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Using Statistical Forecasting Techniques To Improve Inventory Planning

Brendan Carbone - Director of Data Analytics for ForecastRx

  • ABOUT Brendan

Leveraging his in-depth knowledge of statistics and mathematics acquired while completing a degree in economics from New York University, Brendan currently works with the ForecastRx team to develop and improve their proprietary predictive analytics platform for inventory planning. Notably, he introduced machine learning forecasting algorithms to the ForecastRx repertoire, which have helped many companies plan and order their inventory much more efficiently and accurately than previously possible.

Before joining ForecastRx, Brendan was part of a small team that started an Amazon private label company that was able to generate seven figures in revenue in just over a year and has continued to grow ever since. While the business did enjoy immediate success, the team realized they had some major obstacles to overcome in order to take the operation to the next level: inventory planning and demand forecasting. Dealing with heavy product seasonality and overseas suppliers with lead times regularly exceeding 80 days, a more advanced approach than typical sales rate forecasting was needed. As a result, ForecastRx was born.


  • Importance of Proper Inventory Planning
  • Some Important Terms/Factors to Consider for Inventory Planning
  • Obstacles to Effective Inventory Planning
  • Common Inventory Planning Methods
  • Tips on Getting the Most Out of Excel
  • Other Forecasting Options


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