Digital transformation refers to the process and strategy of using digital technology to drastically change how businesses operate and serve customers. The phrase has become ubiquitous in the age of digitization. That’s because every organization – regardless of its size or industry – increasingly relies on data and technology to operate more efficiently and deliver value to customers.
History of Digital Transformation
Although computer technology has been around for decades, the concept of digital transformation is relatively new. It arrived in the 1990s with the introduction of mainstream internet. Since then, the ability to convert traditional forms of media (like documents and photos) into ones and zeroes has paled in importance to what digital technology has brought society. Today, digitization touches every part of our lives, affecting how we work, shop, travel, educate, govern and live.
Digital transformation practices are commonly used in the context of business. The introduction of digital technologies has sparked the creation of new business models and revenue streams. Emerging technologies such as artificial intelligence (AI), cloud computing and the Internet of Things (IoT) accelerate transformation, while foundational technologies like data management and analytics are needed to analyze the massive amounts of data resulting from digital transformation.
Digital transformation is not about technology alone. It occurs at the intersection of people, business and technology – and is guided by a broader business strategy. Success comes when organizations can effectively use data created by or through technology in a way that enables business change to occur dynamically.
Digital transformation is made possible by the union of:
The convergence gives life to a digital business, allowing organizations to deliver digital experiences, digital operations and digital innovation. A digital business can innovate quickly and scale up innovations to deliver the digital products and services that customers value.
Fighting Childhood Cancer With Cloud Analytics
Childhood cancer is a devastating fact of life. But one nonprofit is making a difference using cloud-based analytics to fuel childhood cancer research. By optimizing each donor's journey, The Kids' Cancer Project has accelerated its fundraising efforts – channeling more than $50 million into fighting childhood cancers, developing less-intensive treatments and finding a cure.
Digital Transformation in Today's World
Your journey to digital transformation begins with research. Here are three insight-rich assets to demystify the topic and put you on a path to success.
The CIO Perspective
Meet CIOs and technology innovators from around the globe to see their approach to digital transformation. Through their stories, you'll discover how all types and sizes of organizations encounter many of the same challenges. And learn how successful CIOs have innovated to achieve success.
Evolving Your Analytics Platform
Wondering how to succeed in the cloud? Learn why organizations are moving to the cloud, where they are with their cloud-based digital transformation efforts, and the struggles they face in shifting analytics to stay in sync with the digital economy.
Four Tips for Successful Digital Transformation
Start your journey toward digital transformation. Learn what it means to evolve for the cloud, embed analytics into operations, and ultimately create value from data using AI in your organization.
Digital transformation is all about unlocking value in your business processes and releasing it back to customers – as well as being agile enough to use data and analytics to create new, innovative experiences. The journey of digital transformation will lead organizations to be analytics-driven, and the application of embedded AI technologies will become second nature.
How Digital Transformation Works
A business cannot fully realize the benefits of digitization unless all three components of digital transformation – people, business and technology – work in concert. Embedding these components into an organization’s culture demands strong leadership from people like the chief data and analytics officer (CDAO), chief information officer (CIO) or even the CEO. The result of such orchestration can be a customer-centric business that’s focused on ensuring every action taken is done so with customer experience in mind.
Organizations that succeed with digital transformation efforts by shifting their mindsets, strategies and culture to keep pace with changing needs can achieve outcomes such as:
An Engaging Digital Experience
Success is creating a digital experience that feels relevant, effective and emotionally enticing for customers. Digitally transformed businesses know how to deliver experiences customers truly desire rather than simply relying on traditional products or services.
Businesses must be responsive and agile enough to deliver on the precise experiences and services customers value. Accomplishing this requires having the right technologies and processes in place; having the right people and skills; and having an organization that supports collaboration, experimentation and innovation.
This often starts with experimentation in innovation labs and test-and-learn mindsets. However, organizations must equally focus on building a scalable innovation approach, which requires appropriate investments in scaling and putting value-added proofs of concept into production.
Digital transformation affects each organization differently. But every successful transformation includes the same core components.
People: The Human Side of Digital Transformation
Attracting and retaining digital talent is of paramount importance. But it’s just as important to nurture the right type of organizational structure and culture to support collaboration, flexibility and speed.
Digital-first companies hire the best employees they can afford and integrate them into multiple areas so the results from one area can be shared with others. Digital productivity and collaboration tools help employees bring digital products to market with greater speed and agility.
Once companies collect a few wins with digital transformation practices, they often reorganize to break down departmental silos and form cross-functional teams dedicated to serving the customer. The next step is intentionally creating an organizational structure that fosters purpose, autonomy and mastery.
