“Every piece of equipment has a finite life.” This saying is common among lab managers and other lab staff. Like humans, equipment slows down, produces errors, and breaks down, often at the worst times. And as humans, we tend to hold onto things far too long. However, relying on aging equipment, especially sophisticated instruments like a liquid chromatograph mass spectrometer (LC-MS), can put your lab’s work at risk. Determining when an instrument has surpassed its optimal performance can be challenging for a variety of reasons, but this decision-making process is an important one that lab managers must feel confident doing.
What are the risks of aging lab equipment?
Aging systems can bring increased risk—some are obvious while others often go unrecognized until they unexpectedly occur. We may fail to notice that instrument performance is beginning to degrade, but failures to meet system suitability or injection failures are hard to ignore.
HPLC system downtime due to routine maintenance or repair is an obvious risk to business continuity. If you don’t have someone in-house with the expertise and time to troubleshoot instrument problems, you may need to pay for a service technician to travel to your lab and perform the required services—an expensive proposition. In addition, lab managers can spend a considerable amount of time sourcing spare parts, spare instrumentation, or reorganizing schedules to overcome the lack of fully operational HPLC instrumentation.
There also comes a time when instrument vendors cannot continue to provide all the parts or support necessary to maintain older systems. Software defect corrections or enhancements related to significantly aged or obsolete instrumentation will no longer be offered and there are advantages in upgrading in terms of technical support and instrument performance. Aging technology usually isn’t compatible with today’s new smart and connected labs.
What factors influence our decision-making process?
There are several reasons why lab managers may delay investing in a new system. These are mostly explained by our experiential risk decision-making frame. Fear, uncertainty, and doubt hit our risk center hard and motivate us to act. This helped us survive but now plagues us with indecision or bad decisions. We also fear taking the wrong action more than no action. Here’s where inertia and procrastination often live, ready to attack our abilities to decide. Threat(s) to value often override any objective risk decision-making, too. If a lab manager’s greatest value is the lab budget, costs will represent a threat to that value.
Risk combines severity of consequence with probability of outcome (and sometimes adds in our exposure to the hazard) as a third factor. Unfortunately, humans are notoriously bad at differentiating probability from possibility. A lab manager might wonder, “What if my methods don’t translate easily to a new HPLC system?!” Or, “Why should I spend money on a new HPLC when my existing system works fairly well most of the time”… Decisions are difficult to make and so we get stuck with indecision despite improved instrument performance and uptime being a benefit to the business, reputation, and customers, and so often no decision is made until instrumentation fails completely and productivity is unfortunately impacted.
As you can see, when it comes to humans, risk-based decision-making is more complex and messier than most of us realize. It’s called “judgment under uncertainty” for a reason. We’d like to think we’re deeply analytical when it comes to risk, but we’re not, we’re emotional. There are three risk systems—analytical (cognitive/logical), experiential (affective/emotional), and political (social groups). We don’t use them evenly when it comes to risk decision-making. We use our experiential risk system more than our analytical risk system.1
Our cognitive biases influence our risk perceptions. Two examples are the sunk cost fallacy and confirmation bias. While others are possible, these two dominate for aging equipment. The sunk cost fallacy causes us to give greater value to our previous costs we have sunk into it than to the value of investing in a new one. An example is, “We’ve spent thousands of dollars maintaining our old workhorse HPLCs. How can we possibly give up that investment?” This fallacy dominates our thinking despite likely cost savings due to fewer failures, lower solvent costs, lower service costs, and less downtime.
Confirmation bias is when we falsely believe in our existing mental model. An example is, “This is working okay as I see it, so I don’t need to invest in a new one.” This is a common mindset despite other evidence that it’s not working, such as poor performance, data quality issues, break downs, communication errors, out of specification results, and failing to keep up with industry standards.
We also use mental shortcuts to make quicker and easier decisions. Our brain is only about two percent of our body weight, yet it uses 20 percent of our fuel to run it. So, it needs to find easier, less energy-intensive means to process input and create actions. Lab managers already have so many decisions to make each day that mental shortcuts are necessary but have consequences.
How can lab managers address fears around instrument decision-making?
Change can be scary. Our first concern is often the cost, both hard and soft. What’s the initial capital cost? What about service? How much downtime will result while the new system is installed and tested? Will it work differently? How much re-training will we need? What other unknowns might we experience? It’s an emotional thought process with many questions, which can feel paralyzing. A decision may seem watered down, but a simple list of pros and cons can help—start by listing them. Then go back and give each a priority ranking if that’s easier.
The benefits of replacing aging lab equipment
Managing and mitigating concerns around replacing aging instrumentation opens you up to see the benefits of a new system. A new piece of equipment will often provide access to new functionality. Sometimes this isn’t realized by the lab staff until they try it out and someone will excitedly say, “Did you see what it can do?”
Along with new functionality, it might provide helpful automation to a process that required manual attention before. With the moves toward smart and connected systems, QA and training costs may be expected to decrease. Typically, new equipment runs more efficiently, has significantly improved uptime, is design to more easily troubleshoot and operate, and the performance of the instrumentation is improved compared with legacy technology. Employees are often motivated by the opportunity to work on modern technology and learn new skills and are usually very keen to spend less time troubleshooting and more time getting their work done. New equipment also helps ensure data quality, reduced variability, and can contribute to lab sustainability efforts and metrics.
It’s important to involve staff in the process of evaluating new technology given their many perspectives and knowledge. They may have experience gained working on different vendors’ systems and will have more direct knowledge of the quality of service and support from different vendors. They might be more aware of regulatory changes that could help impact a purchasing decision (e.g., related to the benefits of scaling methods using allowable adjustments and changes to USP 621). Often, it’s not until the team goes through the full assessment process together that the solution becomes as clear as a pristine pool of water. Having an open and growth mindset are key.
We must constantly make judgments or risk-based decisions. Our experiential risk system dominates our analytical one causing a variety of problems. Cognitive biases, mental shortcuts, threats to value, fear, uncertainty, and doubt often prevent us from performing sound, objective evaluations.
Older systems have many risks that create both current and future issues. Some of these risks are obvious, while others are hidden away. Newer systems hold many values and benefits. Just like risks, these benefits are both apparent and covert, and resolve immediate needs as well as needs still to come as the lab evolves. Managers must decide for their lab’s needs to be both efficient and effective. So, what’s your risk appetite for equipment failures?
1. Slovic et al. “Risk as Analysis and Risk as Feelings: Some Thoughts about Affect, Reason, Risk, and Rationality.” Risk Analysis. Vol. 24, issue 2, pp. 311-322. April 2004. DOI: 10.1111/j.0272-4332.2004.00433.x . https://onlinelibrary.wiley.com/doi/abs/10.1111/j.0272-4332.2004.00433.x.