As any architect worth his brick and mortar will tell you, a solid foundation is the key to achieving the desired outcome of any substantial structure. This is certainly true when it comes to implementing a successful digital transformation with an eye toward maximizing the benefits of artificial intelligence and all of the other new technologies now available.
While it is easy for C Suite decision makers to become dazzled by the potential offered by advances in technology, it is also important to remember that emerging technology solutions are not guaranteed to succeed unless companies merge their digital & technology agenda with their corporate vision.
At Dell Technologies, we encourage our customers to look beyond the capabilities of a particular technology like AI and focus instead on the internal layers of application that go into creating a flexible and robust foundation on which myriad AI solutions can prosper.
At its core, any smart digital agenda has four main goals: modernizing the workforce, enhancing your customer experience, encouraging the adopting of flexible new business models, and gaining a competitive advantage.
To do so effectively, the 21st century CEO, or the Connected CEO in other words, must recognize the stages needed to give tomorrow’s technology the platform it needs to succeed, from edge to core to cloud.
Step One involves taking a hard look at your existing legacy structure, establishing its strengths and weaknesses, and deciding how best to incorporate and/or upgrade your IT designs to best suit your company’s goals. Do your applications need to be modernized, or are they capable of handling the needs of tomorrow’s mobile, analytics, data and cloud requirements? Would your data centers best benefit from more traditional (IaaS) structures, a cloud native (PaaS) setup, or a more flexible hybrid combination of on and offsite repositories? For many of today’s businesses, infrastructure modernization relies on a host of products capable of enabling a hybrid cloud platform designed to drive cost efficiencies and increase speed. Special attention must be paid to the ways in which data is to be managed, stored, and shared, both throughout the company and externally.
Step Two focuses on building a layer of customer engagement IT, which not only heightens the all-important customer experience, but opens new channels for data mining that serve to improve data quality and enhance message focus. This helps a company better understand its customers, and thus allows them to build more accurate machine learning algorithms to give them an added competitive edge and increase brand trust and loyalty down the line.
Advances in AI, as well as augmented reality (AR), virtual reality (VR) and the Internet of Things (IoT), have led to a dramatic shift in the way modern consumers interact with the digital world. As these solutions further break down the barriers between human and machine relationships both online and in-store, the user experience will continue to evolve and the ways companies communicate with their customers will grow more personal.
Emerging customer engagement apps rely on the formation of a new intelligent intermediary layer capable of connecting people and systems, and for savvy companies, their potential goes beyond the customer experience to include the workplace itself. Virtual assistants, chatbots, kiosks and digital assistants have the power to spread real-time information in ways previously only imagined, while intelligent things such as smart phones and cameras allow humans and machines to collaborate throughout every step in the supply chain. Both consumer and employee benefit from the same technology.
Step Three involves the all-important data layer. If, as Michael Dell states, “data is today’s rocket fuel”, then this layer is the navigation system guiding a company’s vision. The role of a strong data centric analytics platform and corresponding data lake goes beyond the simple collection, storage and prioritizing of data to include analyzing these mountains of information and predicting trends based on past performance. Properly implemented, it aids in the prevention of data drift, improves data integrity, hones customer focus and offers a user-friendly interface to provide the C Suite with up-to-the-minute facts on which to base decisions.
The earlier a company commits to a smart data strategy, the more cost effective the results and the easier it is to customize new applications. Early adopters also benefit from greatly reduced data migration periods and eliminate the need for future apps to be reworked to align with their existing central data repository.
Once a strong data layer is firmly in place, Step Four can then focus securely on the advantages of AI. This layer enables companies to develop well-governed, accurate machine learning models that apply to every stage of their business. Machine learning is capable of taking on those tasks at which computers excel, such as analyzing large amounts of data, monitoring the business environment and making accurate predictions based upon past performance as well as plotting trends. This frees up the workforce to engage in more human-centric functions such as planning, strategizing and orchestrating the business based on that output.
This allows a company to:
◈ grow revenue streams by identifying new areas of business and using predictive analysis
◈ increase efficiency by relating pertinent information in real-time and improving productivity by using analytical insights to enhance focus
◈ improve customer service and satisfaction through more personalized engagement and predictive insights
◈ boost security and compliance by monitoring unusual behavior and broken patterns throughout the entire enterprise, including the cloud
◈ create customized algorithms for present and future machine learning solutions that can function to improve performance both internally and externally, building upon acquired knowledge to improve future performance
Gartner states that “the ability to use AI to enhance decision making, reinvent business models and ecosystems, and remake the customer experience will drive the payoff for digital initiatives through 2025.”
However, investing in a series of well-planned intermediary layers has additional payoffs that go beyond enhancing AI solutions. Solid technology foundations help emerging tech integrate more efficiently with one another, thereby unlocking a host of new methods and substantially increasing their reach.
AI, AR, VR, IoT and Blockchain all benefit equally from a solid, up-to-date internal foundation – IoT to collect data, AI to analyze, AR/VR to visualize, cloud services to add speed and flexibility, and Blockchain to secure. Given the proper base, these technologies go from standalone solutions to a cohesive business organization infrastructure capable of being customized to a company’s needs and greatly increasing both their present and future value.
