Despite prior research on outlier mitigation, our analysis of jobs from the Facebook cluster shows that outliers still occur, especially in small jobs. Small jobs are particularly sensitive to long-running outlier tasks because of their interactive nature. Outlier mitigation strategies rely on comparing different tasks of the same job and launching speculative copies for the slower tasks. However, small jobs execute all their tasks simultaneously, thereby not providing sufficient time to observe and compare tasks. Building on the observation that clusters are underutilized, we take speculation to its logical extreme—run full clones of jobs to mitigate the effect of outliers. The heavy-tail distribution of job sizes implies that we can impact most jobs without using much resources. Trace-driven simulations show that average completion time of all the small jobs improves by 47% using cloning, at the cost of just 3% extra resources.