A predictive forecasting or scheduling tool analyzes current and historical data, including unstructured data such as text, audio and video, to predict future demand or supply for a product or service, as well as functional and operational metrics. With the rise of artificial intelligence and machine learning, predictive analytics tools are becoming increasingly accurate, leading to improved customer experience with less product shortage. The tools also produce cash and cost savings since the workforce can be right-sized and inventory reduced.

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Customer Experience Tools and Trends

Our insights share how the right CX tools make customers’ lives richer and more fulfilling and strengthen a company’s economics by holding down costs and securing new revenue streams.

How companies use predictive forecasting or scheduling tools

• Demand prediction. Accurately predicting demand optimizes revenues and allows managers to anticipate production volume and stock levels to satisfy customer demand.
• Inventory management. Generating fewer or better predicted outages, maintenance windows or breakdowns, and avoiding product shortage, is critical to improving the customer experience and avoiding lost revenue while also decreasing inventory costs.
• Workforce planning. Anticipating demand helps companies schedule the right staffing levels and train employees to better serve customers.
• Identifying growth drivers. Predictive forecasting allows managers to understand what drives revenue growth so that they can focus investments on the critical levers of growth.

Key considerations

• Assess the reliability of the tool with feedback loops, checking actual results against initial forecasts.
• Input criteria of the tool must be regularly adjusted to improve the tool’s accuracy based on accumulated experience.
• Include not only internal data, but also external data that might affect performance, operations and demand.