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• innovatorProfile
  • InnovatorProfile
    • id51
    • linkedin_urlhttps://www.linkedin.com/in/nancyselph/
    • summary_bio<p>Nancy Selph is the COO for Innovation and Data Governance at Deutsche Bank in New York. She manages the central team that supports the innovation function globally through labs in locations around the world. The labs collaborate with a global focus and share three principal goals: to help the bank evaluate and adopt emerging technologies, to develop a culture of innovation, and to contribute to the bank's digital strategy.</p> <p>The launch of the Deutsche Bank Innovation Lab New York in March marked the fourth lab in the iconic bank’s global initiative to create an ecosystem for Fintech innovation. Representing an integral component of the Frankfurt-based bank’s broader, growth-oriented digital strategy of enhancing products and service to clients, the labs explore and evaluate scores of start-ups and emerging technologies to unlock business benefits such as better risk management, tighter controls and enhanced client experience.</p> <p>The innovation labs were the brainchild of Kim Hammonds, Member of the Management Board and Group Chief Operating Officer, three years ago after she joined Deutsche Bank from Boeing. The labs are located near Deutsche Bank’s business and technology centers and embedded within top innovation ecosystems. The core function of labs teams are as innovation specialists representing the bank’s interests. They seek to understand the demand challenges of internal partners within the bank and then look to globally vet new and emerging technologies. They then explore if there is a match and conduct experimentation to see if the solution can work inside the bank.</p> <p>Among the technologies Deutsche Bank has adopted via the labs is a web-based financial risk analysis tool. The new service alerts credit risk officers so they can actively manage client ratings, thereby supporting better business decisions and liquidity for clients. Another tool helps analyze surveillance data harvested from multiple sources bank-wide.</p> <p>The labs help transform the bank through adopting emerging technologies and by working on the more complex process and technology themes the bank faces. Digital retail banking, Distributed Ledger and the future of international payments are some of the larger challenges they are exploring.</p> <p>“Some people believe innovation has to be instant and revolutionary. But all eureka moments come from years of hard work and evolutionary change. Global banks will evolve to where we want to be in this same way. We will utilize new technologies to solve challenges that will be rolled out incrementally across the bank.”</p> <p>Having worked for a Fintech pioneer in the early 1990s, Selph has the benefit of having both witnessed the impacts of several game-changing innovation generations in the finance sector, and of understanding changing expectations in an age of digitally empowered customers. In her career, she has held key operations and executive roles with five investment banks.</p> <p>“I joined a small company called Teknekron Software Systems in 1990, which revolutionized the way trading floors operated,” she recalls. “Teknekron developed the middleware which distributed digitized stock market data to trading floors. The company became TIBCO in 1994. That technology in the early ‘90s was game-changing. We knew more about technology than the people using the systems, which is typically not the case today. This is because most people working at Deutsche Bank, or any other enterprise, tend to have access to faster and cheaper consumer products than we can provide inside of the bank. Banks have merged and they have been acquired, and they have different systems for varied purposes. It is very challenging to fully integrate those systems. That is one of the challenges the bank has when adopting new technologies.”</p>
    • answer_1<p>The idea of the lab presence itself is about giving people a space to come and think differently and engage with us. We run demand sessions with our business teams to get to the root cause of their challenges and then find solutions to meet those needs. It is the applied adoption of new technologies with a return on investment by decreasing risk, simplifying the environment or increasing revenue. By the time we have introduced the technology into the bank, we are confident it will make a difference.</p>
    • answer_2<p>All large banks have challenges. The size, credentials and history of the bank reflects the complexity of the underlying systems and processes that need to be transformed. The labs have been created specifically to tackle these challenges on all fronts. Some are easier than others to solve, but the needs of our business and technology partners within the bank are always our focus. Something that helps overcome impediments is how well the labs have been embraced by the bank. There is huge support and engagement at the executive level to make Deutsche Bank great from a technology perspective. </p>
    • answer_3Innovation is one of the pillars of Deutsche Bank and at the cornerstone of everything the bank is doing. Our CEO, John Cryan, talks about the innovation labs often in his public speeches as a means to enable us to service our clients in a better fashion. It is a top-down imperative with a bottom-up implementation, making the lab accessible to everybody. The labs are for all Deutsche Bank employees. People come in and see the bank has invested in working differently. Everybody who has walked through our doors or spoken to one of us feels the excitement and takes it back to their desks.    
