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INTRODUCTION AND OBJECTIVES: Robotic surgery has a variable learning curve with multiple factors potentially affecting operative times. We sought to measure the effect of patient, provider, and system-related variables on operative time. METHODS: Retrospective data was collected over a 3.5 year period on 1,099 patients undergoing 11 robotic surgeries by 23 urologists and gynecologists at Cedars-Sinai Medical Center in Los Angeles. Data included patient age, BMI, comorbidities, operative time, surgeon volume, and type of robot (da Vinci Standard vs da Vinci S System). Analyses were performed by linear regression modeling. RESULTS: Average procedure time was 4.87 þ/1.33 hours. Surgeons performed an average of 49 þ/83 surgeries (range 1 to 362, median 1⁄4 8). The upper 25th percentile of surgeons by volume performed 60 or more procedures, and the lower 25th percentile performed four or less. Patients with 25 30) was 0.35 þ/0.08 hours longer vs BMI < 25 (p < 0.001). Diabetes was also associated with increased procedure time, but age and heart disease were not. After performing a subset analysis of surgeons who performed 20 or more surgeries (n 1⁄4 10), the average procedure time for the first 10 surgeries was 4.82 þ/2.83 hours and for the last 10 was 5.03 þ/2.90 hours. The upper (n1⁄45) and lower (n1⁄46) 25th percentile of surgeons had an average procedure time of 5.31 þ/0.74 hours and 4.36 þ/0.77 hours, respectively (p 1⁄4 0.067). After accounting for covariates such as robot type and BMI, high volume surgeons took 0.90 þ/0.44 hours longer than low volume surgeons (p1⁄40.042). The average time for the da Vinci Standard was 4.70 þ/1.12 hours (n1⁄4639 procedures) and for the da Vinci S was 5.10 þ/1.55 hours (n1⁄4493 procedures) (p < 0.001). After accounting for surgeon volume, BMI, department and procedure type, the first generation da Vinci Standard had procedure times 0.35 þ/0.08 hours shorter than the second generation da Vinci S (p < 0.001). CONCLUSIONS: Unexpectedly, surgeon operative times did not tend to improve over time, and operative times were not significantly different between high and low volume surgeons. Also surprisingly operative times were not faster with the newer generation da Vinci model. After overcoming learning curves, surgeons may have an inherent “pace” that dictates their operative time.