WFM Commons Newsletter
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Merv P shares a detailed analysis comparing NeuralProphet and Prophet using controlled datasets. WFM professionals can learn how to evaluate forecasting models based on their specific data characteristics, ensuring they choose the right approach for their unique forecasting needs.
Read the full post on LinkedInThe new forecasting module within the Capacity Plan provides accurate volume forecasts and AHT analysis, streamlining capacity planning. Unlike typical methods, it assesses trends, seasonality, and the limitations of historical data to deliver reliable forecasts without unnecessary complexity. WFM professionals will…
Read on LinkedInThis post highlights the importance of accurately forecasting Average Handle Time (AHT) by utilizing a nesting headcount mix of tenured agents. WFM professionals will find value in the Capacity Plan, which simplifies this process without the hassle of validating assumptions.
Read on LinkedInWFM Commons' Capacity Plan uses interval scheduling to provide critical insights into your workforce needs. It highlights staffing inefficiencies, revealing understaffed and overstaffed intervals that traditional headcount metrics miss, ensuring you align agents where they're needed most.
Read on LinkedInIn a recent test, a seasonal naïve forecasting model significantly outperformed six more complex models, achieving an 8.9% MAPE compared to 14.4% for the best complex model. This reveals that WFM teams often select models based on perceived sophistication rather than accuracy. Learn how the right model choice can…
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