    • answer_4<p>Over the next few years, technologies such as artificial intelligence, robotics, machine learning, and analytics will transform the banking industry. What these new technologies can do with analyzing and transforming vast amount of data is amazing.</p>
    • answer_5<p>I love how Panera Bread leveraged technology to change the ordering experience. The wait was long and the orders were not always right. They transformed their ordering process through in-store kiosks and a mobile app, so now it takes a minute instead of eight to order your food there. I’m always looking for ways to save time in my life, so this resonates with me.</p>
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  • Leader
    • id220
    • nameNancy Selph
    • job_titleCOO of Innovation & Data Governance
    • companyDeutsche Bank
    • headshotnancy headshot(140x140).png
    • company_logoDB Logo (140x60).png
    • bio_full<p>Nancy Selph is the COO for Innovation and Data Governance at Deutsche Bank in New York. She manages the central team that supports the innovation function globally through labs in locations around the world. The labs collaborate with a global focus and share three principal goals: to help the bank evaluate and adopt emerging technologies, to develop a culture of innovation, and to contribute to the bank's digital strategy.</p> <p>The launch of the Deutsche Bank Innovation Lab New York in March marked the fourth lab in the iconic bank’s global initiative to create an ecosystem for Fintech innovation. Representing an integral component of the Frankfurt-based bank’s broader, growth-oriented digital strategy of enhancing products and service to clients, the labs explore and evaluate scores of start-ups and emerging technologies to unlock business benefits such as better risk management, tighter controls and enhanced client experience.</p> <p>The innovation labs were the brainchild of Kim Hammonds, Member of the Management Board and Group Chief Operating Officer, three years ago after she joined Deutsche Bank from Boeing. The labs are located near Deutsche Bank’s business and technology centers and embedded within top innovation ecosystems. The core function of labs teams are as innovation specialists representing the bank’s interests. They seek to understand the demand challenges of internal partners within the bank and then look to globally vet new and emerging technologies. They then explore if there is a match and conduct experimentation to see if the solution can work inside the bank.</p> <p>Among the technologies Deutsche Bank has adopted via the labs is a web-based financial risk analysis tool. The new service alerts credit risk officers so they can actively manage client ratings, thereby supporting better business decisions and liquidity for clients. Another tool helps analyze surveillance data harvested from multiple sources bank-wide.</p> <p>The labs help transform the bank through adopting emerging technologies and by working on the more complex process and technology themes the bank faces. Digital retail banking, Distributed Ledger and the future of international payments are some of the larger challenges they are exploring.</p> <p>“Some people believe innovation has to be instant and revolutionary. But all eureka moments come from years of hard work and evolutionary change. Global banks will evolve to where we want to be in this same way. We will utilize new technologies to solve challenges that will be rolled out incrementally across the bank.”</p> <p>Having worked for a Fintech pioneer in the early 1990s, Selph has the benefit of having both witnessed the impacts of several game-changing innovation generations in the finance sector, and of understanding changing expectations in an age of digitally empowered customers. In her career, she has held key operations and executive roles with five investment banks.</p> <p>“I joined a small company called Teknekron Software Systems in 1990, which revolutionized the way trading floors operated,” she recalls. “Teknekron developed the middleware which distributed digitized stock market data to trading floors. The company became TIBCO in 1994. That technology in the early ‘90s was game-changing. We knew more about technology than the people using the systems, which is typically not the case today. This is because most people working at Deutsche Bank, or any other enterprise, tend to have access to faster and cheaper consumer products than we can provide inside of the bank. Banks have merged and they have been acquired, and they have different systems for varied purposes. It is very challenging to fully integrate those systems. That is one of the challenges the bank has when adopting new technologies.”</p>
    • summary<p>Nancy Selph is the COO for Innovation and Data Governance at Deutsche Bank in New York. She manages the central team that supports the innovation function globally through labs in locations around the world. The labs collaborate with a global focus and share three principal goals: to help the bank evaluate and adopt emerging technologies, to develop a culture of innovation, and to contribute to the bank's digital strategy. </p>
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    • Article
      • id1365
      • date2023-01-04
      • titleIs Your Company Mistaking Technology For Digital Transformation?
      • author(null)
      • publisherForbes
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      • urlhttps://www.forbes.com/sites/sap/2023/01/24/is-your-company-mistaking-technology-for-digital-transformation/?sh=4eb4bfa771e9
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      • id1361
      • date2020-08-10
      • titleA Cornucopia Of Cloud Storage Solutions
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      • publisherForbes
      • description
      • urlhttps://www.forbes.com/sites/tomcoughlin/2020/08/10/a-cornucopia-of-cloud-storage-solutions/#66c77bb76938
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      • created2020-08-12 17:48:21
      • modified2020-08-12 17:48:21
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    • Program
      • 0
        • id31
        • titleBringing Simplicity To Multi-Cloud Complexity
        • subtitleAdvancing Data Connectivity, Logistics and Value
        • summaryThis initiative aims to explore the forces, factors, challenges and requirements driving the need for improved data logistics in today’s multi-cloud world.
