When Japan's Coca-Cola bottling company wanted to launch a new soft drink, it faced an age-old manufacturing and distribution problem: how many bottles to put on the market and where to bottle and warehouse the product to best meet the demand.
Traditionally, silos were the answer. The marketing, manufacturing, inventory and transportation teams would each take decisions about their areas of responsibility, very often without sharing plans. The end result was stock-outs and piles of unsold products.
Coca-Cola studied its marketing plan and modelled its bottling, warehousing and transportation networks into one solution. When the product took off, Coke came up with almost 100 bottling lines and warehouses.
Today, the bottler plugs in consumer demand on a daily and weekly basis to figure out what product to run, on which lines, and what inventory to transfer between warehouses based on real sales in real markets.
End-users like Coke have been using design and simulation tools to optimise factories, warehouses and transportation departments for years. Supply chain practitioners, however, are learning their limitations. It's great to optimise material handling inside a distribution centre (DC), but how much value do you gain if that DC is in the wrong location?
This is where the new generation of supply chain network design and inventory optimisation applications come into play. These tools allow a supply chain manager to design the optimal network to meet cost and service level requirements; perform what-if scenarios to model various solutions as well as changes to the network as business conditions change; and optimise levels and location of inventory in the supply chain based on constraints like budgets, service requirement levels or profit margins.
Who is using network design? Most of the time, it's companies with tiered distribution networks, global sourcing strategies, or fairly comprehensive manufacturing structures in place. How big are the savings? According to Aberdeen Group (www.aberdeen.com), inventory reductions of 15 to 25 per cent are not unusual.
What's different about this new approach? Traditional supply chain design takes a demand forecast to determine the right location for a facility or the right amount of inventory to go into a warehouse based on priorities like service levels and buffer stock. The focus, however, is on a single location or the processes and amount of inventory inside that location.
The new set of tools understands that a facility doesn't operate in a vacuum but is part of a broader network. They take a holistic view of a supply chain, including inventory in warehouses, inventory at the line, inventory in transit, and inventory at a third-party logistics provider or co-packer facility.
But it's not just figuring out where and how to produce and warehouse a product. Network simulation and design tools can also be used for risk mitigation - simulating what might happen across the network if a plant/warehouse unexpectedly goes offline for several weeks because of a natural disaster - and for determining the carbon footprint associated with a particular supply chain model.
While design and optimisation tools use complex algorithms to work their magic, understanding how they work is basic. When we're talking about network design, we're looking at the structure of the supply chain. We're making strategic and tactical choices about how the supply chain should be run to support a marketing plan and service level agreements at the lowest possible cost. That process begins with a baseline understanding of an existing strategic distribution network.
The system takes information, such as where manufacturing facilities and warehouses are located, where inventory is stored, and what type of transportation channels are in place. The system can also consider variables like the cost of labour, currency exchanges, and the tax consequences of one design over another.
Using that model, the application then runs a series of what-if scenarios to determine how the supply chain performs.
Crunch the numbers, run the what-if scenarios, and the system is able to create a map of what the manufacturing, distribution and transportation network should look like within a region, or across the globe.
Once a supply chain design is in place, the application is used to simulate the network to make decisions on an ongoing basis. Users will take real demand, real orders, and real forecasts with all the variability in the market and make choices.
Inventory planners and controllers also face increased complexity. A major retailer today could face a problem of having many and different stock keeping units. On top of that, they have more than one sales channel with different DCs supplying stores and direct-to-consumer orders.
The answer to this is inventory optimisation. While traditional solutions look at the inventory levels at a specific location, like a parts depot or warehouse, a proper solution looks beyond and optimises inventory positions throughout a network of trading partners.
These solutions begin with a forecast that aggregates the demand from all the various channels along with the availability of inventory across the network. Once this is done, the tool can be used to optimise inventory in a variety of ways.
While companies like Coke in Japan are taking advantage of these new tools to take costs out of their supply chain, the real value is that they allow forward-thinking logistics professionals to use their supply chains strategically to gain a market advantage.