Decision-making is a core responsibility for all lab managers. As management guru Peter Drucker said, “Decision-making is the specific executive task.” The staff and the organization are dependent on these decisions to proceed. Difficult decisions often come when there are unpleasant choices, a lack of real alternatives, or a fundamental disconnect between the values of the organization and the individual making the decisions. Making these difficult decisions puts significant stress on most lab managers.

A disciplined approach and access to appropriate data are required to better navigate difficult decisions. Big or difficult decisions benefit from a decision-making process that moves through five different stages: defining the question; gathering information and data; evaluating alternatives; deciding; and following through. It might seem that defining the question is obvious because a decision is needed, but it is worthwhile to ensure that the right issue is being decided. Much time can be wasted gathering information around a tangential issue. Clarifying the question also aligns the lab leadership team around just what needs to be decided, and the parameters of that decision.

Get training in Making Data-driven Decisions and earn CEUs.

One of over 25 IACET-accredited courses in the Academy.

Making Data-driven Decisions course

Utilizing data to make informed decisions

Making difficult decisions is like many other problem-solving activities. It is greatly beneficial to invest some time and energy in exploring the causes of the issue, accumulating appropriate data related to the decision, and investigating options and alternatives. One of the common mistakes involved in difficult decisions is rushing to a specific outcome before the data is evaluated and all of the alternatives are understood. It is especially important for big and/or difficult decisions to ensure that all appropriate options are understood prior to making the decision. Part of this information gathering process is to obtain, and use, the appropriate data. Data-driven decisions are more objective, easier to justify, and easier to explain than decisions made in the absence of supporting data. Evaluating the available information and alternatives is often best done as a team. Even if the decision needs to be made by the lab manager, getting context, perspective, and new ideas from other lab leaders can shed new light on the required decisions. In addition, using data to drive decisions comes naturally to many lab managers because of their history as lab scientists who effectively gathered and analyzed data while executing scientific roles. 

One part of the decision evaluation process that is often overlooked is risk analysis. It can be helpful to consider the best and worst outcomes of the decision, as well as the most likely outcomes, and have a discussion with lab leaders about how well the lab can tolerate the likely risks. One of the key risks to consider is the negative outcomes from postponing a difficult decision. While a thorough evaluation is important, it is also important to make decisions, and not to get bogged down in analysis paralysis. Teddy Roosevelt said, “In any moment of decision, the best thing you can do is the right thing, the next best thing is the wrong thing, and the worst thing you can do is nothing.” The whole lab relies on the lab manager making decisions. The absence of decisions undermines trust in staff, erodes employee engagement, and derails the effectiveness of lab operations.

Communicating decisions to staff

Once a decision is made, it is vital for the lab manager to follow through. The absence of action following a key decision is identical to no decision being made. The first step of follow-through is communicating the decision to the rest of the lab. This communication must include several different components: the actual decision, why it was made, the expectations of actions, and how to sustain the decision. The more difficult the decision, the more important the communication surrounding it. Following the communication, the lab manager needs to generate an action plan to ensure the decision is implemented and sustained. Peter Drucker also said, “Unless a decision has degenerated into work, it is not a decision; it is at best a good intention.”

"The more difficult the decision, the more important the communication surrounding it.”

During the follow-through process, it is also important to continue learning. Evaluate the effectiveness of the decision and strive to learn if the evaluation process preceding the decision worked well to guide the lab to the best outcome. Building a culture of continual learning helps labs to build resilience around change, and helps lab leadership adjust and modify decisions to reach more optimal outcomes.

While there are many different kinds of difficult decisions that lab managers face on a regular basis, here are three examples to illustrate the process.

Terminating a staff member

Terminating lab staff is perhaps the most difficult decision faced by a lab manager. Whether through performance issues or driven by an organizational layoff, a termination decision is personal and permanent. Some factors to consider when contemplating a termination include the level of performance of the individual, trends or progress in their performance, the impact on teammates, the risks (operational, legal, organizational), and any available alternatives. Terminating a poor performer can be put into context when considering the impact of the poor performance on teammates, and the message to the organization of accepting the poor performance. Terminations driven by layoffs are much more difficult because the process devolves into which person(s), rather than when.

Promoting a staff member

Promoting a deserving colleague can be a great joy of lab management. Making the decisions about who has earned the promotion most, and what the lab can afford in promotional increases, often makes these decisions difficult. These difficulties are multiplied in organizations that strictly restrict promotional budgets or place additional burdens of proof on lab managers to approve promotions. Sometimes, the most difficult decisions regarding promotions are around communicating to deserving individuals that their promotion was denied or greatly delayed.

Some factors to consider when contemplating promotions include the merit of the candidate, the increase in responsibility, observed attitudes and behaviors, performance versus expectations, the cost of the promotional increase, equity of the decision, and priority with respect to other candidates. Gathering data on all of these inputs and evaluating them objectively will help drive decisions that are coherent and equitable.

Purchasing new capital equipment

Lab staff expect management to provide the tools, equipment, and instruments required to execute the science. However, budgets are limited, so lab managers face difficult decisions about what and when to purchase new capital equipment. Some of the important considerations around capital purchases include evaluating needs versus wants, prioritizing needs, budgeting for capital, evaluating return on investment, exploring alternatives (like outsourcing), and understanding the cost of ownership.

The key difficulties are around communicating difficult choices to lab staff, and effectively advocating capital needs to senior management. Following a data-driven decision-making process enables better communication in both directions. 

Lab managers make a significant impact on their labs through the decisions they make. The bigger and more difficult decisions often have the greatest lasting impact on the success of the lab. Having a robust decision-making process that includes defining the question; gathering information and data; evaluating alternatives; deciding; and following through enables lab managers to make more thorough and objective decisions, and communicate the decisions to the lab with greater clarity and confidence.