        • description<p><strong>Overview</strong></p> <p>The Business Performance Innovation (BPI) Network, in partnership with DBM Cloud Systems and the CMO Council, is undertaking research into the forces, factors, challenges and requirements driving the need for improved data logistics in today’s multi-cloud world. Global enterprises are seeking to integrate vast repositories of data across multiple public and private clouds and on-premise systems to extract more value, use and return on these assets. In particular, this relates to decision-support analytics, product and service delivery, customer intelligence and personalized engagement, operational improvement, business compliance, and continuity.</p> <p>While multi-cloud and hybrid cloud environments provide major advantages, they also increase the complexity of managing, translating, processing and moving data. Chief Data Officers, infrastructure IT executives and others in the enterprise are now seeking new and innovative ways to gain greater control, visibility, performance and efficiency in the way they manage data to optimize its value.</p> <p>The program will engage data and IT executives from major companies, as well as leading system integrators, consulting firms and solution providers to understand needs, requirements and best practices in optimizing data economics, protection and logistics in today’s multi-cloud, mega-data world.</p> <p><strong> </strong></p> <p><strong>Background</strong></p> <p>The growing importance of the Chief Data Officer underscores widespread recognition of the essential role and value of data and analytics in the modern, agile customer-centric enterprise. This is further compounded by the significant cost, challenge and complexity of unifying, migrating, replicating, protecting, storing and governing data “ponds, lakes and dams” in today’s multi-cloud and hybrid cloud computing environments.</p> <p>Data has become one of the chief engines of value creation. Its role in improving analytical decision making, enhancing our ability to understand, reach and engage customers, and increasing the value of both existing and new products and services has made data a highly valued currency and asset base for enterprises operating digitally across data borders, ramparts and fences.</p> <p>Fueled by an explosive proliferation of new data sources—from mobile computing, social media and rich media applications and services, to the advent of the Internet of Things, which will generate some 50 million connected sensors by the end of 2020—the amount and variety of data being stored is growing exponentially.  According Seagate Technology, the amount of data generated worldwide will increase to 163 zettabytes by 2025 from 12 zettabytes in 2015.</p> <p>In today’s multi-cloud, mega-data world, better Data Logistics and Performance Management (DLPM) has become essential to competing in the Data Economy. According to 451 Research, some 80 percent of companies are now utilizing two or more clouds. Three-quarters of companies say they are pursuing a hybrid/multi-cloud strategy.</p> <p>In this highly distributed compute environment, the requirements to understand where data resides across multiple public clouds and on-premise systems and cost-effectively store, protect and move data to its optimal location becomes critical. With the coming rise of edge computing and micro-data centers designed to bring data and applications closer to users to reduce latency and thereby improve application and workload performance, data management and logistics become even more complex. The edge is creating even more data, with increased data volumes having to be transmitted across networks and between clouds.</p> <p>Object-based data storage is now the dominant storage architecture globally, particularly in the cloud, and will be used to store 85 percent of the world’s data by 2025. Developed initially to handle the explosive growth of unstructured data, such as video, images, web pages, log files and IoT data, object storage saves data along with associated metadata in blocks as objects that can contain multiple information formats.</p> <p>It has a variety of advantages over file and block storage, including massive scalability, greater flexibility via metadata for analytics, better governance, faster retrieval, and improved cost efficiencies. In addition, continued technical advances are improving both the performance and the applicability of object storage for new use cases. A major challenge, however, is that the object-based storage systems used my various cloud providers are all different, making data synchronization and translation a challenge.</p> <p> </p> <p><strong>The Data Logistics Mandate</strong></p> <p>In this new world, Chief Data Officers and CIOs must optimize how they manage vast volumes of data across multiple clouds and data environments through better data logistics. There are more data silos, greater distribution of data, vast increases in volume, and a growing demand to understand, protect and exploit data for business growth and optimization while holding down costs.</p> <p>Among those logistical challenges are the need to keep track of where data resides, and cost-effectively synchronize, replicate and move data to optimize value, efficiency, security and governance based on cost differences, processing and analytics capabilities, performance advantages, and regulatory requirements.</p> <p>Organizations need to be able to be able to identify what data needs to be replicated and effectively transmitted and synchronized across different clouds and on-premise locations to improve the availability, security and value of data.</p> <p>For example, organizations increasingly need to move data to specific service providers to conduct analytics or take advantage of specific vendor technologies, lower processing and storage costs, or meet geographic requirements. Particularly when data replication and synchronization is a continuous activity, organizations need to automate this process based on established rules and policies to improve cost efficiency, eliminate errors and reduce management complexity.</p> <p>For object storage data, the capacity to fully utilize metadata to identify location, type and value is now a critical aspect of data logistics, as is the ability to transfer data with a minimum amount of performance degradation and data corruption. New solutions that can handle replication outside of the data path are delivering improved visibility, performance and data quality.</p> <p>Advancing data logistics is a major imperative for today’s data-driven organizations and their chief data officers. The mandate to improve data availability, performance, value and cost-efficiency will be a critical competitive differentiator in a multi-cloud, mega-data world.<br /><br /><strong>To get involved in this initiative, please reach out to <a href="mailto:dmurray@bpinetwork.org">Dave Murray</a>. </strong></p>
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    • Article
      • id1359
      • date2020-07-22
      • titleHybrid Cloud Security: Benefits and Challenges
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      • publisherBusiness2Community
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      • urlhttps://www.business2community.com/cloud-computing/hybrid-cloud-security-benefits-and-challenges-02329045
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      • created2020-08-12 17:47:17
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        • id31
        • titleBringing Simplicity To Multi-Cloud Complexity
        • subtitleAdvancing Data Connectivity, Logistics and Value
        • summaryThis initiative aims to explore the forces, factors, challenges and requirements driving the need for improved data logistics in today’s multi-cloud world.
