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 to learn and increasing their ability to apply the resulting insights at scale.
IDC's European Data Strategy and 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.
These awards were presented on June 8, 2020. Congratulations to all the winners and runners-up, and thanks to all who entered. You can find details of all the category winners and runners-up below or listen to the awards ceremony here.
Innovation with AI
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.
Winner: NatWest Markets
NatWest Markets is using innovative AI technology to put in place a communications intelligence platform to help it radically transform its operations. As with many other banks, NatWest Markets has relied on email as a way to communicate and coordinate work through its operations; it found that roughly 70% of the daily work for operations staff was outside core IT systems, with 40% of time taken communicating in Outlook alone and a further 30% manipulating data. Working with specialist vendor Re:infer, NatWest Markets ingested over 12 months of emails from the Operations Function — containing well over a 15 million emails — and applied unsupervised deep learning to identify the patterns of semantics, entities, and sentiment from this email base. Working with subject matter experts from NatWest Markets, the team has been able to get to key insights in just eight hours of work — and clearly identified bottlenecks, inefficiencies, risk events, complaints, and exceptions — as well as new revenue opportunities. The company has now identified significant change opportunities and plans to expand its work this year.
By unlocking the power of data and artificial intelligence, Philips, a leading health technology company, wants to deliver effective yet cost-efficient solutions that support people throughout the continuum of care, from healthy living and prevention, through diagnosis, treatment, and home care. The power of artificial intelligence and machine learning expands to internal initiatives as well.
Philips collaborated with specialist vendor Antuit.ai to apply AI and ML proprietary techniques to drive demand forecasting accuracy for the benefit of customers and consumers, as well as Philips. In the initial phase, the focus was on a number of accounts in North America covering the Personal Health product portfolio where the team was able to improve forecast accuracy by more than 20%, enabling better fill rates and fewer stockouts. This resulted in turn in improved service levels for its customers. Based on its success, a full-scale global deployment is in progress.
Runner-Up: London AI Centre
The London Medical Imaging & Artificial Intelligence Centre for Value Based Healthcare is a consortium of three world-class universities, four high-performing research hospitals, major industry partners, and a large number of small to midsize enterprises that seeks to drive AI enablement of the NHS, use data to transform public health, and provide better care for patients in London and southern England. Bringing together technology, data-driven strategies, and AI, this collaborative effort also aims to reduce wasted healthcare effort and deliver significant financial savings.
Led by King's College London and based at St Thomas' Hospital, the consortium has built a state-of-the-art AI platform using networking, storage, and compute technology from vendors including NetApp and NVIDIA — enabling data collection and processing to be carried out quickly and efficiently without jeopardizing governance or compliance obligations. The new platform means the London AI Centre can process more data and train more models in less time, helping healthcare data scientists reach informed conclusions that can improve care and save lives.
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).
Winner: Lufthansa CityLine
In 2018, increasing capacity constraints in the aviation ecosystem, like airport infrastructure or air traffic control, led to problems with operational performance at Lufthansa CityLine. This resulted in insufficient punctuality, with a negative impact on customer experience. Instead of hiring process consultants to examine the issue, CityLine started the PROMOTE (PROcess Mining for OperaTional Excellence) program based on the process mining technology from Celonis — an analytical solution for discovering, monitoring, and improving real, data-based processes by extracting event logs readily available from the organization's existing IT systems.
On its process mining journey, Lufthansa CityLine has applied the practice to multiple interconnected operations processes. Starting with Technical Fleet Management, Lufthansa CityLine was able to reduce delays in maintenance work by 15%; in Ground Operations, the airline has analyzed and optimized a complex web of activities managed by multiple service providers to increase flight punctuality by 300,000 minutes.
Runner-Up: Philips Healthcare
Medical imaging systems such as MRI and CT scanners must provide optimal clinical performance and predictable cost of ownership. Healthcare costs are exploding worldwide, and unplanned downtime of medical imaging systems can have significant impact on health service providers. In response Philips Healthcare has developed maintenance services for hospitals based on remote monitoring and proactive maintenance. Rather than waiting for a medical device to fail and dispatch a field-service engineer to fix it, Philips devices are connected to a remote monitoring infrastructure that uses Big Data to detect and predict issues before they occur or have impact on the clinical workflow.
