Chief Strategy Officer Yahara Software, Wisconsin, United States
Many laboratories purchase a LIMS in the hope that it will be the answer to all laboratory software questions and struggle to know what other systems could be beneficial and when their lab might need a larger software ecosystem to fully support it’s operations. Like all software, each LIMS has a specific set of features and functions which makes it better suited to some tasks than others. As the marketplace grows, LIMS have emerged which are increasingly tailored to certain disciplines (e.g. microbiology, chemistry, bioinformatics) providing increased support for specialized areas but reducing the likelihood of flexible, broad range applicability across organizations. And while many enterprise LIMS vendors provide additional applications in order to fully support laboratory operational needs, they can be prohibitively expensive or require more support than desired depending on the feature sets provided.
In this talk, we will provide information on the various processes within laboratory operations where software can prove beneficial by reducing errors, creating efficiency gains, or both. We will demonstrate through case studies how different needs can produce different laboratory software landscapes. During the talk, listeners will learn about overall software strategies, such as enterprise vs. best of breed and the benefits and risks to each approach. We will review the types of software they might consider to meet their needs, (LIMS, ELN, QMS, integration engines, data analytics platforms, etc.), what the focus of each software application is and the task it is best suited for, as well as what questions to ask when assessing these systems for fit within their own laboratory. Finally, we will provide information on the trigger points that commonly cause laboratories to consider adding new software or upgrading current systems.
At the end of the talk, listeners will emerge with an overall picture of how and where software can support laboratory operations as well as the set of applications (in addition to LIMS) commonly found in laboratories and strategies to assess their own software landscape for improvements in the future.
