Introduction 

Biotechnology research is constantly changing, but laboratory software and technology don’t always keep up with the ever-changing innovation. Labs have difficulty focusing on the technology and software side of things because they’re focused on making new discoveries. That focus is correct, but due to limited resources, laboratories are suffering the consequences of not investing in modern software, which can not only save time and money, but can help make discoveries faster..

Most of the time, biotechnology labs are using Laboratory Information Management Systems (LIMS) that are outdated, if they’re using any formal system at all. Using legacy data management systems has caused labs to suffer from data silos, a phenomenon that stifles growth and innovation, and which is only getting worse with new discovery techniques..

What are data silos?

A data silo occurs when some data is in one location, while other data is in another (or multiple locations), and that information isn’t easily accessible by other groups (or even yourself) within your own organization or company. Data silos can happen in any industry and in any department within an organization.

In many cases, data silos develop naturally and are unintentional. This is what makes them particularly problematic – you don’t realize there are data silos in your organization until everything is a mess. Typically, this gets realized by researchers when it’s too late – researchers spend hours finding and linking data to provide a complete picture of an experiment or run an anlaysis. What’s the use of having a great deal of data if it can’t be easily searched or accessed by those who need it?

Why do labs have data silos?

Biotech R&D labs are notorious for suffering from data silos. Labs have a tremendous amount of information that they deal with on a daily basis, with many researchers working on various experiments and analyses simultaneously. If a reliable and intuitive data management system is not utilized, then labs find themselves without just one data silo, but many data silos.

If a proper data management tool is not in place then scientists within an R&D lab will have their own method of recording data. Data collection and storage might range from lab notebooks, paper and pen, Excel spreadsheets, Sharepoint, Google Drive, local devices, multiple cloud services, etc. These different data collection and storage methods create inefficiencies and data loss between data silos, compounding data management issues. ‍

Even if a data management tool is in place, if it is not intuitive for researchers to use, then they may choose to collect their data using the same siloed methodologies. Now the company has two problems, an expensive data management system and poor user adoption!

Why are data silos a detriment for R&D labs?

Data silos hinder and restrict lab operations by reducing the ability to analyze data and the ease with which it can be shared. Data is needed instantaneously and data silos hinder lab employees from finding the information they need quickly and efficiently. Data silos are a major impediment to faster workflows and smoother running laboratories. Workflows are directly impacted by data silos and research can, at times, be halted due to the inability to record, monitor, track, organize, and share data.

Within an R&D lab, data silos can cause:

  • Inconsistent data and low searchability. Naturally, people organize data in different ways. Currently, many labs use platforms such as Sharepoint and Google Drive, which allow individuals to input and organize data in their own unique method and to change existing “filing” systems. If access is granted, individuals can change and organize the data to suit their needs, which creates an inability to search and locate specific data when required. If one scientist is using a pen and paper while another is using Excel the data is not consistent and is entered differently, it reduces the data quality, accuracy, and integrity. This causes major issues downstream when researchers need to replicate the experiment or do additional analysis on these results..
  • Loss of time and increased errors. The amount of time wasted in a lab can be reduced if an intuitive software is utilized across the entire lab. With current methods, lab personnel lose a tremendous amount of time tracking their data (whether it’s with pen and paper, Excel, Sharepoint, etc) because each approach requires various levels of effort and accuracy. Time is lost when trying to search, analyze, and share data with others. It can take a long time to search through various locations, find a certain experiment, extract that data, additional time to analyze it, and more effort to share it.
  • Reduced collaboration. Data silos impact researchers’ ability to easily share their data. This hinders workflow and can impact the outcome of experiments and research results.
  • Increased security risk. Data silos perpetuate data storage in various locations, whether it’s on pen and paper, Sharepoint, or Excel spreadsheets. This allows users to access their data via unauthorized methods (such as storing on a personal device or cloud).. This dramatically increases the likelihood that data is lost or vulnerable to theft. As consequences for data breaches become more serious, companies need to put more focus on data security..
  • Duplicate data. Data silos do not allow easy access to information, therefore, scientists and automated equipment may input duplicate data into various locations or run experiments that have already been completed because there was no information readily available that was already complete.

Overcoming data silos within a lab – next steps

Limmi’s data hub allows biotechnology companies to seamlessly collect, monitor, track, organize, and handle all aspects of the research and development data with no downtime, no waiting, and, most importantly, allow effortless retrieval of data. No more lost or mislabeled data, everything is available in one place.

We brought 30 years of experience in the software and data science industry together to build a new type of data management platform that’s built to be highly configurable, requires no additional infrastructure for your lab, and easily integrates with your existing tools and workflows that are already present in the lab. Limmi makes it easy to get started if you’re a small laboratory, but is also scalable, allowing it to grow with your lab as you expand.

Our intuitive tool was written with scientists and lab employees in mind. Limmi was designed to dramatically improve all aspects of the lab workflow, ensuring that time is saved, efficiency is maximized, and data is secure and easily accessible. All information about lab inventory, each experiment, and all results are readily available and effortlessly shareable. Other laboratory software systems simply wrote software that scientists and lab employees then had to “figure out.” Limmi did the opposite – considering the scientists and their needs and then built a dynamic software that is intuitive and puts the scientist in control.

Conclusion

Data Silos tend to occur naturally in businesses and laboratories because different people and automated equipment tend to use a variety of different platforms and methods to record data. These naturally occurring data silos create a host of issues for labs that increase costs and errors. The best solution is an easy-to-use, intuitive, and quick to implement management system such as Limmi, to help lab personnel record and manage data in a modern and easy to use way.

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