IDC European Data Strategy
& Innovation Awards 2022
Organizations the world over are investing to implement "future of intelligence" strategies that increase their capacity to learn, at the same time as increasing their ability to synthesize the information they need in order to learn and increasing their ability to apply the resulting insights at scale.
IDC's European Data Strategy & Innovation Awards are focused on celebrating the European organizations that are blazing trails in this area and on improving awareness of "what works." The awards recognize excellence in European organizations' strategic consideration and management of data, and use of data, analytics, and AI to drive innovation, new products and services, and operational excellence.
The winner of these awards will be announced at IDC’s European Data and Intelligence Summit 2022. The closing date for nominations is March 25, 2022.View Event
Nominations in this category are specifically for enterprise initiatives and projects that leverage AI (based on machine learning or deep learning) techniques and technologies to deliver new products or services or radically transform a business process.Nominate a Project
To be nominated in this category, an enterprise must have used first-, second-, or third-party data to create new business insights that lead to exemplary material business impacts (for example, a significant change in business or customer focus, a new product or service opportunity, an operational efficiency improvement or risk reduction).Nominate a Project
To be nominated in this category, an enterprise must be able to demonstrate a significant advance in its ability to effectively and efficiently manage data at scale for business advantage. A nominated initiative might, for example, revolve around integrating data across a hybrid cloud environment, introducing a robust life-cycle management model across all core enterprise data, architecting an enterprise data platform that harmonizes approaches to data management across all major data types and use cases, etc.Nominate a Project
Each of the three category winners will receive:
A certificate of their achievement awarded during IDC's European Data & Intelligence Digital Summit 2022 before an audience of their peers
A digital badge for use on their business website and/or participants' personal online profiles
Coverage in a dedicated IDC case study report
Coverage in a press release and via IDC's social media channels detailing the outcome of the awards
Each shortlisted award entry will receive a digital badge for use on their business website and/or participants' personal online profiles and coverage in a press release and via IDC's social media channels detailing the outcome of the awards
Last Year’s Winners
Winner: Aksigorta A.Ş.
This major Turkish insurer used DataRobot's AI technology to revolutionize its price modeling. Aksigorta A.Ş. had been running an industry-standard pricing model and was finding it difficult to meaningfully differentiate or compete on price. It set about developing a new price model leveraging DataRobot's technology platform, as well as newly available government datasets. The group created a dual-speed pricing approach using both the industry-standard GLM models and the new AI model to serve new pricing recommendations to its underwriters. Since implementing the new model, Aksigorta A.Ş. has been able to more accurately and competitively price its premiums, leading to a 55% increase in the group's market share of the Turkish passenger car market, a 237% rise in the light commercial vehicle market, and an increase in the group's overall margin to 23% from 15%.
U.K.-based neobank and digital lender Zopa introduced Explainable AI and human-in-the-loop systems into its fraud detection systems with the help of AWS Clarify. Zopa uses advanced ML technology to flag potentially suspicious applications that are then passed on for human review. Zopa wanted to improve transparency within its models and make it easy for the fraud team to understand which aspects of an application had caused the application to be flagged for human review. Zopa introduced AWS Clarify to generate individual explanations each time its algorithm flagged an application. For regulated lenders like Zopa it's important to understand how each factor contributes to an ML model's decisions. Zopa was also able to enhance its models to enable it to reduce fraud loss within the company by more than half. Additionally, use of the ML interpretation improved investigation times for the financial crime team threefold.
HSBC wanted to reduce the time employees were spending on handling internal policy queries in the risk department. The company formed a team to deliver Operational Resilience and Risk Application (ORRA) — a chatbot designed to handle a range of policy queries. Using Google Cloud's DialogFlow technology, HSBC was able to build ORRA to help employees to find information and respond to queries far faster than they were able to previously. ORRA has also increased transparency throughout the organization regarding the type of policy queries that need answering and therefore where the opportunities are to improve the policies themselves.
The U.K. National Health Service Business Service Authority (NHSBSA) was able to automate and improve handling of calls to its call centers using Amazon Connect, Alexa, and Lex. The introduction of the virtual agent to handle Overseas Healthcare Service & EHIC queries reduced call volumes to human agents by 40%. The project enabled savings of $650,000, but it also crucially freed up resources that could then be redeployed to support pandemic-related phone inquires via the NHS 111 helpline.
Winner: Wrightington, Wigan and Leigh Teaching Hospitals NHS Foundation Trust
Like every other part of the U.K.'s National Health Service and health services the world over, Wrightington, Wigan and Leigh Teaching Hospitals NHS Foundation Trust (WWL) had colossal challenges to overcome to deal with the demands of the COVID-19 pandemic.
Building on top of its existing data and analytics investments, based on Qlik technology, WWL added the ability for clinicians to "writeback" operational observations (around things like mortuary and ward capacities, positive COVID tests from staff, and so on). Capturing up-to-date data made it easier for WWL to plan major operational changes, such as partitioning facilities to keep positive and negative patients separated. WWL's data scientists built predictive models based on this data that were integrated back into Qlik, enabling the organization to effectively predict demand. Subsequently, WWL has gone on to share its experiences as well as its models with other healthcare organizations.