Fostering a culture of innovation and continued refinement through insight-driven decision making from top to bottom is essential. Data and technology will only take a company so far. Culture and leadership must be the heart of change. With the right organizational culture, almost anything can be achieved.
Business: Organizing for Success
Strong leaders who put digital and customer experience at the core of the business model drive successful transformation efforts. These leaders must ensure their digital transformation strategies address cultural gaps – and that everyone understands where the organization is going, and why.
Strategy and customer experience
Customers are at the center of many digital transformation projects. Makes sense, right? Because improving the customer experience is a top priority at most organizations. Digital transformation efforts rely on digital technology to convert customer insight into customer-centric products and services. This helps organizations to better engage customers – and gain even more value for the business.
Digital transformation is often used to boost agility and operational efficiency. When technologies like AI and advanced analytics are used to improve internal business processes, transformation becomes possible. Automation speeds processes while freeing workers to focus on more strategic tasks. And self-service dashboards give employees better access to insights, speeding and improving decision making across the organization.
Companies that fail to evolve risk extinction. Conversely, those aligning the components of digital transformation to adjust their business models can create new digital offerings and revenue streams to evolve with the market. Remember how Netflix used to mail DVDs? By digitizing its business model, Netflix has grown into one of the biggest entertainment companies in the world.
Technology: Foundational & Emerging
Digitally enlightened companies layer technology to delight customers and meet business needs. Having a flexible, cloud-enabled platform that includes foundational technologies like data management and analytics allows businesses to scale and grow. Adopting emerging technologies allows them to differentiate and disrupt with new products and services.
- Cloud computing. Cloud computing gives organizations quicker access to data, software and capabilities. This, in turn, makes them agile enough to transform. Cloud offers a fundamental change in service delivery and consumption, a disruptive technology enjoyed by anybody who uses virtual assistants like Alexa or a business that communicates on Slack.
- Artificial intelligence. AI is used to automate processes, especially low-level processes done consistently at high speeds – such as examining microchips for defects. It also enables personalization at scale. In turn, marketers can offer smart services like chatbots, which use natural language processing to understand context and perform humanlike functions.
- Advanced analytics. Analytics turns data into insight. And insight is what organizations use to innovate in a digital world. With advanced analytics, sophisticated algorithms can be woven seamlessly into daily operations, increasing the speed and accuracy of virtually any process. An analytics platform brings together all analytics efforts, from data to discovery to deployment.
- Data management. Doing business in a digital world means coping with the torrent of structured and unstructured data pouring in from seemingly infinite sources. Data fuels the technologies that enable digital transformation. To succeed, organizations must be adept at accessing, preparing, cleaning, managing and governing data.
- Marketing analytics. Customer-centricity is practically synonymous with digital transformation. As organizations scramble to meet the evolving needs of consumers, they increasingly depend on customer intelligence software and tools to understand and segment customers – key steps in providing a great customer experience.
- IoT. Being able to analyze diverse data in real time, as events happen, gives IoT a place in many transformation projects. This is because gathering data from sensors and connected devices is only half the picture. The real value of IoT comes from being able to analyze the streaming data and take action on it quickly – filtering relevant data from noise. Manufacturers have been successful at using IoT technologies to optimize the supply chain.
- Big data analytics. Big data accelerates the need for transformation – and the big data resulting from digitization requires big data analytics to unlock its value. By applying advanced analytics and AI to big data, organizations can make faster-paced, forward-thinking decisions. This, in turn, allows businesses to evolve as new, data-driven businesses arise.
To get the best results possible from digital transformation efforts, it’s important to have a trusted and flexible analytics platform that yields high returns on your data, talent and analytics investments. Find out how SAS Viya delivers the perfect balance of choice and control across the full analytics life cycle – from data to discovery to deployment.
- Article AI optimises campaign performance at WWF and drives ROIIn its mission to advocate for endangered species and for the environment, the World Wide Fund faces challenges familiar to all brands. By optimising its marketing through the smart use of machine learning and AI the WWF was able to address the issues of cost and purpose successfully.
- Article Shut the front door on insurance application fraud!Fraudsters love the ease of plying their trade over digital channels. Smart insurance companies are using data from those channels (device fingerprint, IP address, geolocation, etc.) coupled with analytics and machine learning to detect insurance application fraud perpetrated by agents, customers and fraud rings.
- Article A guide to machine learning algorithms and their applicationsDo you know the difference between supervised and unsupervised learning? How about the difference between decision trees and forests? Or when to use a support vector algorithm? Get all the answers here.