        • description<p><strong>Overview</strong></p> <p>The Business Performance Innovation (BPI) Network, in partnership with DBM Cloud Systems and the CMO Council, is undertaking research into the forces, factors, challenges and requirements driving the need for improved data logistics in today’s multi-cloud world. Global enterprises are seeking to integrate vast repositories of data across multiple public and private clouds and on-premise systems to extract more value, use and return on these assets. In particular, this relates to decision-support analytics, product and service delivery, customer intelligence and personalized engagement, operational improvement, business compliance, and continuity.</p> <p>While multi-cloud and hybrid cloud environments provide major advantages, they also increase the complexity of managing, translating, processing and moving data. Chief Data Officers, infrastructure IT executives and others in the enterprise are now seeking new and innovative ways to gain greater control, visibility, performance and efficiency in the way they manage data to optimize its value.</p> <p>The program will engage data and IT executives from major companies, as well as leading system integrators, consulting firms and solution providers to understand needs, requirements and best practices in optimizing data economics, protection and logistics in today’s multi-cloud, mega-data world.</p> <p><strong> </strong></p> <p><strong>Background</strong></p> <p>The growing importance of the Chief Data Officer underscores widespread recognition of the essential role and value of data and analytics in the modern, agile customer-centric enterprise. This is further compounded by the significant cost, challenge and complexity of unifying, migrating, replicating, protecting, storing and governing data “ponds, lakes and dams” in today’s multi-cloud and hybrid cloud computing environments.</p> <p>Data has become one of the chief engines of value creation. Its role in improving analytical decision making, enhancing our ability to understand, reach and engage customers, and increasing the value of both existing and new products and services has made data a highly valued currency and asset base for enterprises operating digitally across data borders, ramparts and fences.</p> <p>Fueled by an explosive proliferation of new data sources—from mobile computing, social media and rich media applications and services, to the advent of the Internet of Things, which will generate some 50 million connected sensors by the end of 2020—the amount and variety of data being stored is growing exponentially.  According Seagate Technology, the amount of data generated worldwide will increase to 163 zettabytes by 2025 from 12 zettabytes in 2015.</p> <p>In today’s multi-cloud, mega-data world, better Data Logistics and Performance Management (DLPM) has become essential to competing in the Data Economy. According to 451 Research, some 80 percent of companies are now utilizing two or more clouds. Three-quarters of companies say they are pursuing a hybrid/multi-cloud strategy.</p> <p>In this highly distributed compute environment, the requirements to understand where data resides across multiple public clouds and on-premise systems and cost-effectively store, protect and move data to its optimal location becomes critical. With the coming rise of edge computing and micro-data centers designed to bring data and applications closer to users to reduce latency and thereby improve application and workload performance, data management and logistics become even more complex. The edge is creating even more data, with increased data volumes having to be transmitted across networks and between clouds.</p> <p>Object-based data storage is now the dominant storage architecture globally, particularly in the cloud, and will be used to store 85 percent of the world’s data by 2025. Developed initially to handle the explosive growth of unstructured data, such as video, images, web pages, log files and IoT data, object storage saves data along with associated metadata in blocks as objects that can contain multiple information formats.</p> <p>It has a variety of advantages over file and block storage, including massive scalability, greater flexibility via metadata for analytics, better governance, faster retrieval, and improved cost efficiencies. In addition, continued technical advances are improving both the performance and the applicability of object storage for new use cases. A major challenge, however, is that the object-based storage systems used my various cloud providers are all different, making data synchronization and translation a challenge.</p> <p> </p> <p><strong>The Data Logistics Mandate</strong></p> <p>In this new world, Chief Data Officers and CIOs must optimize how they manage vast volumes of data across multiple clouds and data environments through better data logistics. There are more data silos, greater distribution of data, vast increases in volume, and a growing demand to understand, protect and exploit data for business growth and optimization while holding down costs.</p> <p>Among those logistical challenges are the need to keep track of where data resides, and cost-effectively synchronize, replicate and move data to optimize value, efficiency, security and governance based on cost differences, processing and analytics capabilities, performance advantages, and regulatory requirements.</p> <p>Organizations need to be able to be able to identify what data needs to be replicated and effectively transmitted and synchronized across different clouds and on-premise locations to improve the availability, security and value of data.</p> <p>For example, organizations increasingly need to move data to specific service providers to conduct analytics or take advantage of specific vendor technologies, lower processing and storage costs, or meet geographic requirements. Particularly when data replication and synchronization is a continuous activity, organizations need to automate this process based on established rules and policies to improve cost efficiency, eliminate errors and reduce management complexity.</p> <p>For object storage data, the capacity to fully utilize metadata to identify location, type and value is now a critical aspect of data logistics, as is the ability to transfer data with a minimum amount of performance degradation and data corruption. New solutions that can handle replication outside of the data path are delivering improved visibility, performance and data quality.</p> <p>Advancing data logistics is a major imperative for today’s data-driven organizations and their chief data officers. The mandate to improve data availability, performance, value and cost-efficiency will be a critical competitive differentiator in a multi-cloud, mega-data world.<br /><br /><strong>To get involved in this initiative, please reach out to <a href="mailto:dmurray@bpinetwork.org">Dave Murray</a>. </strong></p>
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      • date2020-07-22
      • titleIt’s Time To Rethink How To Get More From Your Data
      • author
      • publisherForbes
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      • urlhttps://www.forbes.com/sites/forbestechcouncil/2020/07/22/its-time-to-rethink-how-to-get-more-from-your-data/#3117717c6762
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        • id31
        • titleBringing Simplicity To Multi-Cloud Complexity
        • subtitleAdvancing Data Connectivity, Logistics and Value
        • summaryThis initiative aims to explore the forces, factors, challenges and requirements driving the need for improved data logistics in today’s multi-cloud world.