The key to a successful digital transformation that allows companies to get the most out of tomorrow’s technology and maximize return on investment lies in sound preparation and a view to the long term. These often overlooked internal layers are the unsung heroes of the Digital Age, and their importance cannot be underestimated.
At Dell Technologies, we encourage our customers to look beyond the capabilities of a particular technology like AI and focus instead on the internal layers of application that go into creating a flexible and robust foundation on which myriad AI solutions can prosper.
Customizing your Digital Agenda – The Value of Layers
At its core, any smart digital agenda has four main goals: modernizing the workforce, enhancing your customer experience, encouraging the adopting of flexible new business models, and gaining a competitive advantage.
To do so effectively, the 21st century CEO, or the Connected CEO in other words, must recognize the stages needed to give tomorrow’s technology the platform it needs to succeed, from edge to core to cloud.
Step One involves taking a hard look at your existing legacy structure, establishing its strengths and weaknesses, and deciding how best to incorporate and/or upgrade your IT designs to best suit your company’s goals. Do your applications need to be modernized, or are they capable of handling the needs of tomorrow’s mobile, analytics, data and cloud requirements? Would your data centers best benefit from more traditional (IaaS) structures, a cloud native (PaaS) setup, or a more flexible hybrid combination of on and offsite repositories? For many of today’s businesses, infrastructure modernization relies on a host of products capable of enabling a hybrid cloud platform designed to drive cost efficiencies and increase speed. Special attention must be paid to the ways in which data is to be managed, stored, and shared, both throughout the company and externally.
Step Two focuses on building a layer of customer engagement IT, which not only heightens the all-important customer experience, but opens new channels for data mining that serve to improve data quality and enhance message focus. This helps a company better understand its customers, and thus allows them to build more accurate machine learning algorithms to give them an added competitive edge and increase brand trust and loyalty down the line.
Advances in AI, as well as augmented reality (AR), virtual reality (VR) and the Internet of Things (IoT), have led to a dramatic shift in the way modern consumers interact with the digital world. As these solutions further break down the barriers between human and machine relationships both online and in-store, the user experience will continue to evolve and the ways companies communicate with their customers will grow more personal.
Emerging customer engagement apps rely on the formation of a new intelligent intermediary layer capable of connecting people and systems, and for savvy companies, their potential goes beyond the customer experience to include the workplace itself. Virtual assistants, chatbots, kiosks and digital assistants have the power to spread real-time information in ways previously only imagined, while intelligent things such as smart phones and cameras allow humans and machines to collaborate throughout every step in the supply chain. Both consumer and employee benefit from the same technology.
Step Three involves the all-important data layer. If, as Michael Dell states, “data is today’s rocket fuel”, then this layer is the navigation system guiding a company’s vision. The role of a strong data centric analytics platform and corresponding data lake goes beyond the simple collection, storage and prioritizing of data to include analyzing these mountains of information and predicting trends based on past performance. Properly implemented, it aids in the prevention of data drift, improves data integrity, hones customer focus and offers a user-friendly interface to provide the C Suite with up-to-the-minute facts on which to base decisions.
The earlier a company commits to a smart data strategy, the more cost effective the results and the easier it is to customize new applications. Early adopters also benefit from greatly reduced data migration periods and eliminate the need for future apps to be reworked to align with their existing central data repository.
Once a strong data layer is firmly in place, Step Four can then focus securely on the advantages of AI. This layer enables companies to develop well-governed, accurate machine learning models that apply to every stage of their business. Machine learning is capable of taking on those tasks at which computers excel, such as analyzing large amounts of data, monitoring the business environment and making accurate predictions based upon past performance as well as plotting trends. This frees up the workforce to engage in more human-centric functions such as planning, strategizing and orchestrating the business based on that output.
This allows a company to:
◈ grow revenue streams by identifying new areas of business and using predictive analysis
◈ increase efficiency by relating pertinent information in real-time and improving productivity by using analytical insights to enhance focus
◈ improve customer service and satisfaction through more personalized engagement and predictive insights
◈ boost security and compliance by monitoring unusual behavior and broken patterns throughout the entire enterprise, including the cloud
◈ create customized algorithms for present and future machine learning solutions that can function to improve performance both internally and externally, building upon acquired knowledge to improve future performance
Reaping Multiple Benefits to Increase ROI
Gartner states that “the ability to use AI to enhance decision making, reinvent business models and ecosystems, and remake the customer experience will drive the payoff for digital initiatives through 2025.”
However, investing in a series of well-planned intermediary layers has additional payoffs that go beyond enhancing AI solutions. Solid technology foundations help emerging tech integrate more efficiently with one another, thereby unlocking a host of new methods and substantially increasing their reach.
AI, AR, VR, IoT and Blockchain all benefit equally from a solid, up-to-date internal foundation – IoT to collect data, AI to analyze, AR/VR to visualize, cloud services to add speed and flexibility, and Blockchain to secure. Given the proper base, these technologies go from standalone solutions to a cohesive business organization infrastructure capable of being customized to a company’s needs and greatly increasing both their present and future value.
The key to a successful digital transformation that allows companies to get the most out of tomorrow’s technology and maximize return on investment lies in sound preparation and a view to the long term. These often overlooked internal layers are the unsung heroes of the Digital Age, and their importance cannot be underestimated.
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