When it comes to investing in a data management solution, it’s not easy to decide on when is the right time to implement a system. For young, growing R&D companies, this may not feel like a top priority. If you’re working with a small team, managing data using Word docs, Excel spreadsheets or even paper notebooks may seem sufficient for the time being. However, there are significant organisational benefits starting to use a data solution early on, rather than playing catch-up later. Here are 5 reasons why having a data solution is a valuable asset for small teams and is a good long-term investment as your research processes scale up.
1. It is a lot easier to implement a system early on than when it’s overdue.
It’s only a matter of time when a company reaches a certain scale, and adopting a data solution becomes a necessity. However, migrating existing data to a mature data solution at that point can be a painful process. Compiling scattered files, paper records, and email attachments is error-prone and extremely time-consuming. It’s also more difficult to convince your scientists to adopt a new system when they’re already used to a certain way of recording their data. Instead, if you set a system in place early on, you can avoid painful system migrations and risk losing valuable data in the process.
2. Better project continuity and knowledge transfer as your team evolves.
If you don’t have a unified method of data documentation, every scientist has their own personalized approach to recording experiments. This means individual paper notebooks, files saved locally on personal computers or personal Google Drives. It can become a big problem when scientists leave the team and there is a disconnect in knowledge transfer, leading to costly data loss for the company. Thus, maintaining a standardised system for data sharing can prevent inconsistencies in ongoing projects as the makeup of your team evolves.
3. Quick access to comprehensive data can save time and resources.
Every bit of effort counts, especially for young companies, so the last thing you want is spending an unreasonable amount of time searching for your data or duplicating work that has been done already. This can cause delays in your research processes and may negatively impact your progress. Having a data solution in place can eliminate these pain points and help you focus on the more important tasks.
4. New age data solutions are flexible and configurable to evolve alongside your research.
There’s a general consensus that most legacy data systems are laborious to upkeep and can take up to months to get set-up. For growing companies, by the time the legacy system is fully deployed, your research needs may already be different. Finding a data solution that offers flexible configuration and can accommodate changes in your R&D workflow with minimal effort is key. Compared to clunky legacy systems, the new generation of data management platforms with modernised UI designs and software configurations are more optimised to meet the needs of growing research teams.
5. A unified data system can help you make better R&D decisions.
It can be an uphill battle for growing R&D companies to improve the efficiency and effectiveness of their R&D processes without a unified data system. This is especially true if you’re developing novel workflows or having to industrialise complex research pipelines. Thus, having a system to help standardize and structure data into a comprehensive overview can help you make better decisions that will lead to more reproducible and desirable results.
Labstep is a provider of scientific data management software for R&D organisations across industries (Biotech, Pharma, Biology, Chemicals, Agriculture etc) who need to manage, capture, share and use data effectively.
The Labstep platform is an end to end flexible research environment that connects your notebook, inventory, applications and data in one collaborative workspace.
Curious to learn more about how to get started with a data management system? Contact us or book a demo today