In today’s fast-paced world, accurate predictions about future trends are crucial for successful businesses, online and offline. Whether forecasting sales, planning purchase orders, or managing inventory levels, having reliable insights into what lies ahead can make or break success. In the realm of data science, one powerful approach is time-series forecasting.

Time-series forecasting involves analyzing historical data points to predict future values based on patterns, trends, and seasonality. While various methods and algorithms are available, one particularly effective approach stands out for its scalability and accuracy.

ForecastRx is transitioning to this new, cutting-edge time-series forecasting technique that offers superior accuracy in identifying seasonality and short- and long-term trends while efficiently handling outliers, missing data, and factoring in holiday sales periods.

  1. Pattern Recognition: Just like ForecastRx’s previous forecasting models, this new forecasting method analyzes up to four years of sales history to identify seasonal trends. Our new forecasting models can delve deeper than just monthly patterns. It can uncover patterns in weekly and daily sales spikes as well as seasonal trends around holidays.
  2. Trend Analysis: Some forecasting models can wrongfully identify coming out of a seasonal period as a downward trend, but ForecastRx layers in long-term trend analysis with seasonality to increase the accuracy of the forecast.
  3. Holidays and Special Events: The new forecasting method recognizes national holidays and special events, such as Prime Day and Black Friday, to accurately predict demand during critical sales periods leading up to the holiday. Being able to train the forecasting models to recognize events is an important advancement because holidays don’t always occur on the same date or day of the week; analyzing year-over-year seasonality may not be enough.
  4. Data Anomalies: Our new forecasting package is robust regarding missing data and outliers. These data points are identified and often discounted from the forecast, enabling you to save time and effort cleaning data from stockouts and one-off promotions, which would normally negatively impact your projections.

https://www.linkedin.com/pulse/time-series-analysis-athul-anish/

ForecastRx’s new forecasting package also utilizes an analyst-in-the-loop approach, which blends statistical forecasts with human judgment to fine-tune the forecasts, so you know the output has been vetted for accuracy.

What looks different:

You will still receive a twelve-month forecast for each item, displayed in our Forecast Report, and your sales history in the Item Card. The display will still look like the same ForecastRx you know and love, with a more precise outcome.

We understand the importance of reliability and precision in forecasting, which is why we’re dedicated to leveraging the latest advancements in data science to bring you the best possible forecasting solution.

To see for yourself, sign up for our free 30-day trial today!