        • description<p><strong>Overview</strong></p> <p>The Business Performance Innovation (BPI) Network, in partnership with DBM Cloud Systems and the CMO Council, is undertaking research into the forces, factors, challenges and requirements driving the need for improved data logistics in today’s multi-cloud world. Global enterprises are seeking to integrate vast repositories of data across multiple public and private clouds and on-premise systems to extract more value, use and return on these assets. In particular, this relates to decision-support analytics, product and service delivery, customer intelligence and personalized engagement, operational improvement, business compliance, and continuity.</p> <p>While multi-cloud and hybrid cloud environments provide major advantages, they also increase the complexity of managing, translating, processing and moving data. Chief Data Officers, infrastructure IT executives and others in the enterprise are now seeking new and innovative ways to gain greater control, visibility, performance and efficiency in the way they manage data to optimize its value.</p> <p>The program will engage data and IT executives from major companies, as well as leading system integrators, consulting firms and solution providers to understand needs, requirements and best practices in optimizing data economics, protection and logistics in today’s multi-cloud, mega-data world.</p> <p><strong> </strong></p> <p><strong>Background</strong></p> <p>The growing importance of the Chief Data Officer underscores widespread recognition of the essential role and value of data and analytics in the modern, agile customer-centric enterprise. This is further compounded by the significant cost, challenge and complexity of unifying, migrating, replicating, protecting, storing and governing data “ponds, lakes and dams” in today’s multi-cloud and hybrid cloud computing environments.</p> <p>Data has become one of the chief engines of value creation. Its role in improving analytical decision making, enhancing our ability to understand, reach and engage customers, and increasing the value of both existing and new products and services has made data a highly valued currency and asset base for enterprises operating digitally across data borders, ramparts and fences.</p> <p>Fueled by an explosive proliferation of new data sources—from mobile computing, social media and rich media applications and services, to the advent of the Internet of Things, which will generate some 50 million connected sensors by the end of 2020—the amount and variety of data being stored is growing exponentially.  According Seagate Technology, the amount of data generated worldwide will increase to 163 zettabytes by 2025 from 12 zettabytes in 2015.</p> <p>In today’s multi-cloud, mega-data world, better Data Logistics and Performance Management (DLPM) has become essential to competing in the Data Economy. According to 451 Research, some 80 percent of companies are now utilizing two or more clouds. Three-quarters of companies say they are pursuing a hybrid/multi-cloud strategy.</p> <p>In this highly distributed compute environment, the requirements to understand where data resides across multiple public clouds and on-premise systems and cost-effectively store, protect and move data to its optimal location becomes critical. With the coming rise of edge computing and micro-data centers designed to bring data and applications closer to users to reduce latency and thereby improve application and workload performance, data management and logistics become even more complex. The edge is creating even more data, with increased data volumes having to be transmitted across networks and between clouds.</p> <p>Object-based data storage is now the dominant storage architecture globally, particularly in the cloud, and will be used to store 85 percent of the world’s data by 2025. Developed initially to handle the explosive growth of unstructured data, such as video, images, web pages, log files and IoT data, object storage saves data along with associated metadata in blocks as objects that can contain multiple information formats.</p> <p>It has a variety of advantages over file and block storage, including massive scalability, greater flexibility via metadata for analytics, better governance, faster retrieval, and improved cost efficiencies. In addition, continued technical advances are improving both the performance and the applicability of object storage for new use cases. A major challenge, however, is that the object-based storage systems used my various cloud providers are all different, making data synchronization and translation a challenge.</p> <p> </p> <p><strong>The Data Logistics Mandate</strong></p> <p>In this new world, Chief Data Officers and CIOs must optimize how they manage vast volumes of data across multiple clouds and data environments through better data logistics. There are more data silos, greater distribution of data, vast increases in volume, and a growing demand to understand, protect and exploit data for business growth and optimization while holding down costs.</p> <p>Among those logistical challenges are the need to keep track of where data resides, and cost-effectively synchronize, replicate and move data to optimize value, efficiency, security and governance based on cost differences, processing and analytics capabilities, performance advantages, and regulatory requirements.</p> <p>Organizations need to be able to be able to identify what data needs to be replicated and effectively transmitted and synchronized across different clouds and on-premise locations to improve the availability, security and value of data.</p> <p>For example, organizations increasingly need to move data to specific service providers to conduct analytics or take advantage of specific vendor technologies, lower processing and storage costs, or meet geographic requirements. Particularly when data replication and synchronization is a continuous activity, organizations need to automate this process based on established rules and policies to improve cost efficiency, eliminate errors and reduce management complexity.</p> <p>For object storage data, the capacity to fully utilize metadata to identify location, type and value is now a critical aspect of data logistics, as is the ability to transfer data with a minimum amount of performance degradation and data corruption. New solutions that can handle replication outside of the data path are delivering improved visibility, performance and data quality.</p> <p>Advancing data logistics is a major imperative for today’s data-driven organizations and their chief data officers. The mandate to improve data availability, performance, value and cost-efficiency will be a critical competitive differentiator in a multi-cloud, mega-data world.<br /><br /><strong>To get involved in this initiative, please reach out to <a href="mailto:dmurray@bpinetwork.org">Dave Murray</a>. </strong></p>
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      • id1358
      • date2020-07-21
      • title8 Innovation Trends Cultivating the 'Next Normal' Post COVID-19
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      • publisherBecker's Health IT
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      • urlhttps://www.beckershospitalreview.com/digital-transformation/providence-8-innovation-trends-cultivating-the-next-normal-post-covid-19.html
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      • titleThe power of emerging technologies: Finding value through data
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        • titleBringing Simplicity To Multi-Cloud Complexity
        • subtitleAdvancing Data Connectivity, Logistics and Value
        • summaryThis initiative aims to explore the forces, factors, challenges and requirements driving the need for improved data logistics in today’s multi-cloud world.
