Hi all automation nerds,
I love this forum for the technology exchange with like-minded, but am wondering how you transform your excitement into the real lab world where the majority of scientists and technicians often is very reluctant and maybe even scared of the changes to come with lab automation?
Do you have any tips&tricks or strategies to get people on board of the journey?
I am planning an implementation workshop for our new automation system and need some advice on how to overcome current reluctances and plant a seed of change&chance into people’s minds.
Thanks for your feedback, Cornelia
Hi Cornelia,
for me it worked like this: Show how much throughput I can handle with the robot vs. manual pipetting. Fast and reliable results will convince almost everybody.
Don’t frighten people to break sth, tell them that this can happen but is very rare if good care is taken.
best
Dominik
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In my experience, they just have to see it in action. No amount of visuals or data is going to change people’s minds as much as seeing it in person and running it to compare against their manual process. Not even scientists are immune from BS emotional, personal feelings. And in fact, I’ve heard a few stories of scientists trying to sabotage automation data so keep an eye out.
The other thing that will force change is $$$. If your automation is a big cost saver for the company, a strategic part of their vision to reduce costs and increase throughput… why even waste precious resources trying to convince scientists or technicians? Let the VP’s & higher ups handle that, it’s their job. Your job is to implement & execute, that battle has been fought & won as far as you should be concerned.
Finally, how do you ensure proper implementation? Accountability. Flat out. It’s all fun and games but at the end of the day, people need to be held accountable so that decisions and outcomes are data driven and business driven.
This isn’t 2005 anymore, automation has come a long way and people have to adapt or move out of the way.
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My answer is not nearly as deep as some of the others but…
One time I just made a quick method that people could put in their initials into a prompt and the instrument pipetted dyed water into a 384 plate in the shape of their initials. I put a clear seal on it, and everyone kept the plate as a souvenir.
I guess moral of the story is similar to what @luisvillaautomata said but more along the individual bias part - making sure folks are having fun and enjoying work can go a long way.
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Very true and though…
I can read your own frustration between the lines and carry mine from previous experience as well. Therefore, I would actually prefer to give the key players the chance to play along before management kicks in. Also, because I need trustworthy people to implement and run the system.
It’s not frustration, it’s business.
They can be as much a part of this process as the rest of us (and I love working with scientists who are legit curious about automation) but ego’s need to be checked in at the door. Furthermore by the time the equipment comes through that door, the decisions generally have been made at a strategic level and it’s up to all parties to ensure that implementation is carried through to the best of everyone’s capabilities.
I try to involve scientists early and up front but I am honest that this is business and the business decision has been made so we either work together or this fails (and it won’t fail on my end.)
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Obviously I’ve got a few dogs in this fight as I’m an automation sales rep that has a big focus on the segment of folks with no automation experience/helping automation teams expand their automation footprint into the ‘standard’ benches.
With that being said up front:
- take your time. Unless you are higher-up and can just decree a change, it’s going to take time to get people on board.
- break it down. There is a lot of jargon in the automation scene–simplify it and explain your terms. When describing a function, explain why it matters. We’re really good at assuming certain things are self-evident because we are very familiar with it.
- Use transition instruments. (Once again, a bit self-serving since I sell a lot of these, but it’s a viable strategy) Often times these applications don’t have to be fully automated (or don’t necessarily justify the expenditure or space a large system takes). Warm people up to automation with semi-automated instruments or processes. To speak from my portfolio, get a handheld decapper to familiarize people with automation friendly tubes and decapping. As throughput ramps, you can get a more expensive benchtop system. Get something like the ML600 for basic repeated dispenses. they have to control it, but the liquid movements are all pre-programmed. Or step into truly automated instruments with something like the ML Prep–it’s not going to automate an entire workflow, but it can take on those tricky or tedious steps and automate chunks of the workflow. As they see automation actually helping and being reliable, then you can scale into the larger systems (that are often a little trickier to setup/program/run).
Education and getting hands on are key. And all of this goes no where without support in management.
