Use simulation modelling for demand planning The American multinational General Electric (GE) first chose to use demand planning after it opened a giant battery manufacturing plant in 2012. The Durathon battery production had over 27,000 variables. This meant that GE had a lot of data. GE wanted 20-20 visibility to make real-time operational decisions, such as: do I need an additional operator in the next eight hours?. This is where simulation modelling paid off, allowing GE to run what-if? scenarios and optimise the results whenever they needed. For GE, it was mission accomplished. They achieved real-time production optimisation by determining a baseline capacity that allowed for some variability. This also incorporated the systems dynamics to identify bottlenecks, plan production ramp-ups and control a gradual expansion of the plant all of which enabled overall improvement of the whole manufacturing system. Use predictive analytics for competitive advantage Since the 1950s, the needs of both the consumer and businesses have grown and diversified and the supply chain engine now needs road-testing for any eventuality. Enter predictive analytics. Demand planning is essential for supply chain management and predictive analytics can help customers to model an efficient business as the industry continues to change and evolve. All businesses with a supply chain spend valuable time making sure it adds value, but new advanced analytic tools make it possible to dig deeper into supply chain data in search of savings and efficiencies. This is important today, as profit margins are being increasing squeezed, due to business competition. Choose the right demand planning tool A yacht manufacturer in Italy needed to simplify is planning process. Yet luxury yachts require a huge amount of time and care because the manufacturing process is complex, and the quality and craftsmanship cannot be sacrificed. Fair Dynamics and DSE Consulting provided a demand planning support tool developed with a hybrid approach. This solution, which combined the simulation of human and automated decision making, provided scheduling, resource, review stage planning alongside production planning data analytics all in a matter of seconds. Ensure your forecast planning is up-to-date For businesses today, the cost of failing to maintain an accurate forecast can be catastrophic financially. In todays market, a company may see benefits in sticking to the traditional model for operational excellence, but in the long-term it could be outperformed by a competitor using simulation modelling to predict demand from thousands of new scenarios. As businesses who are likely to be your competitors - begin to modernise their approach to supply chain management, you must ensure your business modelling and forecasting tools are helping you gain competitive edge. As businesses continue to improve and grow, demand planning has become increasingly important and predictive analytics have become a crucial area of expertise helping customers to model an efficient and cost-effective service and solution in the face of ever-changing demand. SOURCE: Adapted from Supply Chain Digital, 2017 Answer ALL the questions in this section. SECTION B [60 Marks] Answer ANY THREE (3) questions in this section. Question 1.1 (20 Marks) The basic EOQ is one of the oldest and the most often used methods of ordering and controlling inventory. In light of the above case explain EOQ methods in operations management of the supply chain.