What The iPhone Maker Can Learn From Analytics
iPhone 5s is out of stock around the world! There is a back-order of at-least two weeks in most places in India and US. What an overwhelming response to a great product! But what a lousy fact that a great product will not reach everybody who yearns for it because some people will just not be able to wait for that long to have one in their hands!
Stock-outs are the bane of any retail business – they are costly and they result in long-term losses – consumers shift to competition when their needs are not met in today’s fast paced world. Companies around the world are spending unprecedented amounts of money to find ways to prevent stock-outs and ensure that they can serve what consumers want, at the time when they want it! But it is more easily said than done!
For example, a typical apparel retailer stocks thousands (some even stock millions) of different SKUs; additionally consumer demand, driven by fashion trends, can be very difficult to predict – especially for new launches and sales during holiday seasons. While stock-outs result in loss of valuable profits, too much stock has an inventory cost that can again reduce profits substantially. Science of data analytics is now showing a ray of hope to bring simplification to such complex business problems, taking decision making from a rudimentary gut-feeling based to a much smarter fact-based.
Most retail companies today operate in the master franchisee model where another company becomes the master franchisee and manages the operations of the different stores of the brand. In such cases, it is important to understand the difference between what the brand company sells to its master franchise stores and what the stores in-turn sell to the consumer. This metric is where the insights are hidden. Business Analytics organization helps companies track, understand and action this metric to optimally manage stocks and avoid costly stock-out or over-stock situations.
As a specialized retail and CPG analytics firm, we have been helping clients companies like Nike, Amway, Avon and Payback, among others solve these type of problems, including helping them manage their inventory levels across hundreds of retail outlets. in the process, we have uncovered some interesting insights in our analytics work that were not so obvious to managers based on gut feeling. For example, we helped a sports retailer generate insights from their sales data during the IPL season in India; this enables them to customize their promotional offers by specific geographies by telling them in which cities is the cricket fever at a higher level to justify lesser promotional investment!
I believe, perhaps the Indian Railways should engage in sophisticated data analytics based insights creation to ensure that next time a traveller wants to book at train ticket, they don’t have to plan 8 weeks in advance! And the same may apply to Apple; when they launch iPhone 6! After all, out of stock, is out of business! -
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