This article was initially published in bobsguide.com
In Geoffrey A. Moore’s seminal book Crossing the Chasm he describes a five technology adopter lifecycles of innovators, early adopters, early majority, late majority and laggards. The “chasm” is the most difficult step of innovations transitioning between visionaries (early adopters) and pragmatists (early majority). In my experience at each of the cycles noted below, the transition over the chasm is where the most vocal resistance and calls of “hype” are usually heard. The posit for this article is that Cloud Computing is well into the early majority phase while “Big Data Analytics” is just now crossing the chasm in the Financial Services industry, and suggests how you might think about potential impacts and practical approaches.
As background, it may be interesting looking back at many of the technology innovation cycles the have impacted Financial Services over the last 30 plus years:
· 1980’s: The explosion of the Personal Computer, Ethernet, and introduction of car phones signaled the beginning of individual control of information and being location agnostic.
· 1990’s: Relational Databases (RDBMS), client-server architecture, electronic trading, flip phones and early adoption of the World Wide Web began changing core business and operating models and improved access to data.
· 2000’s: The early majority acceptance of the Internet as a business platform, complex event processing, Blackberries, laptops vs desktops, business intelligence tools, open source software and early adoption of Cloud Computing delivered unprecedented productivity improvements for people working literally anywhere in the world.
· 2010’s: The current cycle of mobile computing, social media, early adoption of Big Data Analytics and early/late majority acceptance of Cloud Computing/virtualization is changing the way that we interact with each other on a personal level as well as with our employees, employers, customers and business providers. The visionary Internet of Things (IoT) promises to change the way we interact with just about everything else.
Cloud Computing
Marc Benioff of Salesforce.com was the first person really beating the drum regarding the power of Cloud Computing. More than just hosting software as an ASP – often with a terminal emulator supporting fat client applications – the Cloud was, and is, all about functionality and interoperability with variable pricing and minimal IT support needed. In theory a business user can put down a credit card and have immediate access to a fully supported platform to support a specific business function. Should they need additional functionality, the user can access that quickly from the Cloud ecosystem of other providers to meet their specific needs. The reality is that there is usually some conversion and implementation needed, but Cloud computing makes running a business vastly easier that installing and integrating on-premises systems.
For example, PanoVista.co’s partners offer solutions such as data governance, global equity research and portfolio construction, all asset class performance attribution, and collateral management delivered via Amazon Web Services (AWS) and Microsoft Azure clouds. Clients benefit by being productive within days or weeks rather than months or years, and our partners can quickly develop new functionality and keep all clients current with drastically lower support costs.
Big Data Analytics
Big Data is a term that references the 3 V’s: Volume, Velocity and Variety. Whereas structured data in Financial Services often contains very large data sets and real time pricing and transaction data, it’s really the huge Volume and Variety of unstructured data that adds complexity that traditional relational databases cannot support. This is where new - often open source – Big Data technologies and techniques come into play. Hadoop, NoSQL, and text search are all technologies that can scale horizontally (using distributed servers) across internal and Cloud-based structured and unstructured data sources to feed analytical languages (such as R and Python) and business intelligence applications to bring new insights into business.
Big Data Analytics is an area that has not yet crossed the chasm from the visionaries to the pragmatists in the Financial Services industry. For examples of how early adopters are using these technologies, visit www.panovista.co/blog.
Security
One common theme of all of the innovation cycles noted here is that as our access to information and productivity has steadily increased, so too have the information security challenges. The perception of many firms is that on premise data is more secure than either private or public Cloud providers. However, recent information breaches by companies either not keeping their applications current or not encrypting their data in place, along with the great strides made by Cloud providers, is starting to change that perception.
At the recent AWS Summit in New York in July, Nate Sammons, Principal Architect at NASDAQ, provided a case study of their data security and encryption approach. He noted that encryption slows down processing speed, about 25% in their case; this performance drag is one explanation of why many internal IT teams might not enable encryption. However, one advantage of AWS Elastic Compute Cloud (EC2) is that NASDAQ can dynamically scale up processing as needed to overcome the encryption overhead across the millions of daily trades processed, as well as to support the predictive analytics they perform using a variety of open-source technologies.
What does this mean to the Financial Services industry?
As the industry continues to change, Cloud Computing and advanced Big Data analytics will have a growing positive impact on streamlining existing and creating new business models. However, it is possible to start with smaller projects by looking for key decision points that may lead to incremental change. Some questions to ask yourself and your business include:
· Can our existing technologies be moved to the Cloud for a positive ROI? For example, is a core platform overdue for an upgrade along with the supporting hardware and software, and is a Cloud option available? If the core platform is due for replacement, what is the true TCO (total cost of ownership) of competing on premise vs. Cloud offerings?
· Are we competitive enough? Do we have control of our data or do we have gaps in data ownership and quality? Do our teams have the right tools to streamline and automate their daily work? Are we really getting -– and using -- the best information possible to manage our investments and make important business decisions? Are we using data visualization effectively and pro-actively, and is the underlying information feeding our Business Intelligence tools correct and validated?
· Are we responsive enough? Can we uncover new opportunities by mining our own data? When new client or business opportunities arise, can we react fast enough or do our internal processes bog us down? Is our environment flexible enough to scale up and down as needed?
Of course, information security should be foremost in considering these questions and potential alternatives. A final note from the ASW Summit noted above is that many healthcare providers are adopting the Cloud – including the need to support HIPAA compliance.
In closing, the recommendation is to always think about how you can improve your business, either by making it more efficient, more accurate, more responsive and more competitive. You may find that Cloud Computing and potentially newer technologies will play a big part in achieving your goals.
