Collecting and analysing data from laboratory or industrial equipment can be time-consuming and complex.
Whether you are typing up handwritten notes, copying data points from Excel spreadsheets, or using multiple manufacturer’s platforms, data logging and documentation can be tedious.
The overwhelming task of automating and standardising data logging is, in most cases, the main reason why even global companies have yet to fully leverage the potential of their lab data.
One roadblock is dominating
In 9 out of 10 cases, we found that the main reason companies do not start standardising their data gathering from lab equipment is the perception that you must have all systems and processes in place to create the desired value.
But this perception is wrong.
If there is one thing we have learned at Inniti after years of helping industrial SMEs and global companies do more with their equipment data, it is this:
There is no perfect plan.
We see that some of our clients have been most successful in extracting and utilising equipment data by using one simple mantra:
Think big, start small, learn fast.
Based on this mantra, we came up with five steps you can do today if you want to successfully gather high-quality, reliable equipment data to enrich your product development, quality control, and production.
1. Find a starting point
Start small and find a starting point that is attainable for your organisation. Select a simple process or piece of equipment that could benefit from standardised data and lead to more value creation. This will be your first use case.
My main advice in this step is to start simple and focus on value.
2. Leverage data to add value - the pilot
After you find a use case where you can add value, you can collect the first data points to better understand which kind of data would enrich your lab operations or industrial processes.
The magic of this step is doing more with less.
Get a solid and granular understanding of what data you need and do not need. You will save yourself and your organisation time by only setting up structures for collecting the data that adds value to your use case.
3. Operationalise data logging
Now that you know which data points you need, you can establish structures for collecting data regularly. This can be done manually or digitally.
This is often the step where solutions like Inniti can be extremely helpful. Inniti is a flexible connectivity solution that can free up valuable resources and make operational structures more efficient, secure, and stable.
4. Prove the use case and copy the approach
Now that you have completed one use case and discovered the added value, choose a new case and replicate the process.
Your next use case will be much easier to plan and execute. Once you see the value created and how quickly you get results, you will be eager to replicate the process.
5. Start building big and automate
The final step is where you can really start thinking in scale. At this point, your organisation will understand how to build successful use cases and valuable processes when extracting equipment data.
You now have a solid understanding of how to scale your use cases across your organisation.
Additionally, if you haven’t already found a way to automate your data logging, now is the right time. You can either implement custom solutions designed for your purposes or set up a more flexible solution such as an Inniti solution or similar to allow you to easily scale your digital set-up.
Automating your data logging will also be extremely valuable for integrating your data output into your ERP, LIMS, ELN, or whatever system your organisation uses to store and analyse data.
So, make sure that whatever solution you choose has flexible integration opportunities.
Need help putting these steps into action? Let’s talk.
At Inniti, we work with global companies to digitalise processes, automate data logging, and help them get more out of their data. We would be happy to talk with you.
Inniti helps ambitious companies do more with their data. Our IoT Connector and cloud-based platform enable companies to access, analyse, and monitor data from lab and industrial equipment.