All cloud insights Flashcards
What percentage of their applications do large companies use on the cloud
As a median, large companies run only 15 to 20 percent of their applications in cloud, even when they have been running cloud programs for years and even after they account for the use of software-as-a-service (SaaS) products
What is the reason for this disconnect between aspiration and reality (They want to be on cloud but are not adopting it)
Getting value from public cloud, it turns out, is complicated. Companies have spent the past several decades building enterprise technology organizations, processes, and architectures designed to work for on-premises environments. Much of that needs to change.
What could transform this and lead to more of a cloud initiative?
Generative AI could transform the cloud investment-and-return equation. When McKinsey gathered nearly 80 CTOs and cloud program leaders together this fall, we heard that many believe generative AI may be a disruptor that transforms ROI dynamics for cloud programs and accelerates cloud adoption.
There are two elements to this opportunity. One is using cloud to support generative AI initiatives. With its massive calls on compute, storage, and networking, generative AI needs cloud to scale. Generative AI’s complexity, moreover, requires implementation via scalable enterprise cloud platforms rather than via disconnected pilots and initiatives run by individual development teams.
The second element of opportunity is using generative AI capabilities to accelerate cloud programs. Currently, remediating some applications to run effectively in cloud typically requires investments equal to several years’ worth of support and maintenance costs. Early efforts to apply generative AI to application remediation and migration have indicated a 40 percent reduction in time and investment required, though much work still is needed to understand how the improvements apply for different types of applications
How much can cloud generate in EBITDA by 2030
Cloud can generate about $3 trillion in EBITDA by 2030.
The value cloud generates from enabling businesses to innovate is worth HOW MANY TIMES MORE Than what is possible by reducing IT costs
The value cloud generates from enabling businesses to innovate is worth more than five times what is possible by simply reducing IT costs.
Which region has the most to gain from cloud?
Asian companies have the most to gain from cloud, with $1.2 trillion in EBITDA by 2030 at stake, driven by a higher rate of baseline revenue growth and more room to grow. American institutions stand to capture about $1.1 trillion in cloud value, while European institutions may have a somewhat smaller opportunity of $773 billion, primarily due to regulatory headwind
What % of companies have fully captured cloud’s potential value?
Only 10 percent of companies have fully captured cloud’s potential value, while another 50 percent are starting to capture it, and the remaining 40 percent have seen no material value.
What are the 3 things companies that capture ROI in cloud do well?
Companies that have captured the most ROI consistently do three things well: work closely with business leaders to focus on high-value business cases, build a robust cloud foundation, and adopt a product-oriented operating model.
What are the primary sources of lost value in cloud programs
Lost value in cloud programs comes from three primary sources: unrealized use cases (focusing on IT savings rather than new value), cloud sprawl (redundant cloud foundations), and stalled adoption (breakeven generally comes at around 50 percent cloud adoption). Taken together, these three factors can completely erase the benefits cloud can provide—and even destroy value
What is operational technology and how does cloud come in to help here
Operational Technology (OT) refers to the hardware and software systems that monitor and control physical devices and processes within industrial environments. OT is responsible for the direct monitoring and/or control of physical equipment, assets, processes, and events within the company. Some examples include:
Automated process controllers that manage operations in real-time.
Autonomous equipment for carrying out tasks without human intervention.
Site information systems that manage data generated from industrial operations.
OT is distinct from traditional Information Technology (IT) in that it deals with the direct control and execution of physical operations. Industrial companies are exploring ways to leverage cloud technology for OT to overcome challenges such as the distinct architecture of each site, the need for reliable operation in sometimes hazardous environments, and the difficulty of transferring and using operational data efficiently across distributed sites.
By integrating OT with cloud technology, companies can manage data better, automate routine tasks, provide self-service tools, and ultimately free up resources to focus on other important tasks. This integration is seen as a crucial step in digital transformation, enabling industrial sites to increase efficiency, reliability, and innovation.
