Workforce Management (WFM) Forecast feature plays a crucial role in helping companies predict their capacity plans by providing insights into the expected volume of cases and determining the optimal number of agents required to handle those cases efficiently.

What is Forecast and Capacity Planning:

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In the realm of workforce management, a Forecast refers to the estimation of the number of cases that are anticipated to arrive with a defined future time period. This forecast acts as a key input for companies to plan and allocate their resources effectively, ensuring they have the right workforce in place to meet customer demands. Capacity Planning or Workforce Forecasting, on the other hand, is an approach by which companies predict their employee capacity requirements, the necessary skills that are relevant to department needs and parameters like AHT or targeted SLAs, using historical data to identify trends and patterns in their organization.

How Sprinklr helps Predict Capacity Plans:

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Sprinklr employs a sophisticated forecasting approach, leveraging multiple advanced AI algorithms, like Prophet, ARIMA and SARIMAX, to estimate future case volumes accurately. The utilization of forecasting algorithms ensures a robust and adaptable approach to predicting future case volumes, providing companies with accurate and actionable insights.

Once the forecasted case volumes are determined, Sprinklr utilizes Erlang C and Erlang X algorithms for precise staffing level calculations. These algorithms are specifically designed for workforce management staffing optimization. By leveraging these algorithms, Sprinklr ensures a precise and data-driven approach to determining the staffing levels required to meet the forecasted case volumes, optimizing workforce management and thereby enhancing operational efficiency.

Key Features:

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AI-Driven Forecasting: Sprinklr's proprietary AI incorporates advanced algorithms such as Prophet, ARIMA and SARIMAX to analyze historical data, current trends, and other relevant factors. This results in accurate predictions for future case volumes.

Capacity Planning: The forecast generated by Sprinklr aids in determining the optimal number of agents needed to handle the expected volume of cases. This ensures that companies can allocate resources efficiently, preventing overstaffing or understaffing scenarios by utilizing algorithms like Erlang C and Erlang X.

Real-time Adjustments: Sprinklr's forecasting module's dynamicity allows for real-time adjustments based on evolving conditions. This adaptability ensures that companies can respond effectively to sudden changes in case volumes or other factors influencing workforce requirements.

Optimizing Resource Allocation:

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Data-Driven Decision-Making: Sprinklr's WFM forecast empowers companies to make informed, data-driven decisions regarding staffing levels, ensuring optimal resource allocation.

Improved Efficiency: By accurately predicting capacity needs, companies can enhance operational efficiency, delivering better customer service and meeting service level goals.