Mumbai: Data-driven Digital Transformations (DDDT) are fast becoming a mainstay owing to their exceptional capability to drive operational efficiency and functional effectiveness across product categories and service domains.
With new-age technologies becoming the talk of the town, the relevance of data-driven digital transformation (DDDT) has assumed strategic importance. Organizations are increasingly realizing the transformative potential of data-driven insights, and to that end, many exciting developments are emerging in the technology domain. Notably, the role of DDDT is multifaceted and stands in sharp contrast to the monolithic orientation of the conventional data approach. Instead of just collecting the data, DDDT takes an encompassing view and develops long-lasting solutions for optimizing productivity, elevating efficiency, and boosting profitability, among others. Here are a few critical approaches that can be used in DDDT to elevate its transformational potential across industrial sectors further:
a) Facilitating hype-personalization: Taking the trend of personalization one step forward is AI capabilities which enable firms to sense the latent needs of consumers and offer groundbreaking solutions to meet them. This proactive anticipation, termed hype-personalization, is emerging as an important strategic tool and besides helping firms to remain profitable, it also enables the industry to adopt innovations and stay ahead of the innovation curve. Hyper-personalisation also helps make businesses more customer-centric with stakeholders firmly following the principles of creating, communicating, and delivering superior value for target markets. Leading firms across product categories and service domains, including the likes of Walmart, Google, and Amazon, are using hyper-personalization and setting an example for other businesses to follow for achieving higher levels of customer satisfaction and profitability.
b) Enabling Hyper-Automation: AI-based algorithms have become so advanced today that the entire automation process can be completed without external support. Smart algorithms today come with holistic capabilities that not only equip them with completing the automation process on their own but also modify/alter outputs on a real-time basis. Take, for instance, the leading industrial engineering organization Siemens, which uses AI-powered bots to automate operations, diagnose discrepancies, and run preventive maintenance to keep potential issues at bay. By fully utilizing these end-to-end integration capabilities, firms can easily achieve significant cost savings and reduce downtime while delivering better growth prospects throughout value chains.
c) Data science democratization: Unlike the past scenarios where a few resource-rich organizations monopolized data science, today's situation has changed drastically thanks to the advent of low-code/no-code tools. The new-age development philosophy allows organizations from across the board to derive profound business insights from their data. Regardless of technical competence, anyone in the organization can use these tools to analyze data and offer personalized experiences to the target market. These development packages come with simplified visual interfaces that allow the use of drag-drop menus to make full use of the data science and use its tools and technologies for generating crucial insights on parameters of the organization's strategic and tactical interests.
d) Smarter Edge: Edge technology is making a tectonic shift by emerging from the shadows of just being the faster processing system to offering complete end-to-end process automation. Self-driving cars are a perfect example of how edge technology makes independent decisions using the data at the edge transmitted with the help of new-age sensors. The rising integration of AI and ML in edge computing is paving the way for smart cities, industry 4.0, and the development of efficient infrastructure, among others. Further, the evolution in edge computing is likely to offer multifaceted benefits for many other industries. It is likely to contribute to attaining Sustainable Development Goals (SDGs) as well.
e) Explainable AI: To address the transparency concerns related to the use of AI, the rise of explainable AI has caught the attention of stakeholders across the globe. Explainable AI offers information on the decision-making process by detailing the underlying variables and dimensions used by AI to reach specific conclusions. This transparency is not only helpful for the internal stakeholders of organizations but also brings synergy by bringing external stakeholders on the same platform. This exchange of information also proves instrumental in developing a sense of trust and ownership among stakeholders which, in turn, is essential for ensuring long-term growth and probability of business ecosystems.
2024 will be a transformative year for the adoption of DDDT in businesses across industrial sectors. Organizations are embracing digital transformations with open arms, and by leveraging digital technologies to derive real-time customer insights, implement workflow automation, and deliver personalized experiences, these firms can remain competitive in the fast-changing and evolving business landscape. In sum, DDDT is likely to keep the growth engines of global economies humming while generating new avenues of growth, profitability, and employment worldwide .
The author of this article is MSys Technologies SVP- Digital Solutions Dhwanit Shah
