By Ashish Mehta, Associate Vice President, Data & Analytics, Infosys
A few years ago, The Economist declared that the world’s most valuable resource is no longer oil, it is data. Digital technology can assist the way businesses to make decisions by converting data into actionable insights. Gartner believes “Organizations will move away from merely using data as resource and analytics as reporting and decision-making support tools. Data and analytics will become the centerpiece of enterprise strategy, focus, and investment.” Data is the new connector in an enterprise powering agility and digital fluidity and a pivot for digital transformation.
Modern enterprises are collecting and analysing vast volumes of data. To derive value from analytics at a scale they are modernizing their data estate which also creates new opportunities to be more efficient and solve many business challenges. As part of data modernization, organizations need to make progressive changes to the way they collect, store, and manage data.
Powered by technology-led disruptions, including ubiquitous network coverage, cheap IoT devices, and the advent of 5G, the data economy will drive the growth of digital natives and create new revenue streams. It will facilitate hyper-personalization, enable products to servitization, build process intelligence and intelligence at the edge, and help with compliance and risk management. In other words, it will transform societies and economies at large. Business leaders are eager to transform their organizations into data-driven agile, sentient, and autonomous enterprises. They are acknowledging that establishing a modern data estate is a foundational step for embarking on digital innovation. For most this will be a massive uplift and transformation of their data landscape.
Data estate modernization can yield great benefits once the hurdles are crossed
As enterprises embark on a digital transformation journey, the cost of managing its data estate can increase exponentially if left unchecked. Enterprise data estate comprises of a complex ecosystem of People, Processes, and Technology that forms the foundation for driving business insights and decision-making while posing significant challenges to govern, manage and transform. Hybrid landscapes, constantly changing technology trends, diverse tools and services, and evolving business demands add to the complexity. With shrinking technology investments, enterprises also struggle to balance the spending between keeping the lights on legacy landscapes and modernization initiatives.
Yet, we’ve seen in the pandemic, data-powered businesses have been more resilient and adapted better to the new normal. Through data estate modernization, organizations can build and deliver a data ecosystem that is leaner, agile, cost-effective, and adaptive. A modern data estate can reduce future CAPEX by investing upfront in innovative ideas; it can reduce OPEX through continuous improvement, innovation, and modernization. By building scalable data platforms, businesses can reduce latency and enable faster data-driven decision-making across the board. Investing in a new proof of concepts or experimentation, it can mitigate the risks of adopting new technologies and accelerate digital adoption and time to value.
To leverage these benefits without getting embroiled by the challenges, enterprises can engage data estate management offerings for the adoption of modern cloud platforms and data architecture. Such offerings reduce the technology debt and enable new capabilities. Many organizations who use managed services might not feel the need for data estate modernization. However, the two differ in many ways.
Understanding data estate modernisation against managed services
Data estate management offerings differ from typical managed services since they offer
accountability in costs with holistic cost management and bundled technology modernization as well as continuous data cloud modernization. The offerings come with a set of core services with the option of extended services.
The transformation of service delivery by the adoption of Agile DevOps and consolidation of services across operations and engineering drives down costs and improves the quality of service. Adopting SRE frameworks and navigating from extreme automation to autonomous operations too helps increase the efficiency of data and AI operations.
Data estate modernization is a definitive move to build business agility and faster time-to-market. Leveraging proven frameworks and solution assets accelerates modernization. The adoption of AI/ML in all stages of data and analytics lifecycle drives automation and operational efficiency. An accelerated data-to-insights lifecycle through the adoption of DataOps/DevOps/MLOps frameworks helps in faster decision-making and reduces cycle time for experimentation. Data modernization and extreme automation enables the enterprise to scale without being constrained by manpower availability. Continuous diagnostics can identify optimization and rationalization opportunities.
Finally, one must focus on business change management to enable enterprises to embrace the new digital ways of working to reap the benefits of modernization. Agile ways of working, machine-assisted decision, and self-service require a step change in the way people within the enterprise engage with each other and with the system. A micro change management approach enables smoother adoption of this change and accelerates value realization.
Essentially, the data estate management offerings help enterprises reduce operational costs while enabling data estate consolidation and their continuous modernization journey.
Harvard Business Review has wondered if a new world order will emerge with a “GDP” — gross data product —that captures an emerging measure of wealth and power of nations.
Data has shaped itself into a major economic force and is playing a transformational role in the enterprises & pursuit of being data-driven agile, sentient, and autonomous enterprises.
Data estate modernization allows data-driven organizations to reimagine their business models and discover new revenue and growth opportunities.