AWS Cloud Enterprise Strategy Blog

Digital Transformation: the Why, Who, How, and What – Part 4, “The What”

Enabling Technology

In part three, ‘The How’ blog post, we covered best practices for transformational processes, and how you can use the digital-transformation process framework to deliver an effective transformation. In this blog post, we dive deeper into the technologies that enable digital transformation.

Contemporary Technology Requirements

The rising expectations of customers and employees, due to the consumerization and ubiquity of IT, are driving business transformation. They expect the same seamless functionality found in apps from Uber, Grubhub, Pinterest, Amazon, and many others. Businesses must become more flexible, data-driven, mobile, social, and automated. These changes require companies to re-evaluate their tools, technologies, and processes to reimagine existing processes, products, and solutions to remain competitive.

New and  advanced technologies bolster this modern, digitally-transformed business environment. Cloud, artificial intelligence and machine learning (AI/ML), Internet of Things (IoT), predictive analytics, data lakes, augmented reality, virtual reality, and mixed reality (AR/VR/MR) work together to support new business outcomes.

We would like to emphasize that digital transformation is a paradigm shift in the organization’s culture and mindset, not just in technology. The technology is important, but it is only a tool to achieve new objectives, not the objective itself.

Why is Digital Transformation Possible Now?

Many people are wondering why digital transformation has become so compelling now. It is true that many of the technologies we are using now were invented and introduced years ago—some even twenty to thirty years ago. We are seeing three factors come together at the same time to make this possible:

  • The continued growth in computing power
  • The corresponding growth and ubiquity of connectivity
  • The abundance of data from multiple sources.

According to Moore’s law, introduced in 1975, computing power doubles every two years, and the cost of computing power is cut in half every two years. Because of this exponential growth, by 2015, computer power had increased 106 times since 1975. This growth allowed digital-transformation technologies that required enormous power to process massive data volumes, such as analytics and AI/ML.

Similar to Moore’s law, Nielsen’s law of internet bandwidth—introduced in 1998—showed massive growth in the bandwidth and ubiquity of connectivity. From 1983 to 2015, bandwidth increased 106 times, enabling the smallest devices embedded in industrial machinery or personal fitness devices to communicate in near-real time. This increase allowed sharing of data at scale.

The ubiquitous connectivity and growth of the internet spawned massive amounts of data when, at the same time, mathematical advances identified patterns in complex data. Businesses now have access to behavioral data, internal systems data, data from sensors, the so-called “digital exhaust data” from users of your applications, location data, and social media data. This data—flooding in from thousands of sources—is  increasing in velocity, volume, and variety of data. Creation and consumption of data went up by 5000% between 2010 and 2020 and is expected to more than double again to 180 zettabytes by 2025. The cloud has been an accelerator, providing vast amounts of storage at continually lower costs, and the underlying infrastructure to collect, move, and process data quickly.

Cloud Powers Digital Transformation

Cloud computing has not just driven the growth and availability of computer and data storage but has enabled new and important capabilities that foster innovation, speed, and agility. Previously, many initiatives stalled, and large, multi-million-dollar programs were reevaluated and labeled as too risky or too expensive to undertake. Likewise, new ideas died on the vine while months passed, waiting for hardware to be designed, procured, set up, and tested.

The cloud has changed this model in three important ways:

Rapid Experimentation

You only pay when you consume computing resources and pay only for how much you consume. This pay-as-you-go model allows you to experiment without flawed estimates or justifications for large complex projects. This staging of investments allows for trying more ideas at little cost, and they are easily eliminated if unsuccessful or can scale up rapidly if they work. With this model, experimentation on the cloud is “forgiving” because the time and cost to build the experimentation environment are low, and it is easy to disassemble the environment in the case of failure and start new experimentation. Thomas Edison once said, “Negative results are just what I want. They are just as valuable to me as positive results. I can never find the thing that does the job best until I find the ones that do not.”

