With the increased use of data-rich technologies, such as next-generation sequencing, mass spectroscopy, and light-sheet imaging, to name a few, researchers are finding themselves tasked with the need to manage much more data than they ever have before. Lab workers tasked with this new responsibility need to implement it quickly, and they often do so using traditional methods and tools. This is fine for the way labs have run in the past, but the methods need reexamination in this new world of data-rich science.

Technological advances come with increases in efficiency as well as increases in productivity, leading to more rapid turnaround of actionable scientific results or clinical diagnoses. Just as we have become more efficient in managing our lives (think about the impact of smartphones), it’s equally important to apply the same principles to become more efficient in managing our labs. While existing laboratory information management systems (LIMS) provide a good start to tackling this problem, there remain inefficiencies prevalent in the laboratory environment, including:

  • Managing Your Instruments and Software Platforms Independently
  • Using Ad Hoc Systems to Maintain Sample and Data Provenance
  • Rough Transition Process from the Wet Lab to Analysis
  • Not Delegating Routine Procedures to Your Lab Technicians
  • Letting Data and Knowledge Leave the Lab When Employees Do

This white paper explores these five inefficiencies we’ve commonly seen and explores ways you can make your lab more efficient using a fully customizable workflow engine.