3 ways big pharma uses big data

How a giant company was overwhelmed by giant amounts of data -- and won
By Benjamin Harris
01:22 PM

In the world of Big Pharma, big data is a looming giant that can be a tough beast to tackle, but it can be a rewarding one too. With a vast amount of data in myriad formats, the Ecuadorian arm of Pfizer knew that using Excel spreadsheets to record and analyze marketing, sales, and distribution data was a Stone Age solution for their Space Age needs. They turned to Noux, an Ecuador-based company that works with SAP to implement a more nimble data-driven system to help with their business intelligence.

Esteban Burbano de Lara, commercial manager from Noux, and Eduardo Saenz, business technology director, Bolivia Ecuador and Perú from Pfizer speak about some of the ways transitioning to embrace Big Data has helped Pfizer and can help other organizations conduct powerful business intelligence and analytics of their markets. 

Deal with data overload

Pfizer collects massive amounts of data on everything from how much of its product is sold at any particular pharmacy to whether a doctor prescribes its medication versus a competing one. Burbano de Lara's team helped Pfizer implement a system that could analyze data as it was coming in. He outlined the complexities of the task, saying "you'll get data from 50 distributors, from five to six marketing forms, data from your in-house teams." Eduardo Saenz worried about the data's density being a factor to overcome, saying that "big data sometimes overwhelms people because it's too big... there is too much data to analyze." He says the system they put in place allows individual users to scale down and segregate the appropriate data for their research. A system that is able to retrieve the appropriate data and ignore the rest is a crucial tool in harnessing big data, Saenz says.

Wrangle multiple streams of information

Most people picture big data as a series of cleanly organized files full of numbers and easily-digestible information. If only, laments Burbano de Lara. "These data sources are very heterogeneous, very dispersed," he says. "Sometimes it's a file, sometimes it's a database, sometimes it's encrypted." Pfizer needed a streamlined way to stay on top of this wide amount of information and make informed decisions on where to head next. 

Keeping all of that information straight can be a challenge. Does a doctor prescribe the competing pharmaceutical more? Should more of an effort be made to reach that doctor, or should resources be focused elsewhere? Saenz says that it was "a big challenge to design a process on how to present all of the information in a friendly manner, using one interface to display all of this information." With the data warehousing solution, he says, "we can analyze each information source individually, but at the same time we can mix all of the information sources. That allows us to see things that other companies cannot see."