Organizations all over the world are undergoing unprecedented change. By sculpting out niche prospects and driving the development vision, global capability centers (GCCs) are essential in assisting them in navigating such changes. Due to their framework, functionality, and economic viability, Global Capability Centers (GCCs) are uniquely placed to play a further important role than before. It is an inevitable conclusion that data used in the proper context at the right time is the critical factor to the success of any large organization. In the present scenario, every large organization makes vital decisions regarding its future based on data available in artificial intelligence and machine learning forms. Today some of the most sought-after competencies and every GCC is building a Center of expertise around data. During the COVID-19 pandemic, the lockdowns and work-from-home mandates provided digitization a turbo boost. Progressively customers now prefer to engage with organizations in a digital model only. Data science, artificial intelligence, automation, and machine learning have become commonplace. In such a digital-first world, enterprises carry no option but to advance their tech adoption. But they experience multiple roadblocks, including disruption of existing models and the need for speed in an increasingly fluid business environment. This has resulted in the scenario that today, data engineering and data scientists are some of the most sought-after competencies, and every GCC is building a Center of expertise around the database. Global Capability Centers (GCC) have become a key enabler for overcoming these challenges and accelerating tech adoption in enterprises. According to a survey, 76% of the respondents mentioned data as one of their critical areas for growth.
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How Global Capability Centers Are Playing With Data In the current scenario, we are witnessing GCC’s investment significantly across the areas of intelligent data, machine learning, video and image analytics, and the utilization of chatbased robots that use textual Data as a source of conversation. There are numerous instances of how data, when used intelligently, can help reduce or eliminate manual intervention with increased accuracy and efficiency. Have a look at these instances. 1. A retail GCC utilizes its product data (image, description, quantity, brand, category, etc.) to correctly group products. Once grouped aptly, it helps the pricing teams correctly price items that come under the same grouping. This info is then visualized on a portal for the teams to make accurate and real-time decisions. In the past, such a process was error-prone, manual, and cumbersome. 2. Another GCC uses financial data with proprietary algorithms to provide higher visibility on cash flow. The platform is utilized today to monitor cash-flow parameters such as delayed payments, account receivables, credit risk, and bad debt and assists in making timely predictions on cash and bad debt variations. 3. Yet another GCC uses data solutions to speed up factory manufacturing processes. They have curated search engines to search for associated solutions and historical problem statements. This assists employees on the production floor get rapid assistance when issues occur rather than waiting and losing precious minutes on a high-throughput manufacturing line. 4. Data is only valid when it is clean, and another GCC is helping do that in an automated way. They have built data cleansing algorithms and templates that offer options to clean data as per the rules that can be highly customized in over 20 languages. Furthermore, it is extended through machine learning to train the model to do this by itself with minimal monitoring. 5. Another GCC uses data to generate a twelve-month rolling forecast of palm fruit yield. This assists estate managers at plantations plan operations accurately and identifying yieldtaking gaps. Numerous other instances exist today where GCCs are at the forefront of using data to solve critical issues such as health and safety compliance, improve production machine maintenance, reduce production line defects, and improve logistics through accurate prediction modeling and speedier dispute resolution.
Conclusion With the push to go digital, continuous worker shortages, and a volatile supply chain, every single organization is increasing its investment in the intelligent use of data and automation. This, coupled with the challenges of data strategy, architecture, scalability, and quality management, need Global Capability Centers to look for innovative options from their vendor partner ecosystem.
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