Businesses are striving to develop digital transformation solutions that increase customer satisfaction, retention, and long-term profitability.
Businesses must move beyond Digital Transformation 1.0 to 2.0 to support rapid business decisions and become situationally aware. What’s the difference? Digital Transformation 2.0 means going beyond simply digitizing back-end systems to developing applications that respond in real-time and run anywhere, anytime, on any interface, and with any method of interaction.
Real-time applications typically work with multiple data inputs, some of it streaming and events-based, and use sophisticated analytics such as artificial intelligence to derive insights and automatically spot changes in time frames short enough to take action as events are happening.
At the heart of many transformations that use real-time applications is the need to become more customer-centric. Businesses are striving to develop digital transformation solutions that increase customer satisfaction, retention, and long-term profitability. Use cases cut across all businesses. An online retailer might seek to offer highly personalized offers dynamically when a customer visits a site. Or, a business might use an automated chatbot to provide enhanced service when a customer calls.
Unfortunately, there are many obstacles on the path to digital transformations and the development of the applications that support them. A recent report by FICO and Arizent identified some common issues and challenges banks face today. Just over one-half (56 percent) of banks surveyed are confident in their ability to anticipate and proactively respond to customers’ needs. A majority (71 percent) voiced doubts around their company’s ability to respond to digital disruption.
While the report focused on banks, many of the same problems are common in most businesses attempting to become more responsive and efficient through digital transformation. For example, the report found that only 5% of companies are successfully using all of the data across their enterprise to make customer-centric decisions. And only 7% are completely confident that their current data and processes empower smarter instantaneous decisions.
Another factor that impedes many digital transformation efforts is the closed nature of most businesses. Digital transformation often requires taking existing services platforms and extending them out via new interfaces. The intent is to make use of services, data, and systems that third parties offer. For example, rather than building its own credit rating application, a Fintech company application would benefit by using a quick call to an established bank’s existing service.
Many businesses are struggling with digital transformation efforts because they face operational challenges. These challenges prevent them from achieving the goals of their transformation. Some of the problems are due to reliance on old and inflexible infrastructure and the reliance on monolithic applications. Other issues are organizational. Frequently, there is a misalignment when it comes to process automation. The business and the technical sides of the house do not talk the same language, do not share information, and are unaware of the objectives and restraints the other side encounters.
Such are the obstacles to transformation. These obstacles must be removed to enable the fast action, and agility businesses require today.
From an infrastructure perspective, businesses are moving to cloud-native architectures to build and deploy real-time applications that will support their transformation efforts. A cloud-native approach gives companies the flexibility to rapidly develop and deploy new applications to meet fast-changing business requirements. Cloud-native architectures are dynamic, with on-demand allocation and release of resources. Such an elastic environment enables rapid scaling to meet the varying demands of real-time applications.
Cloud-native applications are ideal because they can quickly incorporate new features, applications, and data. They are composed of independent microservices-based elements that work together. Such an architecture allows companies to use new or different technology more easily as needed by the business. For example, a company might improve a customer engagement chatbot by using a new cognitive app that delivers better insights into a text stream or improved language processing of a call.
From a development standpoint, the shift is to low-code/no-code methods. Low-code/no-code offers a development environment that uses a graphical user interface to create applications instead of traditional hand-coded programming. The advantages include a significant reduction in the amount of traditional hand-coding, enabling accelerated delivery of business applications. Such capabilities are needed in business today, where speed to market is critical.
With that speed, businesses acquire the agility they require to keep pace with market changes. They can build applications using pre-built modules in the visual environment. Additionally, most low-code/no-code platforms run in the cloud. This automates most of the processes needed to connect to other services and bring the application online. Low-code/no-code methods typically provide cross-platform mobility. With much less effort, developers can build robust applications using third-party APIs and modules from different platforms.
Due to these benefits, the embracement of low-code/no-code is accelerating. The adoption is driven by the escalating demand for business digitization, according to recent market research. The global market size for low-code/no-code platforms is expected to reach $83.5 billion by 2028, with a CAGR of over 36%. Adoption of intelligent communication designs, remarkable growth in data traffic, and advancements in technologies are some of the key reasons responsible for the industry growth.