A Must to Stay Competitive in the Digital Space Technology has become increasingly important in the way we work and interact. As people rely on technology in their daily lives, they develop higher expectations for functionality, usability, and performance. The life sciences industry is no different—technology is at the heart of research and development,
In our previous article, “Roadmapping for Success, A Product-Based Approach to Life Science Software,” we promised to discuss some of the analysis tools in more detail, and how to pick the right set of tools to optimize your feature portfolio. There are more tools to review than the length of this article allows, so the
Rising demand and ever-changing technology expectations of end users has ushered in an era of cloud-hosted Life Sciences IT platforms. These platforms have ever increasing plug and play applications aimed at delivering maximum business value. Delivering high value information systems requires a deep understanding of the end user and in-depth analysis to identify the optimum
There has been an explosion of “off the shelf” personal mobile health apps and devices in the last two years and the trend shows no sign of slowing down. The market for mobile health apps and connected devices is growing at a compound rate of 61%, and could reach $26B by 2017. Coupled with data
The Revolution At the end of 2007 classic, Competing on Analytics, Tom Davenport predicted the rise of “analytical amateurs,” where the enterprise extends its frontline data analytics capabilities across the organization in its effort to become a data-driven enterprise. That transformation would be done largely without assistance from traditional information technology department capabilities and processes.
Data as a Service is a strategy that has been around, but only now have we observed it really coming into its stride. It’s used to access business-critical data in real-time, in a secure, affordable, “cloud” manner. For decades, businesses have sought to become more data-driven, making decisions more of a science than an art.
Executives recognize that the ability to effectively retain and recall knowledge is a mission-critical capability that must be approached strategically. Knowledge assets clearly create corporate value -- perhaps most measurably in the healthcare industry through drug approvals and patent protection. A granted patent or approval converts knowledge or data into a clearly defined commercial opportunity
Unofficially, a 2011 McKinsey white paper marked the beginning of the popularization of the term big data1. Since then, there have been enough large data set projects executed that we are starting to learn why these types of projects sometimes fail. In our opinion, the challenges associated with large data projects fall into five categories:
Company Profile Abbott Laboratories is an American pharmaceuticals and health care products company. Abbott has four core businesses - diagnostics, devices, nutrition, and pharmaceuticals - all of which focus on innovation to improve the health needs of people in more than 150 countries. Business Situation Abbott was experiencing an estimated 40% annual growth in its
Nearly two years into the FDA’s five year plan to invest in IT to meet the goals set forth in the Prescription Drug User Fee Act (PDUFA) and the Generic Drug User Fee Act (GDUFA), the FDA released two draft IT plans. The industry needs to keep a close eye on where the FDA plans