17 ANALYTICS & DATA SCIENCE SPEND & TRENDS REPORT
“Prioritization of insight generating work may differ, and finally how the data is processed and interpreted can also be very specific within departments.
these teams are for each other’s success. Early alignment and collective goal setting are key to a symbiotic relationship between these teams. I am not surprised to see high utility (72%) of data science insights by marketing and sales. While insights were a competitive advantage before, it has become more table stakes now to rely on data driven performance and strategic insights to run the business efficiently. Challenges & Opportunities: It is not entirely surprising to see that working across departments is one of the top challenges, even topping hiring/talent management and data quality. Utility and applications of data and insights vary. Prioritization of insight generating work may differ, and finally how the data is processed and interpreted can also be very specific within departments. For instance the understanding of KPIs and insights, the
visual presentation and rigor of analyses are often not at parity. There might also be significant duplication of insights work when multiple analytics teams are embedded into the organization and are trying to answer similar business questions. Now that we have enough or dare I say too much data, better understanding of this asset is a primary opportunity. Global data definitions, strategic prioritization of insights work, self-service tools and cross- functional training can alleviate some of these top challenges. Conclusion: We have come a long way since I started my professional career in data science and analytics. We are moving fast and in a positive direction with better tools, abundant data, cheaper storage and constantly improving ability to process information. Businesses are increasingly reliant on data science and analytics insights to drive decisions.
Anu Sundaram VP, Business Analytics Rue Gilt Groupe
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