With the advent of Omnichannel Retail, optimizing inventory and automating the related processes has become imminent. In this regard, one of the biggest challenges today’s Retailers face is how much inventory to hold, in what proportions and for what duration.
The primary reason for the enormity of the challenge is the inability of the systems or the availability of data to forecast the demand. The other challenges include, not having or having an ineffective and partial inventory policy in place apart from insufficient replenishment process.
Demand Forecasting
Therefore, to begin with, let us first address the fundamental question of how to improve demand forecasting?
By definition demand forecasting is the process of estimating and predicting customer demand of products or services by using informal methods such as educated guesses, and quantitative methods, such as the use of historical sales data and takes into account external factors like market trends, seasonal demands, yearly growth rate, economic conditions, upcoming promotions among others.
For a system-based demand forecasting also called as perpetual inventory system, you need to have clean, well classified master data along with sizable historical sales transaction data.
Inventory Policy
Define your inventory policy to determine which products to stock and how much to keep of each unit. The most common method is to sort SKUs based on ABC analysis and the Pareto Rule for Inventory Management, wherein you classify your inventory into A, B and C classes depending on their annual consumption value. The other method which is more dynamic in nature and takes the variability into consideration is the XYZ analysis.
Automated Replenishments
Based on the Safe Stock principle, setting Reorder Level and Order Quantity that gets reflected in the automated actual orders. One needs to include the goods in transit as well applying the replenishment function. The algorithm also needs to consider the lead time, opening hours and holidays to avoid outages at the wrong hour.
Having a specialized inventory management software that addresses the above areas is imminent. Machine Learning is being applied to study the heuristics of the past performance and suggest predictions.
Inventory Management Software Checklist
- Should Track every change in inventory – Receive Goods, Stock Transfer, Sales, Returns, Repairs etc.
- Get accurate count by batch number, expiry date and any attribute like color, size, thickness, date of manufacturing, brand, vendor and batch
- Configure alerts for low inventory, expiry, seasonal demands
- Value inventory @ cost (Weighted average PO, FIFO or standard costing) or at sales price.
- Easy stock take using manual sheets, laptops or PDAs.
- Track quantities on order, on hand, in transit and reserved.
For carrying out most of the tasks mentioned above you need a comprehensive and robust inventory management IT systems.
Posibolt is a leading provider of Retail ERP, Inventory and Point of Sale (POS) solutions across retail formats and variety of Distribution Centers whose customers are spread in 10 countries across Africa, Europe, Middle East and Asia.
For more details visit www.posibolt.com or send in your queries to info@posibolt.com