We spend a lot of time talking about developing early-career professionals. And we should. Mentoring, stretch assignments, career paths, networking, professional development — all of that matters.
But I’ve been thinking about the other end of the career spectrum.
What about those of us who’ve been doing this for a while?
I’m well past the point where anyone would call me early-career, but I certainly don’t consider myself finished. Not even close.
My career has been built around adapting, changing, learning, and transforming as the world around me changed.
I started working in an environment that looks nothing like the one we operate in today. I’ve watched laboratory automation go from concept to reality. I’ve seen paper-based laboratories move toward electronic and increasingly paperless environments, and standalone instruments become connected systems in laboratories far more integrated than most of us imagined when we started.
I’ve also watched computer system validation evolve, data integrity become a major focus, cloud technology become commonplace, and now AI is changing things again. And I like it.
I’ve never believed experience means continuing to do something the same way simply because that’s how we’ve always done it.
Quite frankly, if I had taken that approach, I’d probably still be carrying a three-ring binder around and asking someone where the fax machine is.
Experience should make us better at change, not afraid of it.
Laboratory Automation Is a Good Example
When laboratory automation started becoming more common, there was plenty of discussion about what it would mean for laboratory jobs.
What I’ve seen in many environments is that automation didn’t simply replace people. It changed the work.
Automation took over many repetitive activities that consumed time but didn’t necessarily require a lot of judgment. That allowed scientists and quality professionals to spend more time interpreting results, investigating problems, evaluating risk, improving processes, and making decisions.
In other words, the technology changed where people could add value.
That’s an important distinction, especially as we talk about AI today.
Automation can execute a process, but someone still needs to understand whether the process makes sense. A system can generate data, but someone still needs to understand what that data is telling us. Technology can flag an exception, but someone still has to decide whether the exception matters or whether the system is just having a bad day. Critical thinking becomes more important, not less.
I learned early on that it’s not enough to simply provide the data. The real value comes from understanding what the data means and what should happen next. That’s even more true in an automated laboratory. The technology can do more of the repetitive work, which should give people more time to think, question, interpret, and make better decisions.
The Paperless Laboratory Has Changed Too
For years, people talked about the paperless laboratory as if it were always five or ten years away.
Sort of like the flying cars in The Jetsons. Those are still taking their time, but the paperless laboratory is a lot closer.
And a paperless laboratory isn’t simply taking the same paper process, scanning it, and calling it digital.
The real opportunity is changing how information is created, captured, reviewed, approved, transferred, and retained.
It’s about reducing unnecessary manual steps, duplicate work, disconnected systems, transcription, and opportunities for error.
That changes how we have to think about quality too.
We can’t apply yesterday’s thinking to today’s automated, connected laboratory and expect everything to work.
We have to understand the process as a whole, not just whether System A passed a test script. That takes experience — and a willingness to admit that the way we did something 15 years ago may not be the best way to do it today.
Yes, I Still Need Development
Once you’ve been around long enough, people assume you’re the mentor. And I am.
I enjoy mentoring people. I enjoy sharing what I’ve learned. If someone can avoid a mistake because I already made it 20 years ago, I consider that a pretty good return on my investment.
But being a mentor doesn’t mean I don’t need mentors, and being experienced doesn’t mean I no longer need development.
Being a CEO certainly doesn’t mean I’ve somehow completed the professional-development portion of my life and received a certificate saying, “Congratulations, you now know everything.”
I assure you, no such certificate has arrived.
There are plenty of things I don’t know, and that’s fine.
Somewhere along the way I learned it’s perfectly acceptable to say, “I don’t know.”
The important part is what comes next:
But I’ll find out.
That may get easier with experience. When you’re younger, there can be pressure to prove you belong in the room. After you’ve been around a while, hopefully you become more comfortable admitting there are things you still need to learn.
There are new technologies, new ways of doing business, new approaches to leadership, and completely different ways of looking at problems that I can still learn from.
And sometimes the person who understands something better than I do is 25 years old. Great.
Teach me.
Reverse Mentoring Shouldn’t Be Strange
I think we need to get more comfortable with reverse mentoring.
Mentoring doesn’t always have to mean the person with 30 years of experience teaching the person with three.
