In the digital age, data is a currency all on its own. The retail sector has lagged in leveraging the value of real time data, due to a number of factors. However, given the current economic climate, they can no longer afford the luxury of remaining in the dark.
The power of data is revealed through near real-time analytics, and it can deliver incredible benefits for the retail sector.
Harnessing the power of daily sales and stock on hand data is the missing link in enabling Just in Time (JIT) manufacturing – the panacea where manufacturers produce just the right number of goods that are delivered at the right time to the right place to find their way into the hands of the right consumers.
Visibility is the key
The daily sales and stock data in retail holds a powerful repository of information, if it can be further enhanced by getting sales through the tills as each transaction happens this data flow, will provide powerful insight into the daily movement of SKUs, categories and sub-categories, to obtain a live view into what is being sold in real-time.
This will allow the retail chains to finally understand product mixes with high levels of accuracy. Armed with real-time data analytics, they are able to know exactly what is being purchased at what time, and in what combination with other products.
If you can align a loyalty plan to identify and profile the shopper making the transactions then it becomes a game-changer in customer experience strategies and the key to finally truly understanding consumer buying patterns, identifying the effectiveness of promotions, understanding basket combinations and gaining insight into exactly when consumers are purchasing certain products.
Streaming analytics enables JIT manufacturing
With the power of streaming analytics, manufacturers are empowered to understand exactly what products are selling in what volumes, right down to specific flavours or pack sizes and in what retail outlets. With machine learning and advanced analytics, it is possible to build predictive models to start mapping product sales patterns to periods of the month, particular days, etc.
Additional external data such as changing weather patterns, event calendars will also influence sales patterns and if there is enough historic data it is possible to map the influence of the external patterns to predict the expected influence on future events. This is information that can help manufacturers gear production to cater very precisely to consumer demand.
In today’s challenging market, every cent is critical to the bottom line. This granular level of data analytics is no longer a nice to have, but an absolute essential in ensuring that production planning is optimised. It is also critical to empowering purchasers with factual data to ensure they buy and stock what consumers want, when they want it, and to understanding which competitors are picking up the market when stock runs short.
If we consider how the FMCG market is moving, the only way manufacturers will be able to differentiate themselves will be to become extremely efficient and customise their marketing efforts...
Andrew Dawson 28 Jan 2020
Adjusting behaviours on the fly
“Streaming analytics” is the future of real data insight in the retail sector.
The first step is to gain line of sight into the market at a ground level, and then the second phase is to understand what can be done with the data. For partners on the ground, such as merchandisers, store reps and retail specialists, this level of granular data helps to identify challenges such as being under or over stocked versus the expected “days of cover” for that product, or reduced sales versus the category average, all of which make a direct impact to the bottom line.
Data insight is also vital in ensuring that promotions are effective, that operations are competitive, and that any issues can be swiftly identified and promptly dealt with. Deviation tracking, using real-time analytics with artificial intelligence (AI) and machine learning, is the key to tackling these challenges. In the current climate, real-time functionality is critical, as after-the-fact analytics is simply too little, too late.
If ever there was a time for getting real-time data analytics right in the manufacturing and retail sector, it is now. The world is shifting faster than ever, and the future is all but impossible to predict. Harnessing the power of data in real-time is crucial to helping the manufacturing and retail sector survive in a challenging market.