In Geoffrey A. Moore’s seminal book Crossing the Chasm he describes a five technology adopter lifecycles of innovators, early adopters, early majority, late majority and laggards. The “chasm” is the most difficult step of innovations transitioning between visionaries (early adopters) and pragmatists (early majority). In my experience at each of the cycles noted below, the transition over the chasm is where the most vocal resistance and calls of “hype” are usually heard. The posit for this article is that Cloud Computing is well into the early majority phase while “Big Data Analytics” is just now crossing the chasm in the Financial Services industry, and suggests how you might think about potential impacts and practical approaches.
As background, it may be interesting looking back at many of the technology innovation cycles the have impacted Financial Services over the last 30 plus years:
· 1980’s: The explosion of the Personal Computer, Ethernet, and introduction of car phones signaled the beginning of individual control of information and being location agnostic.
· 1990’s: Relational Databases (RDBMS), client-server architecture, electronic trading, flip phones and early adoption of the World Wide Web began changing core business and operating models and improved access to data.
· 2000’s: The early majority acceptance of the Internet as a business platform, complex event processing, Blackberries, laptops vs desktops, business intelligence tools, open source software and early adoption of Cloud Computing delivered unprecedented productivity improvements for people working literally anywhere in the world.
· 2010’s: The current cycle of mobile computing, social media, early adoption of Big Data Analytics and early/late majority acceptance of Cloud Computing/virtualization is changing the way that we interact with each other on a personal level as well as with our employees, employers, customers and business providers. The visionary Internet of Things (IoT) promises to change the way we interact with just about everything else.
Cloud Computing
Marc Benioff of Salesforce.com was the first person really beating the drum regarding the power of Cloud Computing. More than just hosting software as an ASP – often with a terminal emulator supporting fat client applications – the Cloud was, and is, all about functionality and interoperability with variable pricing and minimal IT support needed. In theory a business user can put down a credit card and have immediate access to a fully supported platform to support a specific business function. Should they need additional functionality, the user can access that quickly from the Cloud ecosystem of other providers to meet their specific needs. The reality is that there is usually some conversion and implementation needed, but Cloud computing makes running a business vastly easier that installing and integrating on-premises systems.
For example, PanoVista.co’s partners offer solutions such as data governance, global equity research and portfolio construction, all asset class performance attribution, and collateral management delivered via Amazon Web Services (AWS) and Microsoft Azure clouds. Clients benefit by being productive within days or weeks rather than months or years, and our partners can quickly develop new functionality and keep all clients current with drastically lower support costs.
Big Data Analytics
Big Data is a term that references the 3 V’s: Volume, Velocity and Variety. Whereas structured data in Financial Services often contains very large data sets and real time pricing and transaction data, it’s really the huge Volume and Variety of unstructured data that adds complexity that traditional relational databases cannot support. This is where new - often open source – Big Data technologies and techniques come into play. Hadoop, NoSQL, and text search are all technologies that can scale horizontally (using distributed servers) across internal and Cloud-based structured and unstructured data sources to feed analytical languages (such as R and Python) and business intelligence applications to bring new insights into business.
Big Data Analytics is an area that has not yet crossed the chasm from the visionaries to the pragmatists in the Financial Services industry. For examples of how early adopters are using these technologies, visit www.panovista.co/blog.
Security
One common theme of all of the innovation cycles noted here is that as our access to information and productivity has steadily increased, so too have the information security challenges. The perception of many firms is that on premise data is more secure than either private or public Cloud providers. However, recent information breaches by companies either not keeping their applications current or not encrypting their data in place, along with the great strides made by Cloud providers, is starting to change that perception.
At the recent AWS Summit in New York in July, Nate Sammons, Principal Architect at NASDAQ, provided a case study of their data security and encryption approach. He noted that encryption slows down processing speed, about 25% in their case; this performance drag is one explanation of why many internal IT teams might not enable encryption. However, one advantage of AWS Elastic Compute Cloud (EC2) is that NASDAQ can dynamically scale up processing as needed to overcome the encryption overhead across the millions of daily trades processed, as well as to support the predictive analytics they perform using a variety of open-source technologies.
What does this mean to the Financial Services industry?
As the industry continues to change, Cloud Computing and advanced Big Data analytics will have a growing positive impact on streamlining existing and creating new business models. However, it is possible to start with smaller projects by looking for key decision points that may lead to incremental change. Some questions to ask yourself and your business include:
· Can our existing technologies be moved to the Cloud for a positive ROI? For example, is a core platform overdue for an upgrade along with the supporting hardware and software, and is a Cloud option available? If the core platform is due for replacement, what is the true TCO (total cost of ownership) of competing on premise vs. Cloud offerings?
· Are we competitive enough? Do we have control of our data or do we have gaps in data ownership and quality? Do our teams have the right tools to streamline and automate their daily work? Are we really getting -– and using -- the best information possible to manage our investments and make important business decisions? Are we using data visualization effectively and pro-actively, and is the underlying information feeding our Business Intelligence tools correct and validated?
· Are we responsive enough? Can we uncover new opportunities by mining our own data? When new client or business opportunities arise, can we react fast enough or do our internal processes bog us down? Is our environment flexible enough to scale up and down as needed?
Of course, information security should be foremost in considering these questions and potential alternatives. A final note from the ASW Summit noted above is that many healthcare providers are adopting the Cloud – including the need to support HIPAA compliance.
In closing, the recommendation is to always think about how you can improve your business, either by making it more efficient, more accurate, more responsive and more competitive. You may find that Cloud Computing and potentially newer technologies will play a big part in achieving your goals.
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