As digital penetration continues to open up new channels and markets, growth and technology have emerged as the top CEO agenda, according to a study. We are witnessing large-scale business transformation across technology, strategy, process and talent in practically every industry.
At the heart of this transformation is advanced data analytics powered by Artificial Intelligence (AI), Machine Learning (ML) and Natural Language Processing (NLP). The adoption of AI, ML and data science is key to strategic transformations, including improving customer experience and efficiency, or driving innovation. It is not surprising that analytics and Business Intelligence (BI) is being prioritized as a part of cloud-based services and new technologies in 82 percent of the organizations, followed by technologies such as AI, ML and NLP. McKinsey estimates demonstrate the potential impact of analytics and AI in multiple industries across business areas. For example, in travel, the impact is as high as 9.4 percent of the total industry revenue.
Analytics-as-a-Service (AaaS) allows organizations access to cloud-enabled, real-time and actionable BI which allows not just day-to-day decision-making, but transformation at three fundamental levels. Let me elaborate.
Customer (Experience-driven Businesses)
Return-on-Experience (RoX) is fast becoming a key business metric and is increasingly on the C-suite’s radar. More than 85 percent of companies using customer analytics extensively report deriving significant value from it. However, many organizations who have taken a piece-meal and fragmented approach to analytics may not experience the same results, leading to misplaced skepticism. Hence, while investment in customer analytics continues to grow, business leaders are under increasing pressure to demonstrate value. AaaS provides a viable solution to business leaders in the organization-wide adoption of analytics, and solving typical challenges such as data silos and veracity of customer data across channels, resulting in higher RoX.
Employee (De-centralized Decision-making)
While ‘agile’ and ‘flat organizations’ have dominated the corporate lexicon for decades, the ground reality is far from it. According to a Harvard Business Review study, while 75 percent of business leaders believe it is important for employees to have access to actionable intelligence, only 24 percent of the organizations are able to achieve this. Further, less than 1 in 10 organizations have predictive analytics or automated decision-making. Building an agile and flat organization where employees at all levels are empowered with the right data and decision-making capabilities is at the core of business transformation. AaaS makes on-demand insights accessible to the last-mile of the organization.
Environment (Data-driven Strategies)
According to one study, 60 percent of the organizations with an enterprise-wide analytics strategy in place are witnessing a revenue growth of 7 percent or more. In contrast, only 18 percent of laggards in analytics are able to achieve that growth. Creating and implementing strategies that navigate the complexities of the business environment across market dynamics, regulations, competition and changing customer preferences is nearly impossible without data. AaaS helps build the big picture for decision-makers, capturing micro-insights from the ground as well as macro-economic trends.
Estimates suggest that the AaaS market would cross the USD 100+ Billion mark by 2026 at a compound annual growth rate of more than 35 percent. As I had argued in an earlier article, analytics is being mainstreamed within organizations as a key lever of transformation. AaaS makes the necessary tools available to organizations to this purpose, readily, widely and at a lower cost of ownership along with the adoption of AI and ML technologies.
WNS has been recognized as a 'Leader' in NelsonHall's Vendor Evaluation & Assessment Tool (NEAT) for Advanced Analytics Business Process Services (BPS) in the Overall market segment.
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