        • description<p><strong>Overview</strong></p> <p>The Business Performance Innovation (BPI) Network, in partnership with DBM Cloud Systems and the CMO Council, is undertaking research into the forces, factors, challenges and requirements driving the need for improved data logistics in today’s multi-cloud world. Global enterprises are seeking to integrate vast repositories of data across multiple public and private clouds and on-premise systems to extract more value, use and return on these assets. In particular, this relates to decision-support analytics, product and service delivery, customer intelligence and personalized engagement, operational improvement, business compliance, and continuity.</p> <p>While multi-cloud and hybrid cloud environments provide major advantages, they also increase the complexity of managing, translating, processing and moving data. Chief Data Officers, infrastructure IT executives and others in the enterprise are now seeking new and innovative ways to gain greater control, visibility, performance and efficiency in the way they manage data to optimize its value.</p> <p>The program will engage data and IT executives from major companies, as well as leading system integrators, consulting firms and solution providers to understand needs, requirements and best practices in optimizing data economics, protection and logistics in today’s multi-cloud, mega-data world.</p> <p><strong> </strong></p> <p><strong>Background</strong></p> <p>The growing importance of the Chief Data Officer underscores widespread recognition of the essential role and value of data and analytics in the modern, agile customer-centric enterprise. This is further compounded by the significant cost, challenge and complexity of unifying, migrating, replicating, protecting, storing and governing data “ponds, lakes and dams” in today’s multi-cloud and hybrid cloud computing environments.</p> <p>Data has become one of the chief engines of value creation. Its role in improving analytical decision making, enhancing our ability to understand, reach and engage customers, and increasing the value of both existing and new products and services has made data a highly valued currency and asset base for enterprises operating digitally across data borders, ramparts and fences.</p> <p>Fueled by an explosive proliferation of new data sources—from mobile computing, social media and rich media applications and services, to the advent of the Internet of Things, which will generate some 50 million connected sensors by the end of 2020—the amount and variety of data being stored is growing exponentially.  According Seagate Technology, the amount of data generated worldwide will increase to 163 zettabytes by 2025 from 12 zettabytes in 2015.</p> <p>In today’s multi-cloud, mega-data world, better Data Logistics and Performance Management (DLPM) has become essential to competing in the Data Economy. According to 451 Research, some 80 percent of companies are now utilizing two or more clouds. Three-quarters of companies say they are pursuing a hybrid/multi-cloud strategy.</p> <p>In this highly distributed compute environment, the requirements to understand where data resides across multiple public clouds and on-premise systems and cost-effectively store, protect and move data to its optimal location becomes critical. With the coming rise of edge computing and micro-data centers designed to bring data and applications closer to users to reduce latency and thereby improve application and workload performance, data management and logistics become even more complex. The edge is creating even more data, with increased data volumes having to be transmitted across networks and between clouds.</p> <p>Object-based data storage is now the dominant storage architecture globally, particularly in the cloud, and will be used to store 85 percent of the world’s data by 2025. Developed initially to handle the explosive growth of unstructured data, such as video, images, web pages, log files and IoT data, object storage saves data along with associated metadata in blocks as objects that can contain multiple information formats.</p> <p>It has a variety of advantages over file and block storage, including massive scalability, greater flexibility via metadata for analytics, better governance, faster retrieval, and improved cost efficiencies. In addition, continued technical advances are improving both the performance and the applicability of object storage for new use cases. A major challenge, however, is that the object-based storage systems used my various cloud providers are all different, making data synchronization and translation a challenge.</p> <p> </p> <p><strong>The Data Logistics Mandate</strong></p> <p>In this new world, Chief Data Officers and CIOs must optimize how they manage vast volumes of data across multiple clouds and data environments through better data logistics. There are more data silos, greater distribution of data, vast increases in volume, and a growing demand to understand, protect and exploit data for business growth and optimization while holding down costs.</p> <p>Among those logistical challenges are the need to keep track of where data resides, and cost-effectively synchronize, replicate and move data to optimize value, efficiency, security and governance based on cost differences, processing and analytics capabilities, performance advantages, and regulatory requirements.</p> <p>Organizations need to be able to be able to identify what data needs to be replicated and effectively transmitted and synchronized across different clouds and on-premise locations to improve the availability, security and value of data.</p> <p>For example, organizations increasingly need to move data to specific service providers to conduct analytics or take advantage of specific vendor technologies, lower processing and storage costs, or meet geographic requirements. Particularly when data replication and synchronization is a continuous activity, organizations need to automate this process based on established rules and policies to improve cost efficiency, eliminate errors and reduce management complexity.</p> <p>For object storage data, the capacity to fully utilize metadata to identify location, type and value is now a critical aspect of data logistics, as is the ability to transfer data with a minimum amount of performance degradation and data corruption. New solutions that can handle replication outside of the data path are delivering improved visibility, performance and data quality.</p> <p>Advancing data logistics is a major imperative for today’s data-driven organizations and their chief data officers. The mandate to improve data availability, performance, value and cost-efficiency will be a critical competitive differentiator in a multi-cloud, mega-data world.<br /><br /><strong>To get involved in this initiative, please reach out to <a href="mailto:dmurray@bpinetwork.org">Dave Murray</a>. </strong></p>
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      • descriptionThis exclusive Transform to Better Perform CIO Roundtable has been organized by the Business Performance Innovation (BPI) Network to generate fresh thinking and best practice ideas around an emerging, new scorecard for IT. Being held in conjunction with DatacenterDynamics’ Internet Event at the San Francisco Marriot Marquis, the noon roundtable will bring together a small group of top executives to discuss the new demands and requirements on IT to advance competitive differentiation, build business value and engage customer markets.  The discussion will draw on new BPI Network research and provide ideas and content for a new global report. Participating IT executives are also invited to attend the DatacenterDynamics conference as VIP guests if they choose. To enroll, email Sally: <a href="mailto:squigley@bpinetwork.org">squigley@bpinetwork.org</a>.
