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The term is used too often, but that does not alter the fact that companies in every industry are dealing with digital transformation. In other words, the technology that is used to make companies more productive. Internet (accessibility), apps (skills set), cloud (computing power and data) and AI/machine learning (insight) help companies perform better. But what is digital transformation and how does it work?
Although the speed of digital transformation varies by industry and business activities, the steps are characterized by three phases.
Automation of tasks
This phase is about the digitalization of manual work or the alleviation of that work. It is not so much about replacement, but making (recurring) tasks more efficient. To this end, applications are introduced or developed as part of daily activities. A well-known example is the introduction of an IVR (interactive voice response) system that can receive and answer many telephone questions without having to interact with an employee. Individual tasks are therefore automated, but not structurally integrated into the business process.
Digital expansion
When companies take advantage of cloud-native infrastructures and implement automation through in-house software development, they are moving to a new generation of applications to support the scaling and further expansion of the digital model. The driving force behind this phase is often a manager who has become involved in the choice of an application that can create a unique or new customer experience. Examples include healthcare providers who are increasingly integrating patient records and cost accounting with patient admission and discharge systems and schedule creation. Automated reminders replace a lot of manual work. In this phase the focus is on end-to-end improvement of business processes.
Artificial intelligence (ai)-enabled business growth
As companies progress through digital transformation, they increasingly use advanced capabilities of application platforms, business parameters and data analytics and ml/ai technology. Companies are AI-supported. This phase offers levels of productivity that were previously impossible. A retailer discovers that ten to twenty percent of their login failures are legitimate customers having problems with the validation process. Denying access by definition results in loss in this example. Behavioral analysis can be used to distinguish legitimate users from bots trying to gain access. Technology and analytics have enabled AI-enabled identification to give those users access, increasing revenue and customer loyalty.
Digital scaling
The growing use of applications, business telemetry and data analytics enables companies to scale digitally. Adopting an agile development methodology to quickly implement modifications has significantly shortened the life cycle from 'code to user'. In digital environments, this 'code' determines the speed of action of a company, and the speed change from code to user represents the agility of the company. In this new era of digital economy, applications have become the lifeblood of the global economy. Every company is becoming an application company, and every industry is becoming an application-driven industry.
As IT infrastructure automation and application-driven DevOps processes are embraced by the industry, we expect the emergence of a layer of distributed application services that unites infrastructure, telemetry and analytics. The scale, agility and complexity of digital businesses require applications to have a degree of self-awareness and therefore the ability to automatically adapt to changing conditions. This creates a new generation of application services to collect and analyze all data and then respond. This offers new business opportunities. These distributed application services help application managers improve performance, security, control and customization without necessarily requiring a lot of development.
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Source: Computable
