It is a well-known fact that since the pandemic, with the accelerated digitization of the world, advanced analytics and cloud computing have emerged as one of the most important and crucial technologies to gain competitive advantage. As a result, technology leaders are increasingly scaling their organizations’ data and analytics strategies to stay ahead of the curve using cutting-edge cloud services and tools.
The combined potential of analytics and cloud computing is enormous; It supports business operations and decision-making strategies by providing predictive and prescriptive insights. In fact, the marriage of data analytics and cloud computing is so powerful that it can increase business revenue while reducing the capital expenditures required to achieve desired outcomes.
However, a recent study of data-driven business transformation showed that despite investments of more than a decade, only 8% of companies have fully modernized with the cloud and integrated analytics and AI into processes. Challenges related to securing budgets, maintaining vendor-agnostic cloud architectures, and securing executive support for cloud initiatives prevent many from implementing their ideal data architectures in the cloud. That’s why cultivating a data-driven business culture with an emphasis on data literacy remains a key investment priority for data, analytics and cloud leaders. According to the same study, 88% of technology leaders surveyed said their companies will have invested in cloud-native platforms by the end of 2022.
While business best practices drive the evolution of data analytics, scaling analytics to drive enterprise-wide change involves a cultural component. This component involves moving data and analytics from technology-oriented disciplines to strategic and business-oriented disciplines.
There are three characteristics that differentiate the most data-driven companies from those that have not yet integrated analytics into their day-to-day operations:
- Cross-departmental collaboration: Successful large-scale transformations depend on cross-departmental collaboration between business and technology leaders on analytics and cloud efforts, as well as executive support.
- Technology and Business Strategy Alignment: Data-driven companies have successfully ignited a cultural shift that intrinsically harmonizes business and technology strategy across the organization. Compared to the partial adopters, only a small number of analytics innovators find it extremely difficult to gain leadership support to build a data-driven culture.
- Build data literacy with trusted insights: For a business to be truly data-driven, every employee must have the skills to use data to drive their decisions. As employees need to be able to turn data into insights, data literacy has become an enterprise-wide challenge.
Many of the successful data-driven organizations are moving from centralized data processes and storage to a hub-and-spoke model based on a decentralized data architecture and business data services approach. This approach combines services, technology and business processes. Organizations can build data-driven solutions that align data governance processes with business goals and priorities by creating cross-functional teams focused on solving business problems. A similar shift is happening in cloud computing as well, as CEOs want to focus on creating truly data-driven companies. Thanks to this interaction between people, processes, data and technology, companies will continue to be successful in the future.
Accelerating the cloud journey
When fully embracing cloud-based technology, only cloud-based data and analytics utilizing predictive insights can be realized. Here are three key considerations to plan for a smooth cloud journey.
- Create a cloud-based data and analytics strategy: A smooth cloud journey can only be achieved when you create a cloud-based data and analytics strategy that starts with determining what data you retain, re-host, re-create or want to withdraw cloud; This will serve as the foundation of the cloud strategy. Look for partners who understand the industry and processes and can operate innovation hubs or data labs to test and prove the value of cloud-based analytics.
- Identify opportunities for data and machine learning: Data and analytics leaders can accelerate cloud migration by using pre-trained data, machine learning models, and modular pre-built accelerators. As part of an augmented intelligence strategy, identify ways to leverage these capabilities and uncover meaningful insights. Build a cloud-based data foundation to uncover insights that help employees make better decisions.
- Train and retain top talent: Many data and analytics engineers who have not prioritized the cloud have seen their best and most versatile employees move to other companies. Redesigning cloud applications requires a unique combination of industry, technology, and data skills—a highly sought-after skill.
An initial investment in cloud-based data and analytics is a long-term investment in increased business resilience, as the ability to act on insights has become a differentiator, especially in today’s dynamic world. Cloud computing is not only a smart choice for forward-thinking businesses, it’s needed now more than ever. It is widely recognized that it is an unstoppable trend in the IT industry. I believe cloud computing is the wave of the future. Data-driven decisions powered by the cloud will improve our ability to create best-in-class experiences for our employees, customers, and partners, leading to profitable growth.
The author is Global Analytics Business Leader at Genpact
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