Philips has tens of thousands of connected medical devices around the world that include mission-critical MRI machines and CT scanners. Every imaging system contains many sensors and generates daily large volumes of data: a single MRI system can generate millions of log events each day and hundreds of thousands of data points from its sensors. Philips realized the potential of this data for predicting medical device technical issues and built a Big Data analytics solution by combining its own HealthSuite Digital Platform with the Vertica analytics platform.
Runner-Up: Nationwide Building Society
Like many organizations, Supplier Management at Nationwide Building Society (NBS) has been wrestling with how best to streamline processes, minimize manual processing, and optimize supplier spend. Using data and analytics technology from Qlik, and working in close collaboration, Nationwide's Supplier Management and Data Visualisation teams have used analytics to support continual improvement and transformation of the organization's procurement activities, increased data literacy, and driven adoption of self-service BI and insight tools.
As the engagement progressed, a team of two BI Team members within Nationwide built and deployed a suite of seven analytics solutions for its Supplier Management business, working in a highly collaborative, iterative, and agile fashion, focusing on value-based outcomes. The initiative led to significant cost benefits as well as making it easier to manage supplier risk, pay smaller suppliers more quickly, and build relationships between procurement, finance, and audit teams.
Data Management Excellence
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.
Winner: Dentsu Aegis Network
Dentsu Aegis Network, a leading global marketing service group, has grown over many years through dozens of acquisitions — and as a result it struggled with high cost and complexity in its application and system estate. In an effort to standardize these systems and bring an element of uniformity across its different brands, the company initiated a digital transformation project deploying core strategic SaaS platforms such as Workday, Salesforce, and Workfront. To ensure these new applications worked seamlessly together, the company needed an accessible integration solution that could be rolled out companywide quickly.
Dentsu Aegis Network worked with integration platform vendor SnapLogic to initiate and complete a large number of integration projects quickly — bringing together the multitude of SaaS applications the company is using today and will add in the future, streamlining business processes, and giving the IT team a single and holistic view of their data landscape.
Runner-Up: ICON Clinical Research
ICON is a contract research organization serving pharmaceutical companies, with its business relying on it being able to work effectively and efficiently with regulatory documentation. Regulatory documents are critical in determining the efficacy and safety of new drugs under consideration for regulatory approval and release, and timeliness and accuracy are of the essence — but historically the submission of documents to authorities has been a manual process.
ICON turned to robotic process automation (RPA) specialist UiPath and consultancy EY to help it automate the ingestion and quality control of the documents to its system for regulatory submission and ultimately critical drug approval, and set up an automation center of excellence. Regulatory documents are now submitted automatically, leading to a 75% reduction in backlogs and equivalent reductions in submission timelines. Reducing the submission timelines is especially critical for the therapies and vaccines being developed to treat COVID-19.
SailGP is an annual, global sail racing championship set in some of the world's most iconic harbors. SailGP uses the Oracle Cloud–based platform to deliver real-time data and analytics for multiple applications that empower fans and teams while advancing the sport of sailing.
During each SailGP race, hundreds of sensors on the fleet of F50s collect and stream tens of thousands of data points to an onshore Oracle data storage center. From there, the data is uploaded and stored to the nearest geographical Oracle datacenter for analysis and distribution around the world — all of which happens and is consumable for end users within 150 milliseconds.
The data derived from the sensors — plus the sharing of live video and audio from onboard cameras and microphones — brings viewers closer to the action, helps teams analyze their performance, and gives officials the details they need to make calls with confidence. All data collected during races is shared with each of the teams for analysis so that collectively they can advance sailing and the series performance.
Please contact Neil Ward-Dutton, VP, AI and Intelligent Process Automation, on firstname.lastname@example.org for more information.
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