Predictive Maintenance & IoT: The Digital Oracles For CPG Companies
The Consumer Packaged Goods Industry probably reflects the stiffest competition among its companies. With a continuously oversaturated market and lesser profit per unit, factors such as shelf-placement, brand recognition and mass advertising act as major influencers. In such a scenario, predicting the interplay of the market forces of demand and supply accurately has become increasingly important to strategize the right plan of action. Employing tech-based solutions and data analysis in the entire marketing and supply value chain processes helps to identify predictive patterns in the constantly varying quotient of consumer demand. Quite a few leading consumer-goods companies have started to explore the use of digital solutions in manufacturing, supply chain and delivery processes as a performance booster as well. However, most of these firms find themselves stuck at the million-dollar question, where to start from? What processes can be, and more importantly, need to be improved by deploying today's digital technologies?
IoT AND PREDICTIVE MAINTENANCE-Providing comprehensive assistance to CPG companies
Reducing uncertainties over future demand: One of the biggest areas where CPG companies employ predictive intelligence is to identify future market demand. As maintain inventory involves a lot of cost, both at the warehousing as well as the shelf-distribution level, making accurate demand forecasts has s crucial impact on the operating costs of a business. In fact, with the current scenario of tapping into hyperlocal markets, employing predictive analytical tools becomes all the more important as the target audience size is small and low movement of goods can negatively impact customer engagement. By analyzing historical data, CPG firms can save a lot of money and develop better brand value by ensuring there is no over/under production, stock-outs or late deliveries.
Accounting for variances to ensure smooth operations: From periodic maintenance work to analyzing the effect of climatic changes or seasonal festivities on demand, labour supply, cost of raw material etc. predictive maintenance tools can ensure smooth operations and timely allocation of expenditure. Internet-Of-Things has enabled machines to be included in a digitized framework so that any relevant information regarding them can be easily accessed in a centralized manner. Thus, periodic repairs due to wear and tear and machine condition can be easily generated on a real-time basis by the huge data generated by IoT.
Retail optimizations: IoT has significantly transformed the retail landscape by enabling the evolution of an 'Omni-channel' shopping experience, an ideal amalgamation of online and offline retail environments. Users can choose what they want to buy through online web stores, and instead of waiting for products to be delivered, can easily collect their purchase from the nearest store. Furthermore, users can also easily view the entire inventory of a store online. IoT technology can also provide data to optimize store layouts, enable fully automated checkout, and fine-tune store management for customer convenience. Such innovations enable new business models to allow retailers improve productivity, reduce costs, and raise sales.
Innovation in Inventory Management: According to a June 2015 McKinsey report, automating inventory replenishments can bring down inventory carrying costs by up to 10 percent, which could have an impact of $5 billion to $15 billion per year in 2025. From identifying ideal inventory levels to determining ideal storage conditions or using sensors to track inventory dimensions and assigning specific product lots to retail destinations or triggering automatic reordering, IoT and predictive maintenance tools can combine to make the journey of products from warehouses to end-user destinations a cakewalk.
For a long time, CPG companies have relied on calculated guesses made by retail managers and inventory analysts to devise inventory and retail strategies. However, with the advent of IoT and predictive analytics, collecting, maintaining and analyzing data, even at a granular level, has become extremely easy. From tracking via numbers and barcodes to implementing RFID and GPS sensors, micro-level data analysis gained from predictive tools can enable CPG companies to formulate a product cycle blueprint that helps provide superlative quality-control, optimize deliveries and reduce operational costs to enhance profits.