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Great thread and advice from others! To win over cautious colleagues, try to focus on their core values. Those may include:
- Consistency: Automation ensures consistent, well-defined processes for every experiment, reducing human error.
- Data Quality: Automation minimizes (human) errors for meticulous protocols and quality control, leading to reliable data. This benefits everyone from technicians to scientists to the institution at large. Automation also frees up time for researchers to focus on the fun part: the actual science.
- Budget Efficiency: Automation can save time and resources, allowing the lab to be more competitive and invest in future advancements. e.g., the I.DOT Liquid Handler automates all of the liquid handling steps in any given workflow, saving valuable time and money on consumables like costly reagents and tips. No prior automation experience and little training required.
These are some methods to get them to the eventual live demo phase, which, like others have said in this thread, ultimately seals the deal.
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Hi Cornelia,
Thanks for raising this important subject. You hear countless stories of robots sitting unused because the application/implementation wasn’t right or the experts moved on. I agree with all that is said above and this echoes some of that but maybe there is something new.
The question you ask depends on many things, complexity of kit and application e.g. an out of the box solution rolled out and easy to use vs. an in-house team writing applications with some vendor support/custom methods developed by a vendor. The harder win is if it is automation of a task that they don’t see a big difference time wise doing the way they have always done it, e.g. diluting a few samples, and you would revert to this in case of robot issues. Any robot failures, lack of ease of use will be a major deterrent, uneasily forgiven. The easier win is the automated process is so much faster/efficient that it becomes the only way to do that method and they have no choice.
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Management support is key. To put in the capital for the equipment but also, and probably more importantly, to resource the rollout and maintenance, training (including time allocated for scientist and technician acclimatisation) etc time as required with redundancy if that expert resource was to leave.
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Users need to see how this benefits them personally as they will fear the robots will take their jobs. Their skills and day-to-day work will likely change and that is scary. If they are scientists it will free them up from the mundane tasks to think about and understand the science, automation (if implemented correctly) means the company can take on more work/do work faster with the same workforce and stay competitive and in business, it improves their skill offerings, reduced RSI . . I’m sure they are many more. There will always be laggards , I think this video describes it well https://youtu.be/zClAdLw4yRI?si=jf5uFIE-by8e_W3L Maybe collect their concerns before the workshop so you can have some ready answers.
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Ease of use and reliability are important. Test applications out with the more willing users first, and a wide breadth of them, who are willing to weather a few failures/imperfections and give feedback. Where are the misunderstandings and clarifications needed so a more reluctant user doesn’t go through this first. Every software/hardware has it’s bugs understand them, a great example is this forum. Equipment breakdowns happen but typically are replaceable parts e.g. filters on Di-Tis arms, fingers for plate arms, fixed tips. Have in-house ability to fix these and get going again with minimal down-time.
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Have someone available to support those reluctant users. Have good user prompts, training materials, error support etc to build confidence with the systems. @evwolfson made a great suggestion about the app to write your name, we also did this. Also good for visiting students and marketing vids
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Help them understand the limitations of the system and the possibilities e.g. case studies of successful in house application with early adopters. As suggested above collect their concerns before the workshop so you can have some ready answers. I often get asked what is the smallest volume required and if you have a very small volume sometimes you won’t have enough to run that sample automated with dead volumes vs. manually - potential workaround you can pre-dilute or find labware with smaller dead volumes etc. For dilutions what sample number cutoff (1,10,20+) makes sense to use this system . . .I do try to argue that even 1 sample as you are getting trained and comfortable with the system for when you have 100 that you would not take on manually.
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If the automation team/support is entrenched in the group of users that will be easier. If you have broken out more separately eventually it will be worth having an enthusiastic champion from each team who works with the systems. They can sell it to their teams and be the main contact with the expert group as the user group will know them better. The champion will understand what their team needs the equipment to do.
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Thanks for your detailed reply. The video describes very nicely what I have observed throughout my lab automation journey as well and really gives some greater perspective on how to address this problem.
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