Large and medium scale companies depend on numbers i.e. the numbers of viewers buying their products and most of the focus in away from individual customer satisfaction. This could be taken advantage of by small independent companies. Out-of-stock situations occur more in case of individual shops due to the lack of planning and application of technology.
Problems and implications:
As a small independent store, they have to face stiff competition from rivals and have to compromise on few things to keep the company going.
1. Due to the less availability of resources, awareness, and skills, customer satisfaction is lacking.
2. Between shipment variances, misplaced products, returns, and stolen goods, retailers often find that the inventory numbers they have on paper (or on screen) often don’t match what they have in their stores. Such discrepancies can lead to merchants mistakenly thinking that they have an item in stock when they don’t, so they end up re-ordering the wrong products or quantities.
3. Manual audits and perpetual inventory measurement of OOS levels are inaccurate, do not focus on the lost sales associated with an OOS item and do not adequately point to solutions. The level of PI inaccuracy in many stores is estimated to be, as PI accuracy (where the PI exactly matched the on-hands) ranged from 32 percent to 45 percent.
4. Most OOS sales losses are due to a relatively small number of items. Few of these items have adequate shelf space relative to their demand. Analysis point that 91 percent of the retailers' SKUs are allocated shelf space based on case pack-out and 86 percent of the inventory on the shelf is in excess of 7 day’s supply.
In the recent times, technology has come to help the world in various problems. The out-of-stock impact could be mitigated and customer satisfaction could be increased by small independent store owners using cost-effective AI and machine learning solutions.
1. Products such as NextOrbit use data sciences driven recommendations to predict and mitigate OOS. They have cost-effective monthly subscriptions depending on the number of SKUs and stores. They don’t require long-term contracts. This would improve the in-stock position.
2. Better out of stock measurement techniques should be implemented such as Instrumenting Store Shelves (“Smart” shelves) that are instrumented to feel the number of products remaining on the shelf. These shelves provide accurate and by the minute understanding of Out of Stock. This allows for action in real-time. An algorithmic analysis of the store could also prove quite helpful in finding out the rate and numbers of out of stocks.
3. Most of the big players focus on satisfying a generalized version of people. AI-based solutions that satisfy individuals during in-store shopping would be more profitable than one online for independent stores. The unique values provided by the products should be highlighted. Machine learning solutions could be provided to make product suggestions to the customers based on few simple questions. This would both save the time of the customer and the effort of the staffs.
4. The location of a brick-mortar store is crucial for its sales. Set up shops where demand is high but stores are less. This way the products that the company produces will have a wider reach.
5. A critical part of any supply chain strategy is being able to preemptively maintain inventory levels. Automatic purchasing will free up employees to concentrate on other important duties which in turn will reduce the number of labors required. Similarly, RFID tags should be used instead of manually checking the product. This way the time spent by customers on queue and shop-lifting could be both curbed.