By Matthew Wilson

Team MeetingFor one term of my tenure as an undergraduate at UC San Diego, I held the position of lab technician for a photography lab that was available to all students on campus for a quarterly fee. My duties for keeping the dark room in proper working order were various: ensuring all chemicals were fresh and available for use, maintaining all enlargers and other equipment, cleaning, and helping lab users with any pressing issues as they arose.

I held this particular position for one term and one term only, and the reason for my short tenure was simple: My time as lab technician was an unmitigated disaster. I received constant emails that chemicals were not performing their proper developing or fixing duties, that enlargers were not functioning properly, or that some crucial component of the overall apparatus was missing.

Analysis in the Dark
The first appearance of these problems provided an excellent opportunity for analysis to discover the cause of these problems, but an opportunity that was missed.

Instead of doing a proper analysis, I made assumptions about the performance drivers that were present: Inexperienced students were making mistakes, losing things, or abusing equipment because they lacked the skills or knowledge to do otherwise. In addition, instead of implementing solutions to address skills and knowledge–the only driver I had even considered–I simply made repairs after accidents and moved on with my day, thereby treating each problem as an anomaly instead of mounting evidence of a flawed system.

A greater effort toward analysis would have provided system-wide solutions, instead of hodgepodge quick fixes that involved emergency micromanagement of every new contingency; in other words, a proper solution system should have been the goal. Rossett (1999) defines solution systems as “integrated, cross-functional approaches to solving problems and realizing opportunities…tailored to the situation and coordinated across the organization.” It would be appropriate to place crosshairs squarely on the phrase “coordinated across the organization.” Any analysis that did not address the entire organization, including myself, my superiors, and the students who used the lab, would be woefully inadequate for providing a solution at all levels across the organization.

Analysis Fixer
Given a time machine and the ability to travel back and advise the Matthew Wilson of 2003, I would advocate for the interventions I will now describe. For the sake of brevity, I will use the most common problem I was faced with at the time–developing chemicals not performing their duties–as an example of solutions of which could be extended to all other common equipment malfunctions.

In this case, the ineffectiveness of developer could be caused by students accidentally reusing spent developer instead of disposing of it or accidentally mixing other chemicals with fresh developer, or even improper weekly mixing of new developer by the managing technician (myself). Through analysis, I would have been able to pinpoint which of these scenarios was at fault, and construct a solution to that problem.

This analysis would likely be twofold. First would be a simple review of the recipe for making developer properly, and comparing that to the procedures I followed on a weekly basis. The results of this analysis would promote buy-in from my superiors on a systematic level; if the solution was not a simple matter of correcting my chemical concoction, then a broader solution system would be needed to address the performance of the lab users.

That solution system would begin with consultation of lab users, to assess their knowledge of proper procedures, any equipment issues they encountered that could indicate environmental drivers, and a review of their attitudes toward the importance of pristine chemicals to assess motivation. A simple five- to seven-question survey would suffice to address major concerns.

Using the updated Behavior Engineering Model (Chevalier, 2003), I have compiled what I recall about potential drivers, and what would need to be determined through further analysis, which is presented in red:

Environment Information

Do they have the guides or performance management systems to assist their performance?

No. Chemical containers were labeled, but there were no procedural job aids available for lab users.


Are the materials and tools needed present?

Likely. The lab was well stocked with proper equipment, but further analysis would be needed for certainty.


Are incentives and rewards present?

Yes. They wanted the ability to print properly exposed and processed images, which is enabled by the presence of proper photo chemicals.

Individual Skills or Knowledge

Do they have the knowledge required for desired performance?

Unknown. Further analysis would reveal their understanding of proper procedures.


Do they have the capacity to learn and perform the task?

Yes. They were well-educated college students, and these are relatively simple procedural


Are they motivated to proper performance?

Unknown. Further analysis would determine their value of the importance of pristine chemicals for optimal photo production.

Developing Solutions
Based on this compilation, I have eliminated the categories Capacity and Incentives as causes of the performance gap. Assuming each of the remaining categories potentially contributed, I will now lay out potential solutions for each:

The absence of performance support might be the most glaring omission in this scenario. Procedures for proper chemical use and disposal should have been printed, laminated, and attached to every developing canister and every communal chemical container (and other procedures and checklists should have been attached to other equipment like enlargers and timers). This simple inclusion could prevent a performance gap even in the absence of broader skills or knowledge, and, in the presence of improved knowledge, would enhance transfer.

Skills or Knowledge:
Users of the lab received basic lab training, but that training was conducted by a photography instructor who often taught at the lab, and neither myself nor my supervisor were included in devising this training. This lack of communication created what Rummler and Brache (1995) describe as “silos.” According to Rummler and Brache, these silos act as “tall, thick, windowless structures” built around different pieces of the organizations that “usually prevent interdepartmental issues from being resolved between peers at low and middle levels.” As a result of this organizational disconnect, I am still unaware if chemical concerns were addressed in that training session or to what extent. Analysis would shed light on this, but, regardless of the outcome, eliminating that communication gap and allowing all vested parties to contribute to the goals of that training would preempt future issues.

If the performance gap stemmed from a simple equipment deficiency, this would be easily uncovered through the consultation with users’ phase of analysis, and simply addressed through the replacement of inadequate equipment.

Motivation, if determined by analysis to be a significant driver, would be addressed through improved training and performance support; and increased understanding of how improper chemical management diminishes the quality of users’ film and images would provide users with insight as to the value of proper performance.

Chevalier, R. (2003). Updating the behavior engineering model. Performance Improvement, 42(5), 8-14.

Rossett, A. (1999). First things fast: A handbook for performance analysis. San Francisco: Jossey-Bass.

Rummler, G., & Rache, A. P. (1995). Improving performance: How to manage the white space in the organization chart. San Francisco: Jossey-Bass.

About the Author
Matthew Wilson is a graduate student in the Department of Educational Technology at San Diego State University. He is currently employed by the San Diego Zoo; and, upon completion of his degree, he hopes to continue to serve the field of wildlife conservation in an instructional design or similar educational capacity. He may be reached at

This work was done in partial fulfillment of requirements for Allison Rossett’s performance technology class at SDSU.