Some anomalies result from numerous small changes rather than a few large ones. For example, a $1,000 anomaly might comprise 20 different increases of around $50 each across various contributors. In such cases, even the total of the up to 10 root causes we identify could account for only a small percentage of the overall anomaly. For instance, 20 root causes contributing $50 each would total $1,000, but each individual root cause would only explain 5% of the anomaly. When this occurs, examining all identified root causes collectively provides a more complete picture of the distributed nature of the cost increase, though some minor contributors may not be captured within the top 10.