Keeping inventories stocked to the right levels can be a tricky balancing act. Too much stock ties up cash and can result in wastage, while too little results in shortages, delayed output and missed revenues. Using techniques like constrained and unconstrained optimisation, statistical inventory analysis and time series analysis, you can keep inventories ideally stocked, freeing up cash without risking shortages.
To keep a business’ inventories stocked to the right levels, not only must you be able to forecast the typical demand for any particular item over time, you must also take into account external factors that may affect demand. For some businesses, this may mean tracking hundreds or thousands of items, each with their own set of factors affecting demand.
Peak’s data machine employs stock analytics techniques to track and model demand based on predictable variations like transaction data, replenishment and inventory policies, as well as external influences. It then forecasts demand to provide accurate product listings, improve efficiencies, reduce inventory costs and minimise disruptions to your business.
The Techie Bit
Our forecasts are built using a variety of methods ranging from simple distribution fitting to sARIMA models, exponential smoothing and Bayesian forecasting methods. We use these forecasts, alongside mixed integer programming, to determine the optimum stocking levels for all of your products at all of your sites.
The insights provided by Peak’s inventory and asset optimisation service not only help to maximise return on capital and revenues, but help businesses to run more smoothly. Our platform also allows you to test different courses of action to see which would be best for your business.