Business-Centric Data Science

By Lillian Pierson

Business is complex. Data science is complex. At times, it’s easy to get so caught up looking at the trees that you forget to look for a way out of the forest. That’s why, in all areas of business, it’s extremely important to stay focused on the end goal. Ultimately, no matter what line of business you’re in, true north is always the same — business profit growth.

Whether you achieve that by creating greater efficiencies or by increasing sales rates and customer loyalty, the end goal is to create a more stable, solid profit-growth rate for your business. The following is a list of some of the ways that you can use business-centric data science and business intelligence to help increase profits:

  • Decrease financial risks. A business-centric data scientist can decrease financial risk in ecommerce business by using time series anomaly detection methods for real-time fraud detection — to decrease Card-Not-Present fraud and to decrease incidence of account takeovers, to take two examples.

  • Increase the efficiencies of systems and processes. This is a business systems optimization function that’s performed by both the business-centric data scientist and the business analyst. Both use analytics to optimize business processes, structures, and systems, but their methods and data sources differ. The end goal here should be to decrease needless resource expenditures and to increase return on investment for justified expenditures.

  • Increase sales rates. To increase sales rates for your offerings, you can employ a business-centric data scientist to help you find the best ways to upsell and cross-sell, increase customer loyalty, increase conversions in each layer of the funnel, and exact-target your advertising and discounts. It’s likely that your business is already employing many of these tactics, but a business-centric data scientist can look at all data related to the business and, from that, derive insights that supercharge these efforts.