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      • description<p>An <a href="http://reinventdatacenters.com/advocacy/report">in-depth, global report</a> from the <a href="http://bpinetwork.org/">BPI Network</a> explains how this major shift is already changing the nature of IT, enhancing security and increasing reliability for many companies – and why those who wait will be left behind. Join BPI Editorial Director <strong>Tom Murphy</strong> and <strong>Richard Garratt</strong>, director of data center solutions at Dimension Data, in an important <a href="https://www.apqc.org/knowledge-base/documents/using-data-center-drive-innovation">APQC podcast</a> as they analyze the cause and explore how this transformation will improve the quality of services to consumers while positioning businesses to grow with far greater cost-efficiencies.  </p>
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      • description<p>Today’s senior FP&A executives are facing a critical need to provide a more responsive, flexible and continuous planning, budgeting and forecasting process that will allow them to adapt to changing market conditions and opportunities, which will enable their financial planning to become more relevant and valuable to business outcomes. In this thought leadership webinar we will look at the organizational roadblocks and challenges that are keeping the financial planning function from delivering greater business and decision-making value across the organization and hear from leading executives on how to implement new thinking and processes.</p>
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        • titlePredictability Through Planning Agility
        • subtitleBest Practices in Collaborative Budgeting and Continuous Business Rebalancing
        • summary<p>Through the “Predictability Through Planning Agility” program, the Business Performance Innovation Network will investigate how organizations can make financial processes more relevant in driving organizational excellence, efficiency and decision dexterity, while improving forecasting and budgeting accuracy.  </p>
        • description<p>Improving the accuracy, value and efficiency of financial planning, forecasting and budgeting should be an important goal for any organization.  Research shows companies that are adept in these processes outperform their competition. Yet financial processes and systems frequently lack the agility and responsiveness to keep pace with changing business needs and developments.  Budgeting is often excessively time-consuming and arduous, while the final product is typically out-of-date on arrival.  Financial planning processes should, but often do not, motivate and drive organizational performance. There is a real need for greater timeliness and frequency in budgeting and forecasting with new systems and processes that can improve planning flexibility, speed, and accuracy. Companies need to determine how they can increase collaboration and the value of financial planning across the entire organization.</p> <p><a title="Download Report Now" href="../../../thought-leadership/studies/49/download-report-predictability-through-planning-agility">Download Report Now »</a></p> <p>Through the “Predictability Through Planning Agility” program, the Business Performance Innovation Network will investigate how organizations can make financial processes more relevant in driving organizational excellence, efficiency and decision dexterity, while improving forecasting and budgeting accuracy.  The program will look at the value and limitations of corporate financial forecasting and budgeting processes and discuss the right practices and approaches for improving the performance management aspects of financial processes.  </p>
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      • body<p>In today’s environment of accelerated business cycles, non-traditional global competitiveness and financial accountability, making good decisions is one of the most important functions of a business. However, decision making may be one of the least understood or defined processes within the organization. Executive decisions have become more costly and complex, and yet are critical to a company’s success.</p>
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CORE_PATH	/home/bpinorg/public_html/lib/
CAKE_VERSION	2.3.8
CSS	/home/bpinorg/public_html/app/webroot/css/
CSS_URL	css/
DS	/
FULL_BASE_URL	https://bpinetwork.org
IMAGES	/home/bpinorg/public_html/app/webroot/img/
IMAGES_URL	img/
JS	/home/bpinorg/public_html/app/webroot/js/
JS_URL	js/
LOGS	/home/bpinorg/public_html/app/tmp/logs/
ROOT	/home/bpinorg/public_html
TESTS	/home/bpinorg/public_html/app/Test/
TMP	/home/bpinorg/public_html/app/tmp/
VENDORS	/home/bpinorg/public_html/vendors/
WEBROOT_DIR	webroot
WWW_ROOT	/home/bpinorg/public_html/app/webroot/

PHP Environment

Environment Variable	Value
Php Version	5.6.40
User	bpinorg
Home	/home/bpinorg
Fcgi Role	RESPONDER
Redirect Redirect Unique Id	aBA6QHFtKuJ7eSgU-Wjd3gAAwgA
Redirect Redirect Script Url	/innovator_profiles/view/51
Redirect Redirect Script Uri	https://bpinetwork.org/innovator_profiles/view/51
Redirect Redirect Https	on
Redirect Redirect Ssl Tls Sni	bpinetwork.org
Redirect Redirect Http2	on
Redirect Redirect H2push	off
Redirect Redirect H2 Push	off
Redirect Redirect H2 Pushed
Redirect Redirect H2 Pushed On
Redirect Redirect H2 Stream Id	7
Redirect Redirect H2 Stream Tag	9290-41-7
Redirect Redirect Status	200
Redirect Unique Id	aBA6QHFtKuJ7eSgU-Wjd3gAAwgA
Redirect Script Url	/innovator_profiles/view/51
Redirect Script Uri	https://bpinetwork.org/innovator_profiles/view/51
Redirect Https	on
Redirect Ssl Tls Sni	bpinetwork.org
Redirect Http2	on
Redirect H2push	off
Redirect H2 Push	off
Redirect H2 Pushed
