By Zainab Fazal, M.ADS, BCBA
bSci21 Contributing Writer
Sunny California, a beautiful city and home to “Silicon Valley” is where thousands of new and innovative companies are starting up every year. It is the leading hub, and a startup ecosystem for thousands of high-tech ideas, and accounts for millions in venture capital investments in the United States. When I was first approached to consult to a startup from Silicon Valley, I was excited to use my skills as a behaviour analyst, I just had no idea where to start or how to use them, because that world, and my world (you know, good ol’ behaviour analysis) seemed miles apart in theory and practice.
The startup company was chosen by Y Combinator and moved to Silicon Valley to be a part of their program. They were looking to make better what was already there, and to introduce effective practices that would positively affect their bottom line. After our first meeting, I was asked to help with their client relations department, agent training & overall performance management. As I learned more about the company and its people, I took a step back and thought about how different the tech world from sunny California is, and started wondering how I would disseminate the science I love in this fast-paced world.
Staying true to the science of behaviour analysis, I started recording data – on everything! I didn’t know what information I would need in my analysis or the data I would use, or how, I just knew I needed data to do what I needed to do. I gathered loads of it, did the analysis, put some recommendations on paper and was ready to present it. I was thrilled. I was excited to share my analysis. And then, the CEO of the company said “we don’t have time for processes and systems, and all that training for our agents, we have to just create and do, and do it fast.” That was difficult for me at first, I thought to myself, “but I need to put these systems in place, and then record more data to measure effectiveness, and I need time to do all of that. That’s what I do.” Needless to say, he wasn’t having it!
So I took yet another step back, and thought there has to be a way to make the science that I practice to work in the fast lane. I was not about to let go of data driven decisions, but was prepared to modify my practices to meet their needs.
So I went back to the basics, to what the man himself, Mr. B.F. Skinner, taught us, and delivered what they wanted, but faster.
My first target goal was to help shape desired behaviours of the company’s agents. The differences among all the agents varied greatly, and could not be readily changed, for example, their educational level and experience. As behaviourists, we do not ignore or contend that personal differences do not exist, but we recognize that many of these cannot be easily changed. What we can change is the environment and contingencies, which effectively (we have data to back this up!) changes the behaviours of humans. So that’s what I set out to do for the staff.
Keeping in mind Mr. Skinner’s work on operant conditioning, I looked at using the most prevalent intervention, positive reinforcement. I then explored the schedules of reinforcement to further shape their behaviours (look out for part 2 where I share more about this).
In the initial stages of my analysis, (which can be applied to all work environments), I gathered data and developed strategies using these steps:
- Analyze the current situation to identify the conditions responsible for maintaining the problems.
- Specify the desired performance and define the appropriate behaviours.
- Teach the appropriate behaviours.
- Measure their performance (i.e.,behaviours).
- Providing appropriate consequences based on performance (we used positive reinforcement).
- Evaluate effectiveness.
In the end, I didn’t have to change a lot about my practice, I stuck to the science of behaviour analysis, and it worked – like it always does. I learned, however, that it was not about presenting fancy strategies that seemed like a lot of work and long-term. It was about giving them realistic strategies that could be implemented immediately. It was about creating innovative and easy data collection systems that would provide maximum information. It was about practicing the science, just a whole lot faster!
In part 2 of my ventures in Silicon Valley, I share how we further shaped the agents’ performance through effective training strategies, and the creative use of reinforcement schedules. Stay tuned!
[Originally published on Bsci21.org]