What is some of the hardware and software examples of operational tech
Programmable Logic Controllers (PLCs): These are industrial digital computers adapted for the control of manufacturing processes, such as assembly lines, robotic devices, or any activity that requires high reliability, ease of programming, and process fault diagnosis.
Supervisory Control and Data Acquisition (SCADA) Systems: These systems are used to control industrial processes locally or at remote locations. SCADA monitors, gathers, and processes real-time data, directly interacting with devices such as sensors, valves, pumps, motors, and more through human-machine interface (HMI) software.
Distributed Control Systems (DCS): These are used for complex, large-scale industrial processes, often continuous or batch-oriented, such as oil refining, power generation, chemical manufacturing, and pharmaceutical production.
Human Machine Interface (HMI): Interface software that presents process data to a human operator, and through this, the human operator monitors and controls the process.
Industrial Control Systems (ICS): This term encompasses different types of control systems, including SCADA and DCS, used in industrial sectors and critical infrastructures.
Industrial Robots: Robots designed for manufacturing applications that can be programmed to perform various tasks such as welding, painting, assembly, pick and place for printed circuit boards, packaging and labeling, palletizing, product inspection, and testing.
Smart Sensors and Actuators: Devices that collect data from the environment and convert it into usable information, or take information and act upon it to control a physical process.
Manufacturing Execution Systems (MES): These systems manage, monitor, and synchronize the execution of real-time, physical processes involved in transforming raw materials into intermediate and/or finished goods.
Industrial Network Infrastructure: This includes the various communication systems used in industrial environments such as Industrial Ethernet, Fieldbus protocols, and other networking technologies designed for real-time control and data distribution.
What are the challenges for industrial sites in adopting cloud
Unique sites. Industrial sites are heavily customized for the products they produce and how they produce them. Sensors, data-management methods, and controls vary greatly. Even the same finished goods can be produced at different sites in completely different ways, using completely different technology.
Systems for physical safety. Many industrial sites rely on on-premises technology, such as maintenance systems, personnel location trackers, and proximity detectors, to help keep workers safe. These systems are integral to the physical safety of industrial sites and typically need to function in real-time, without delays, to prevent accidents. The concern is that any failure in these systems, potentially caused by the additional complexity or unreliability of cloud technologies, could put physical safety at risk. Industrial process controllers, which are specialized hardware used to manage industrial processes, are designed with these safety considerations in mind and are often kept on-premises to maintain control and minimize risk
Unreliable connectivity. Many sites are in remote locations that may not be able to reliably use terrestrial networks, so they use satellite links that are not designed to cost-effectively support mass data transfer. For safety and security reasons, some systems are intentionally disconnected from the network, which keeps them safe from cyberattacks but traps useful data.
One benefit of cloud for elevance health
One notable use case is our engagement data platform, which centralizes member-facing data and standardizes interactions across multiple channels using APIs. By leveraging cloud-native approaches, we have achieved agility, scalability, and resiliency in our member-facing applications. This “single-pane-of-glass” approach to standardization, where you, say, improve resiliency in one place and then all your channels are able to immediately benefit, has significantly enhanced member experiences and streamlined processes, providing us with a competitive advantage.
Imagine Elevance Health as a health insurance company with a large number of members (clients). They interact with their members through various channels like phone calls, emails, online portals, and mobile apps. Each of these channels collects and uses member data, such as personal details, health records, insurance claims, and customer service interactions.
After Implementing the Cloud-Based Engagement Data Platform:
All member data is centralized in one cloud-based system.
When a member updates their information on any channel (like the online portal), it’s instantly updated across all channels due to cloud synchronization.
Customer service representatives can see real-time data, regardless of the channel the member uses. This leads to more informed interactions and quicker resolutions.
The use of APIs allows seamless integration of different applications and systems, enhancing the efficiency of data use.
The system can easily handle a growing number of users or an increased load of data processing (scalability).
If there’s a technical issue in one part of the system, the cloud’s resiliency ensures that the overall service remains unaffected.