In fact, one of the most useful reminders for anyone who’s been around a while is this:
You’re never really the smartest person in the room.
You might have more experience in a particular area. You may have dealt with a similar problem ten times before. But someone else in that room knows something you don’t. That’s not a weakness. That’s why you have a team.
Having the highest IQ in the room and being the cleverest person in the room aren’t the same thing. I’d rather surround myself with capable people and lean on them — which is exactly what reverse mentoring is.
I might be able to help someone work through a difficult client situation, understand a regulatory expectation, prepare for an inspection, or recognize a risk because I’ve seen something similar before.
They may show me a better way to use AI, automate a process, analyze information, or look at a problem from an angle I hadn’t considered.
That sounds like a pretty good trade to me. If someone knows something I don’t know, I want to learn it. Their age doesn’t matter.
And for the record, if someone can show me a way to eliminate three unnecessary steps from something I’ve been doing for 15 years, I’m not offended. I’m annoyed I didn’t know about it sooner.
Knowledge Transfer Works Both Ways
Those of us who’ve been doing this for decades also carry around a lot of knowledge that doesn’t always show up in an SOP.
We remember why certain decisions were made, why a procedure contains a particular requirement, what happened the last time something was tried, and where a process tends to break down in the real world.
A lot of that comes from experience, and organizations need to capture it.
But knowledge transfer shouldn’t mean the experienced person downloads everything they know into someone younger, gets a cake in the conference room, and then disappears.
It should go both ways.
I give you context.
You challenge my assumptions.
I tell you why something worked 15 years ago.
You show me why there may be a better way to do it today.
That’s where it gets interesting. And frankly, that’s where both people get better.
And Now There Is AI
I’ve made a deliberate effort to understand and use AI.
I use it. I experiment with it. I challenge it. I look for ways it can improve how I work and how our business works.
Not because it’s trendy, but because I believe it’s going to materially change how we work. Experience also teaches you something useful about technology: it can give you a convincing answer and still be completely wrong. Sometimes spectacularly wrong.
AI can generate an answer in seconds. Experience helps you decide whether that answer makes sense.
That combination is much more interesting to me than arguing about whether AI or people matter more. We need both: technology gives us speed and capability, experience gives us context and judgment. Put them together and we can accomplish quite a bit.
Keep them separated and we’ll spend a lot of time either doing things the old way or confidently doing the wrong thing much faster.
Neither sounds particularly appealing.
I Have No Interest in Standing Still
My business has changed. My role has changed. The industries we work in have changed. Technology has changed.
And I’ve changed with it. That’s intentional.
I’ve been saying for years that success is a journey, not a destination. That’s not a motivational poster to me. It’s a description of how a career actually works.
I have no interest in standing still. And neither should you.
It doesn’t matter whether you’re 25, 45, 55, 65, or somewhere in between.
The moment we decide we know enough is the moment we start falling behind.
Take the chances. Treat challenges as opportunities instead of things to avoid. Even when something doesn’t work out, you usually come out of it better prepared for whatever is next.
I don’t want to spend the later part of my career explaining why every new idea won’t work.
- I’d rather ask how it could work.
- What could we do differently?
- What risk do we need to manage?
- What opportunity are we missing?
And the most important question:
What do I need to learn next?
That question has no age limit.
Standing still may feel safe.
I’m not sure it actually is.
Maybe We Should Ask That Question More Often
We routinely ask early-career professionals where they want to grow.
We should be asking experienced professionals too — not because we need another formal development program with a 14-page form and six required signatures. Just ask the question.
- What do you want to learn next?
- What are you curious about?
- What would make you better at what you do?
- Who could you teach?
- And who could teach you?
Organizations should also ask themselves something a little harder:
Are we still developing our experienced people, or have we quietly decided they’re finished developing?
I know my own answer.
I’m still learning, still changing, still experimenting, still mentoring, and still willing to be mentored.
Experience is not an expiration date.
If anything, it should give you a better foundation for whatever comes next.
So whether you’re early in your career or have been doing this for decades, ask yourself one question:
What are you going to learn next?
I already have a few things on my list.
And if someone can tell me where Microsoft moved that button after the latest update, we can start there.
Joseph A. Franchetti, President & CEO, JAF Consulting, Inc.
