Case Studies

Use cases for data science and analytics continue to grow, and more companies than ever are investing big bucks and a lot of energy into developing their quantitative teams.We teamed up with DataScience to find out just how companies make use of this significant investment. You can check out some of their additional thoughts here. As we put it, we wanted to find out whether companies have a “the more the merrier” approach to sharing quantitative analysis, or if most of the company is still not invited to the data party.We sent a quick “flash survey” to our network of analytics and data science professionals asking them:Who are the ultimate recipients of all the models, recommendations, charts, etc. that you create? Who views and/or uses your work?The analysis conducted by DataScience yielded a lot of interesting insights. Here are our top six:

1. Out of the five audiences we included, clients/customers are the most likely to “always” receive analysis from their data teams, while sales teams consume the least amount of analytics results.2. Within quantitative teams, other data science, analytics, or business intelligence professionals are the most likely to always or sometimes use their teammate’s analysis, however only 56% of respondents say they always share their work with the rest of the team.

3. When looking at traditional predictive analytics professionals (who work with structured data) and data scientists (who work with unstructured data), the results were fairly similar. This could be because the two groups often work side by side on quantitative teams and share results similarly, rather than being at odds with each other.

4. Analytics professionals and data scientists working in Tech/Telecom/Gaming are the most likely to always reach the C-Suite.5. The most significant sharing with others on the data team happens in Financial Services.6. Not surprisingly, Marketing/Advertising and Consulting firms share their work with clients/customers most frequently.Overall, the results show a glimpse into how data is being put to use across many facets of the business, but they also show clear room for improvement in the form of more consistent sharing. As these quantitative teams continue to grow and become a mainstay in the business, more companies will be looking hard at the return on their sizable investments. We’re predicting a greater scrutinizing of analytics ROI this year, and one of the ways that companies might evaluate this is to see how widespread their quantitative team’s work is throughout the business.What do you think of the results – did anything surprise you? Based on these data, where do you think the greatest opportunities lie? Let us know in the comments, and if you have any suggestions for future flash surveys feel free to let us know!