Did you know that around 70% of digital transformation projects fail to reach their initial goals (McKinsey, 2022)?
Before you let that statistic discourage you from modernizing your laboratory, it is important to understand why this happens. Most organizations simply aren’t prepared for the transition; they adopt a software solution without securing the necessary budget, dedicating enough personnel, or training their teams. However, when done correctly, the results speak for themselves: 45% of organizations report major boosts in profits and productivity, and 56% of leaders say the effects of digital transformation exceeded their expectations.
Navigating this transition requires a structured approach. Based on 15 years of experience in laboratory software development and digitalization consulting at BioSistemika, and insights from over 100 global projects, here is our advice on 5 essential steps to successfully digitalize your laboratory.
Step 1: Assess your current state and build a vision
You cannot map out where you are going without knowing exactly where you stand. The first step is to thoroughly assess your current processes, conduct interviews with stakeholders, and identify operational bottlenecks.
During this phase, it is crucial to address the human element: change management. User resistance is a natural reaction, especially from staff who have relied on the same systems for decades. Your team might say, “I am happy with the current system”, “I don’t have time for this”, or “I don’t see the added value”.
To build a supportive climate, you must clearly explain the “why” using concrete facts. Instead of a vague goal like “going digital,” show them the data: “In the last five years, we had 10 compliance deviations due to manual transcription that cost us 500 hours and tens of thousands of euros to resolve”. Work with your internal advocates to define a clear vision and communicate it regularly.
Step 2: Define clear requirements and secure funding
Next, define your precise requirements, outline your budget, and set a realistic timeline.
A major mindset shift is required here: digital systems are critical infrastructure, just like high-end laboratory hardware. Laboratories rarely hesitate to spend hundreds of thousands of euros on analytical equipment, and software should be treated with the same financial priority.
Fortunately, you do not always have to rely solely on internal budgets. Funding can often be secured through national cohesion funds or EU programs like the Digital Europe Programme and Horizon Europe (Pillars I and II). These grants can cover eligible costs such as labor (software development and consulting), equipment depreciation, and software licenses.
Step 3: Choose the right system (and keep it simple)
With over 200 laboratory systems on the market, selecting the right one requires a structured evaluation process. The two most common foundational systems are:
LIMS (Laboratory Information Management Systems): Ideal for sample management, automating sampling workflows, and handling structured data. These are particularly crucial in diagnostic and regulated environments where traceability to the sample is key.
ELN (Electronic Lab Notebooks): Best suited for research environments, allowing scientists to document experiments and manage unstructured data with a strong emphasis on collaboration.
BioSistemika expert tip:
Avoid the trap of over-customization. Just as you wouldn’t ask your bank to customize the buttons on your mobile banking app, you should avoid overly complex modifications to your lab software, as they become expensive to maintain.
Step 4: Plan and execute the implementation
With the system selected, it is time to build your implementation plan. This involves defining your team, setting milestones, and identifying performance metrics and intermediate results.
During the actual implementation, focus on system setup, data migration, and training your “super users”. Do not expect your researchers to implement a new system on top of their full-time duties without dedicated time and training. To build momentum, plan for “quick wins“. Identify a system feature that can rapidly solve an immediate problem in the lab, implement it, and celebrate that small success to foster a proactive digital culture.
Step 5: Establish a feedback loop and monitor progress
Implementation does not end on launch day. You must establish a robust feedback mechanism. If users get stuck or frustrated, they need a dedicated support contact, such as a trained superuser, whom they can call for help. Continuously monitor the system’s progress and gather user feedback to make ongoing improvements.
The ultimate goal: Preparing for the future
By following these five steps, you aren’t just digitizing paper records; you are moving toward FAIR data: ensuring your data is Findable, Accessible, Interoperable, and Reusable.
Not only is this a requirement for European Open Science policies, but it is also the foundational infrastructure necessary to accelerate research and prepare your laboratory for the fast-paced world of Artificial Intelligence.
Ready to start your 5-step journey?
Whether you need strategic consulting, system evaluation, or help securing grant funding, BioSistemika is here to guide you.
Contact us today to turn your digital vision into reality.