Redirect H2 Pushed On
Redirect H2 Stream Id	7
Redirect H2 Stream Tag	9290-41-7
Redirect Status	200
Unique Id	aBA6QHFtKuJ7eSgU-Wjd3gAAwgA
Script Url	/innovator_profiles/view/51
Script Uri	https://bpinetwork.org/innovator_profiles/view/51
Https	on
Ssl Tls Sni	bpinetwork.org
Http2	on
H2push	off
H2 Push	off
H2 Pushed
H2 Pushed On
H2 Stream Id	7
H2 Stream Tag	9290-41-7
Proxy-nokeepalive	1
Http Accept	*/*
Http User Agent	Mozilla/5.0 AppleWebKit/537.36 (KHTML, like Gecko; compatible; ClaudeBot/1.0; +claudebot@anthropic.com)
Http Cookie	CAKEPHP=cl9kk8ec83l5mnvrqfoc8im506
Http Accept Encoding	gzip, br, zstd, deflate
Http Host	bpinetwork.org
Http X Https	1
Path	/usr/local/jdk/bin:/usr/kerberos/sbin:/usr/kerberos/bin:/usr/local/sbin:/usr/local/bin:/sbin:/bin:/usr/sbin:/usr/bin:/usr/X11R6/bin:/usr/local/bin:/usr/X11R6/bin:/root/bin:/opt/bin
Server Signature
Server Software	Apache
Server Name	bpinetwork.org
Server Addr	173.231.198.134
Server Port	443
Remote Addr	18.188.103.74
Document Root	/home/bpinorg/public_html
Request Scheme	https
Context Prefix
Context Document Root	/home/bpinorg/public_html
Server Admin	webmaster@bpinetwork.org
Script Filename	/home/bpinorg/public_html/app/webroot/index.php
Remote Port	18031
Redirect Url	/app/webroot/innovator_profiles/view/51
Gateway Interface	CGI/1.1
Server Protocol	HTTP/2.0
Request Method	GET
Query String
Request Uri	/innovator_profiles/view/51
Script Name	/app/webroot/index.php
Php Self	/app/webroot/index.php
Request Time Float	1745893952.0965
Request Time	1745893952
Argc	0

Included Files

Include Paths

• 0/home/bpinorg/public_html/lib
• 2/opt/cpanel/ea-php56/root/usr/share/pear
• 3-> /home/bpinorg/public_html/lib/Cake/

Included Files

• core
  • Behavior
    • 0CORE/Model/Behavior/ContainableBehavior.php
  • Cache
    • 0CORE/Cache/Cache.php
    • 1CORE/Cache/Engine/FileEngine.php
    • 2CORE/Cache/CacheEngine.php
  • Component
    • 0CORE/Controller/Component/SessionComponent.php
    • 1CORE/Controller/Component/AuthComponent.php
  • Config
    • 0CORE/Config/routes.php
    • 1CORE/Config/config.php
  • Controller
    • 0CORE/Controller/Controller.php
    • 1CORE/Controller/ComponentCollection.php
    • 2CORE/Controller/Component.php
  • Datasource
    • 0CORE/Model/Datasource/Database/Mysql.php
    • 1CORE/Model/Datasource/DboSource.php
    • 2CORE/Model/Datasource/DataSource.php
    • 3CORE/Model/Datasource/CakeSession.php
  • Error
    • 0CORE/Error/exceptions.php
    • 1CORE/Error/ErrorHandler.php
  • I18n
    • 0CORE/I18n/I18n.php
    • 1CORE/I18n/L10n.php
  • Log
    • 0CORE/Log/CakeLog.php
    • 1CORE/Log/LogEngineCollection.php
    • 2CORE/Log/Engine/FileLog.php
    • 3CORE/Log/Engine/BaseLog.php
    • 4CORE/Log/CakeLogInterface.php
  • Model
    • 0CORE/Model/Model.php
    • 1CORE/Model/BehaviorCollection.php
    • 2CORE/Model/ConnectionManager.php
    • 3CORE/Model/ModelBehavior.php
  • Network
    • 0CORE/Network/CakeRequest.php
    • 1CORE/Network/CakeResponse.php
  • Other
    • 0CORE/bootstrap.php
    • 1CORE/basics.php
    • 2CORE/Core/App.php
    • 3CORE/Core/Configure.php
    • 4CORE/Core/CakePlugin.php
    • 5CORE/Event/CakeEventListener.php
    • 6CORE/Event/CakeEvent.php
    • 7CORE/Event/CakeEventManager.php
    • 8CORE/Core/Object.php
  • Routing
    • 0CORE/Routing/Dispatcher.php
    • 1CORE/Routing/Filter/AssetDispatcher.php
    • 2CORE/Routing/DispatcherFilter.php
    • 3CORE/Routing/Filter/CacheDispatcher.php
    • 4CORE/Routing/Router.php
    • 5CORE/Routing/Route/CakeRoute.php
    • 6CORE/Routing/Route/RedirectRoute.php
    • 7CORE/Routing/Route/PluginShortRoute.php
  • Utility
    • 0CORE/Utility/Hash.php
    • 1CORE/Utility/ObjectCollection.php
    • 2CORE/Utility/Debugger.php
    • 3CORE/Utility/String.php
    • 4CORE/Utility/ClassRegistry.php
    • 5CORE/Utility/Inflector.php
    • 6CORE/Utility/Folder.php
  • View
    • 0CORE/View/HelperCollection.php
• app
  • Component
    • 0APP/Controller/Component/PasswordComponent.php
  • Config
    • 0APP/Config/core.php
    • 1APP/Config/bootstrap.php
    • 2APP/Config/routes.php
    • 3APP/Config/database.php
  • Controller
    • 0APP/Controller/InnovatorProfilesController.php
    • 1APP/Controller/AppController.php
  • Model
    • 0APP/Model/Menu.php
    • 1APP/Model/AppModel.php
    • 2APP/Model/User.php
    • 3APP/Model/Article.php
    • 4APP/Model/Event.php
    • 5APP/Model/Report.php
    • 6APP/Model/Leader.php
    • 7APP/Model/Program.php
    • 8APP/Model/Tag.php
    • 9APP/Model/Brainwafe.php
    • 10APP/Model/Tracking.php
    • 11APP/Model/Download.php
    • 12APP/Model/MediaCoverage.php
    • 13APP/Model/InnovatorProfile.php
  • Other
    • 0APP/webroot/index.php
    • 1APP/Lib/AppError.php
    • 2APP/Vendor/ChromePhp/ChromePhp.php
    • 3APP/Lib/Captcha/Captcha.php
• plugins
  • DebugKit
    • Component
      • 0DebugKit/Controller/Component/ToolbarComponent.php
    • Plugin
      • 0DebugKit/Lib/DebugMemory.php
      • 1DebugKit/Lib/Panel/HistoryPanel.php
      • 2DebugKit/Lib/DebugPanel.php
      • 3DebugKit/Lib/Panel/SessionPanel.php
      • 4DebugKit/Lib/Panel/RequestPanel.php
      • 5DebugKit/Lib/Panel/SqlLogPanel.php
      • 6DebugKit/Lib/Panel/TimerPanel.php
      • 7DebugKit/Lib/Panel/LogPanel.php
      • 8DebugKit/Lib/Log/Engine/DebugKitLog.php
      • 9DebugKit/Lib/Panel/VariablesPanel.php
      • 10DebugKit/Lib/Panel/EnvironmentPanel.php
      • 11DebugKit/Lib/Panel/IncludePanel.php
      • 12DebugKit/Lib/DebugTimer.php
  • LessCompiler
    • Component
      • 0LessCompiler/Controller/Component/LessComponent.php
    • Plugin
      • 0LessCompiler/Lib/LessCompiler.php
      • 1LessCompiler/Vendor/lessc.php
  • Minify
    • Config
      • 0Minify/Config/routes.php
  • Opauth
    • Config
      • 0Opauth/Config/bootstrap.php
      • 1Opauth/Config/routes.php