Maintaining an equilibrium in stock levels is not an easy game. Purchase too little, and you’ll hit the stockout, leaving money on the table and customers unsatisfied. Purchase a bit too much, and you have inventory occupying space and tied up capital.
As a business, what can you do about it? Can someone tell you in advance when to reorder the items and when is the time to do a discount sale. The answer is — Stock Forecasting Software. It is the solution through which you can meet the customer demands as well as avoid overstocking. The software leverage Ai, data science, and machine learning to understand past sales, supplier lead times, etc and predict the future stock needs.
Why is inventory forecasting so powerful? Well, effectively matching inventory levels to actual demand allows you to:
- Increase your cash flows by buying only when necessary
- Decrease extra expenses for storage
- Ensure clients don’t go elsewhere due to stockouts
- Improve supplier pricing via accurate ordering.
For any business that wants to compete today, inventory forecasting is a must-have. However, it is not enough to just install the program; a deliberate strategy is needed to maximize the profits.
Here are some:
Integrate it with essential business systems
For inventory forecasting to be accurate, it must study data from all your relevant business systems – your online store, POS system, supplier portals, accounting software and more. Choose an inventory forecasting solution that integrates all these diverse sources of information into one view.
Many ecommerce platforms such as Shopify have built-in ai inventory forecasting options or external software capabilities. With ai inventory forecasting Shopify tells you exactly when you need to reorder from the vendor and even manage that itself.
Consider seasonality and trends
Efficient forecasting requires accommodating cyclical demand patterns caused by holidays/seasons and wider market trends. Ensure your inventory forecasting application incorporates these elements through year-over-year analysis rather than mere averages.
To give an example, if you are in the business of selling winter clothes, your tool should be sensitive enough to detect the annual peak in demand around autumn and therefore pre-build inventory. If you see 25% annual growth, it should also take into account this rate when compiling its calculations.
Improve supplier collaboration
While forecasting increases what is coming into your warehouse or store, it is important that you also collaborate with suppliers. Share your forecast outputs with suppliers so that they can plan their production and have sufficient stock to meet your expected demand.
This sort of Collaborative Planning, Forecasting, and Replenishment (CPFR) with suppliers reduces upstream inventory mismanagement that may result in deviations from your forecasts. The entire supply chain is then synchronized.
Track forecast accuracy
No forecast can ever be 100% accurate – there will always be unforeseen incidents that can disrupt demand. You should however keep checking for any changes in your forecasting error rates so as to understand how accurate your predictions were. If the errors are significantly high, adjust things like comparing timeframes or using more sophisticated data modeling approaches.
Embrace the suggestions
Even the most sophisticated inventory forecasting solutions are just advisory tools – they suggest order quantities, reorder points, safety stock levels and all based upon their computations. Then again, it is still your choice to go for those tips.
In addition, a lot of enterprises do not make good use of their forecasting capabilities because they allow manual intervention and overruling to defeat system recommendations. Trust the figures, adjust your buying and stocking policies accordingly.
Implement cycle counting
No matter how advanced your forecasting system is, its recommendations will be undermined by inaccurate data inputs. Cycle counting – an ongoing process of regularly counting portions of your inventory – is crucial for identifying and resolving database discrepancies.
Whenever you identify a disconnect between your digital records and real-world counts, you can dig deeper into that matter and put it straight right away. This makes sure that these forecasts are based on what is truly available in stock.
Use exception management
Another thing to do is leverage the exception management functionality of your forecasting solution. This allows you to predefine tolerance thresholds for understock and overstock conditions and receive automated alerts when projections fall outside those parameters.
In case there is a sudden inventory problem that may lead to an unmanageable situation, exception-based notifications let you respond quickly by finding out why such happened and responding appropriately with any necessary changes in the forecast prior to ordering.
Conclusion
Inventory forecasting software is undeniably a powerful tool for enhancing profitability and optimizing your inventory levels. But maximizing its impact requires embracing the right high-level strategies touched on here. Accurate demand forecasting is both a science and an art – it takes the right technology paired with smart human leadership to achieve the highest benefits.