Cloud Computing Has Transformed the Way Software is Built

What used to require specialized teams working in close cooperation with one another, long waiting times for infrastructure purchase and installation, and a good deal of money and risk, is now available to companies of any size and budget. The cloud provides access to a series of pre-built services, including numerous advanced new capabilities such as AI/ML, IoT, data lakes, analytics, AR/VR/MR, social media tools, and high-performance computing. These new, on-demand resources shorten your development cycle and dramatically increase your agility since the cost and time it takes to experiment and develop are significantly lower.

Once you have built new business capabilities to enable your digital transformation, you can easily scale up or down based on the needs of the business using the elasticity of the cloud. This just isn’t possible with any on-premise environment.

Focus on Customers Not Data Centers

Cloud computing lets you focus on projects that differentiate your business for your customers, rather than investing time and money on the heavy lifting of racking, stacking, and powering servers.

From Strategy to Execution

Where and how do you begin your digital transformation? Here are a few practical pieces of advice as you start your journey:

  1. As we said in blog one, start with the “why.” Make sure you have a clear understanding of the business need you are addressing. We advise customers to keep drilling down until they have defined the business need in a single sentence. If it takes more than one sentence to describe, it is probably too complicated or too large of a place to start.
  2. Once you have your “why,” turn it into something measurable. Determining how solving this problem will be measured in a meaningful way to the business is essential. Not just because it is how you will demonstrate success but because it helps the team working on the problem prioritize and guide their work in order and determine if they are on track for success. Instead of saying, “Our goal is to reduce manufacturing errors,” change it to “Our goal is to reduce manufacturing errors by 5%.” Make your goal clear, deliberate, and quantifiable.
  3. Transformation is not all or nothing. You don’t have to transform your whole organization from the start. You can pick important areas, implement solutions for them, and scale your learnings to new places within your organization.
  4. As we covered in blog two, determine how you want to organize your teams to address the why. Again, we suggest using Two-Pizza teams, but you must find what works best for your organization. When picking a team to focus your efforts on, try to look for those most open to the idea.
  5. There is a lot to learn about the cloud and digital transformation. Often we find organizations needing help to determine the right services, tools, and approaches that can help address their problem. Don’t go at it alone. While you should be careful not to outsource what differentiates you, it is still advisable to bring in a partner with experience in the area you are working to help get you started. In addition to AWS Professional Services, AWS has an extensive Partnership network to help get you started. Use them.
  6. From here, simply get started. Implement something, observe and measure whether it is delivering value or resolving the problem you identified, and then iterate with improvements to drive more value. If it works, expand/augment and scale its usage up; if it does not work, embrace the benefits of the cloud, and scale the solution down.

This series of four blog posts reviewed digital transformation from organizational, process, and technology perspectives. We have recommended tried-and-tested steps—in the form of high-level frameworks and practical advice—that you can use to move forward. This advice is a good starting point for your organization, but it is just that—a starting point. Follow the concepts from the suggested frameworks but tailor them to your organization’s needs. Finally, use the power of the cloud and the new paradigms it creates as an enabler to your digital transformation and a means to utilize advanced technologies

Make sure this meets your intent. If not, it is unclear what businesses are being driven to do.

Tom Godden

Tom Godden

Tom Godden is an Enterprise Strategist and Evangelist at Amazon Web Services (AWS). Prior to AWS, Tom was the Chief Information Officer for Foundation Medicine where he helped build the world's leading, FDA regulated, cancer genomics diagnostic, research, and patient outcomes platform to improve outcomes and inform next-generation precision medicine. Previously, Tom held multiple senior technology leadership roles at Wolters Kluwer in Alphen aan den Rijn Netherlands and has over 17 years in the healthcare and life sciences industry. Tom has a Bachelor’s degree from Arizona State University.

Gene Shadrin

Gene Shadrin

Gene Shadrin is a Sr. Manager Solutions Architecture at Amazon Web Services (AWS). Prior to AWS, Gene was a CTO / Director of Architecture at American Honda where he established technology innovation program at the local/regional/global levels, instituted enterprise architecture practice, and helped enable new digital business opportunities to improve business outcomes and reduce technical debt. Gene has over 20 years of experience in automotive, software, and retail industries.