WWL is rightly proud that throughout the pandemic its Accident & Emergency service delivery performance has been the third highest in the northwest of England, despite being a small trust. It also used data to enable patients to be transferred safely to help with the prevention of cross-infection.
Runner-up: Lloyd's of London
Lloyd's of London, the world's leading insurance market, has a 300-year history. For most of that time, it has focused on manually created written reports by experts providing insights on the market, rarely containing detailed market data or performance benchmarks. There was a huge opportunity for Lloyd's to transform the breadth and level of insight provided across the huge variety of insurance products and geographies it now serves by creating digital insight products.
Working with Qlik, a small core team at Lloyd's created a digital Insights Hub, offering a wide range of market stakeholders personalized, detailed, and transactional analytics for the first time — based on a new data management and visualization platform. This enables consistent and clear views of the whole market, or specific performance benchmarks down to a specific product in an individual territory. Data is also provided via APIs so market participants can download their own data from the market and conduct their own value-added analyses.
In its first 18 months, the Hub has been adopted by 70 different companies, generated a 400% return on original investment, and is estimated to have saved over 100,000 hours of staff time — as well as leading to glowing reviews from insurers and brokers alike.
Castor, a global provider of clinical trial platform technology aimed at medical researchers, has made the platform available free of charge for more than 250 COVID-19 studies in 40 countries worldwide. This enables researchers to better understand the COVID-19 virus and optimize valuable hospital resources to ultimately understand patient requirements and provide critical care to improve COVID-19 patient outcomes.
Castor worked with Alteryx and a Dutch specialist Alteryx partner, The Information Lab, to speed the processing, integration, and analysis of clinical data from multiple sources. It automated the data analytic processes involved in accessing, validating, and transforming vast amounts of clinical data from traditional and decentralized trials in real time — and as a result, researchers are now able to get real-time access to the data-driven insights needed to quickly respond to COVID-19.
Molslinjen, a Danish ferry operator with more than 7,500 annual departures, needed to improve the accuracy of its passenger and vehicle demand forecasts; these, traditionally, were manually created from historical statistics and experience. If the company could predict demand more accurately, it could utilize its capacity much more effectively.
Working with Copenhagen-based AI and analytics specialist Halfspace, Molslinjen transformed its forecasting process — shifting from manual estimation to using a fully automated, AI-based forecast engine. This engine blends historical demand patterns, up-to-date online and offline reservation data, and real-time data about checkins and surrounding traffic conditions to provide forecasts.
The results are clear: the new forecasts are more accurate than the old (70% of the time). As a result, Molslinjen has seen a 14% uplift in highly profitable business customer usage; over 4,500 additional tickets sold annually; as well as lower fuel consumption from its ferries, driving lower carbon emissions.
French power utility provider ENGIE serves a diverse range of customers across almost 70 countries: from cities to retail customers to large companies and beyond. As a champion of renewable energy, it is on a journey to decentralization by enabling customers to generate electricity through their own assets (like solar panels and windfarms). As a result, it found that its existing data and IT investments relating to planning were no longer fit for purpose.
Working with AWS, Engie has transformed its data management capability — creating a Common Data Hub to align its customers and business units around the same solution, and help ENGIE's business units easily ingest, store, share, and consume datasets through a unified platform and highly secured environment.
To facilitate smooth and easy adoption of the Common Data Hub all around the world, ENGIE provided acceleration templates and documentation to help its business unit administrators see the value of the data they collect and access the data in the distributed data lake. The Common Data Hub forms the backbone of ENGIE's data-driven strategy by enabling data collaboration between information technology and business users, accelerating increased data literacy at every level of ENGIE and helping to optimize internal processes or create new data-driven services.
Commerzbank, a leading international bank with branches and offices in almost 40 countries that transacts approximately 30% of Germany's foreign trade, had a complex challenge to solve. Following a change in German regulation, a bank client is now able to request a cancellation of transactions undertaken on their behalf in the past 13 months — this changed from a cancellation period of just 14 days. The bank was processing these requests manually, which was very time consuming and created real risks of error.
Working with Cloudera, Commerzbank created an automated, real-time, and error-free search engine for historical financial transactions that reduced the time taken to process and complete such requests from 48 hours to a matter of seconds. The acceleration of the search is saving costs and is creating a significantly enhanced, faster customer experience. Looking to the future, the bank is planning to make this process even more seamless for customers by putting the search function — and their data — in their own hands.
Runner-up: United Group
United Group, the leading multiplay telecoms and media provider in southeast Europe, provides customers with a full range of telecommunications services. The company's acquisition strategy has fueled growth and the company has doubled in size in recent years; also, given that its existing analytics platform was declared end-of-life by the vendor, United Group needed to think again.
It wanted to build a new analytics platform that could scale in line with the company's growth, as well as powering new products and services. It worked with Poslovna Inteligencija, a specialist analytics services provider, and Vertica.
As well as delivering customer, operational, financial, and service-quality analytics for delivery via Tableau, United Group has used its new platform to power an innovative new Video Dynamic Advertising platform, which provides dynamic addressable TV advertising over its streaming platform. Vertica analyzes clickstream data, as well as electronic program guide usage data, device data, and customer attributes, to profile customers and provide near-real-time decisions on filling upcoming advertising blocks. United Group has also used Vertica to power a 360-degree customer view within its SAP implementation for customer service.
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