EazyStock’s forecasting algorithms enable you to track and understand demand volatility and adjust replenishment parameters as necessary.
There’s always a place for gut feeling and experience, but wouldn’t it be great if data backed that up? We love an Excel spreadsheet as much as the next person. However, if you’re still using Excel for your demand forecasting, it’s time to try demand forecasting software. EazyStock can make your life easier and provide more accurate forecasts that consider seasonality, trends and promotions with less effort – win-win.
Demand forecasting software is the foundation of any good inventory management strategy. Accurate demand forecasts help balance stock levels to prevent excess stock while ensuring you have product availability to keep customers happy and competitors at bay.
The more confident you are in your demand forecasting, the more confident you can be that you’re reaching your full sales potential and not missing out on sales revenue due to stockouts.
Demand forecasting involves more than simply calculating a three-month running average to predict upcoming demand. While your ERP might have inventory management functionality, it will be too simple and lead to inaccurate forecasts and stocking policies.
While EazyStock isn’t a crystal ball, it offers easy-to-use, advanced demand forecasting functionality to deliver accurate forecasts considering seasonality, trends and promotions. EazyStock’s forecasting algorithms enable you to track and understand demand volatility and adjust replenishment parameters as necessary.
You’ll be able to identify customer behaviour trends and respond accordingly to improve service levels and order fulfilment rates without increasing stock investment.
If you’re struggling with forecasting seasonal items, let EazyStock make your life easier! EazyStock automatically identifies and integrates seasonal demand profiles into the demand forecasting process. This ensures you have enough stock to cover peaks in demand, with the peace of mind that as orders decline, your stock levels automatically follow.
The demand for an item changes as it moves through its product life cycle, from growth to maturity and decline. This means that using the same forecasting method or algorithm won’t work. Using a different algorithm for each life-cycle stage is best to get the most out of your historical data and increase forecast accuracy.
If maths isn’t your strong point, and learning multiple algorithms makes you want to hide, EazyStock classifies stock items into different demand types, depending on their life cycle stage and demand profile. This demand type then determines the statistical algorithm used to calculate high-precision forecasts, and EazyStock does the work for you. If you’re already a maths genius, you’ll love talking to us about our powerful algorithms – and we’ll love explaining them to you! For advice on improving your forecast accuracy, we’ve got a handy guide.
How do you accurately forecast demand for a new product without any sales data? You use EazyStock’s supersession and similar item forecasting functionality.
Whether a new item is replacing an existing one or you’re launching a brand-new product, EazyStock creates forecasts based on sales history from existing or similar items at specific points in time. Combine this with your market research, and cross over and under-stocking off your worry list when new products enter the market.
When you’re running campaigns, balancing high stock availability with a low risk of excess stock at the end of the promotion shouldn’t feel like walking a tightrope. With EazyStock, you can refine your demand forecasts and replenishment parameters to match planned promotional activity making promotional forecasts a walk in the park.
Knowledge is power! EazyStock lets you create accurate demand projections considering lead times and potential stock levels. You can share scheduled order dates and quantities with suppliers so they can plan their operations, and, in return, you can negotiate the best price and get a more reliable supply.