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Virtual
From RandD to ROI: Adding Real Financial Value to Businesses Using Data Science (305263)
*Delali Agbenyegah, Carter's
Keywords: R&D, ROI, Data Science, Predictive Analytics, Prescriptive Analysis
In the past 5 years, Data Science has consistently ranked one of the top 3 jobs in the United States by Glassdoor. This is due to the increased digitalization and data capture across all industries as well as the promise that these data hold to increase business profits through predictive and prescriptive analytics. Even in 2020 where most industries experienced a tumultuous situation, a report by Dice indicated a 50% average increase in the demand for Data Scientists in most industries. On the other hand, Gartner analysts reported that over 85% of big data projects fail. A recent Harvard Business Review publication in February 2021 indicated that 62% of fortune 1000 companies invested $50M or more in big data and AI initiatives in the past 3 years but are still struggling to realize any financial outcome. So why are most companies not seeing the business impact that is promised by Big Data and AI initiatives? In this talk, I will highlight some of the reasons why data science projects fail and introduce my 10-step framework that will empower data science teams to navigate complex business environments and move data science projects from R&D to adding real financial value (ROI).