By Cao Hong, Associate Director and Head of Data Science, Ernst & Young Advisory and Manik Bhandari, Partner & EY Asean Analytics Leader, Ernst & Young Advisory
Addressing this, organizations need to work on the technology and process management in data acquisition. For example, organizations can consider appointing data stewards in the organization who are incentivized to be accountable for maintaining quality of data sources. Also, the growing complexity of artificial intelligence has resulted in a lack of understanding and trust in the system. To this end, transparency and user experience and subsequent education should be factored into design of a data system. In addition, amid data fraud concerns, there should be security technologies to detect and alert fraudulent data manipulations.Deliver value According to Data & Advanced Analytics: High Stakes, High Rewards, a study by EY and Forbes Insight, only seven percent of global respondents have a well-established enterprise-wide analytics strategy that is central to their business. Out of these, 66 percent achieved revenue growth of 15 percent or more, while 63 percent reported that operating margins had increased 15 percent or more in 2016. In addition, 60 percent of them said they improved their risk profiles.
Data-driven innovation is no doubt the technological driver for digital transformation