Supply Chain 4.0 in consumer goods
Over the last 30 years, supply chain has undergone a tremendous change. What was once a purely operational logistics function that reported to sales or manufacturing and focused on ensuring supply of production lines and delivery to customers has become an independent supply-chain management function that in some companies is already being led by a CSO—a chief supply-chain officer. The focus of the supply-chain management function has shifted to advanced planning processes, such as analytical demand planning or integrated sales and operations planning (S&OP), which have become established business processes in many companies, while operational logistics has often been outsourced to third-party logistics providers. The supply-chain function ensures that operations are well-integrated, from suppliers through to customers, with decisions on cost, inventory, and customer service made from an end-to-end perspective rather than by each function in isolation.
Digitization creates a disruption and requires companies to rethink the way they design their supply chain. At the same time, customer expectations are growing: recent online trends have led to growing service expectations combined with much more detailed orders. Also, a definite trend toward further individualization and customization is driving strong growth of and constant changes in the SKU portfolio. The online-enabled transparency and easy access to a multitude of options regarding where to shop and what to buy drive the competition of supply chains.
Supply-chain planning will benefit tremendously from big data and advanced analytics, as well as from the automation of knowledge work. A few major consumer-goods players are already using predictive analytics in demand planning to analyze hundreds to thousands of internal and external demand-influencing variables (e.g., weather, trends from social networks, sensor data), using machine-learning approaches to model complex relationships and derive an accurate demand plan. Forecasting errors often fall by 30 to 50 percent.
Heavily automated, fully integrated demand and supply planning breaks traditional boundaries between the different planning steps and transforms planning into a flexible, continuous process. Instead of using fixed safety stocks, each replenishment-planning exercise reconsiders the expected demand probability distribution. Consequently, the implicit safety stocks are different with every single reorder. Prices can then be dynamically adapted to optimize profit and minimize inventories at the same time.
In the consumer-goods industry, several of the most prominent global conglomerates are leveraging advanced planning approaches, and a strong interest in broader application can be observed.
Logistics will take a huge step forward through better connectivity, advanced analytics, additive manufacturing, and advanced automation, upending traditional warehousing and inventory-management strategies. Easy-to-use interfaces such as wearables already enable location-based instructions to workers, guiding picking processes. Advanced robotics and exoskeletons could have equally dramatic effects on human productivity in warehouses.
Autonomous and smart vehicles will lead to significant operating-cost reduction in transportation and product handling, while at the same time reducing lead times and environmental costs. Linking warehouses to production loading points may even enable entire processes to be carried out with only minimal manual intervention. Finally, as production facilities start to rely more on 3-D printing, the role of the warehouse may change fundamentally.
Order management is improved through a pair of measures: no-touch order processing integrates the ordering system to the available-to-promise (ATP) process, and real-time replanning enables order-date confirmations through instantaneous, in-memory rebuilding of the production schedule and replenishment needs in consideration of all constraints. The net result is reduced costs (via increased automation), improved reliability (via granular feedback), and better customer experience (via immediate and reliable responses).
The supply-chain cloud forms the next level of collaboration in the supply chain. Supply-chain clouds are joint supply-chain platforms between customers, the company, and suppliers, providing a shared logistics infrastructure or even joint planning solutions. Especially in noncompetitive relationships, partners can decide to tackle supply-chain tasks together to save administrative costs and learn from each other.