In the light of increasing volatility, a more challenging planning environment as well as ongoing cost pressure, scenario calculations are gaining in importance in today’s logistics and supply chain management. Powerful software solutions help companies in the process industry prepare optimally for future developments and at the same time realise saving potentials.
Dr. Tobias Gerken, Michaela Schneider
Volatility has always been a challenge in logistics and supply chain management, but in the past two years the swings in the economy have reached unprecedented dimensions. The oil price climbed to an all-time high before collapsing just as dramatically. Capacity utilisation and production showed a double-digit variation within a few months and producer prices fluctuated widely.
Increasing volatility causes uncertainty and presents particular problems for managers in strategic logistics and supply chain management. What should my future lo-gistics and production network look like? Which capacities do I need at the different links of my supply chain, for example at production sites or warehouses? And what could be an optimal product allocation?
In the light of complex planning tasks, lim-ited possibilities for forecasting and constant cost pressure, scenario calculations and simulations are gaining in importance. They enable companies to increase transparency in their supply chains, formulate plans and activities for different development situations and build a robust supply chain that takes account of business related risks. A comparison of different supply chain scenarios furthermore allows saving potentials to be identified and costs in the value chain significantly reduced.
Without specific software support, however, simulating and optimising business networks is generally impossible. Even small companies have too complex structures and too many restrictions and constraints that have to be considered. Since simple spreadsheet solutions like MS Excel are not able to model such complexity, specialised software for supply chain design and simulation is essential.
Realistic solutions in demand
Leading solutions in this field combine simulation and optimisation functionality. The decisive factor when it comes to choosing software is the optimisation technology used. The ORion-PI Value Network Optimisation solution from Axxom Software, for example, works with patented, intelligent optimisation algorithms which allow the efficient and holistic optimisation of supply chain networks. Depending on the task at hand, these specific algorithms determine the optimal product allocation, production sites, distribution strategies or inventory concepts.
Optimisation should be based on an integrated model, so that all relevant parameters can be taken into account and optimised simultaneously. This holistic approach offers many advantages: on the one hand, it is possible to simulate and optimise the network while considering all planning levels – even across complex networks. On the other hand, all processes, dependencies, restrictions and constraints can be modelled and assessed at the same time. Only with a holistic optimisation strategy the full potential can be identified and realised.
When choosing a solution, it is important that it facilitates realistic and easy-to-use modelling, simulation and optimisation of the supply chain. Many systems only envisage restrictions like simple capacity limitations or cost factors such as linear transport, production and logistics costs. However, these restrictions are often insufficient, especially for companies with a variety of product ranges and value added processes. A realistic network model and optimisation also needs to take account of complexity costs and economies of scale. Axxom’s ORion-PI Network Scale Savings is a concept which considers such factors and thus renders the supply chain optimi-sation more realistic and more efficient.
Simulating different scenarios
In addition to the choice of suitable software, the data used as a basis for optimising the network is a crucial success factor. The kick-off meeting and the definition of objectives and proceedings are therefore closely followed in the project agenda by a data-related phase concerned with the generation of the required input. This can often be extracted from existing IT systems. Realistic assumptions can be substituted for any data that is missing.
One important part of this data is information about the network structure: where are my suppliers based, where are my production and distribution sites located, which customers receive which products and where do the branches concerned reside? A second data set includes information and master data about raw materials, intermediates or finished prod-ucts as well as relevant production quantities and commodity flows.
In addition, information about restrictions and constraints needs to be captured. For example, does one location include a hazardous goods warehouse or cold store? Are there any goods that must not be transported together? Finally, suitable cost factors are added to the network: How much does transport between the production and distribution sites cost, and what are the operative costs of the individual sites?
Based on this information, a preliminary scenario – a so-called baseline – is built in the software. It describes the as-is situation of the network and contains all suppliers, locations, products and customers as well as commodity flows between these elements. Experience shows that even this first model can simplify an analysis of the as-is state of the supply chain and provide important insights. Quick gains can often be identified directly. From this point on, different scenarios can be created by varying the input data in a targeted way. These scenarios can be analysed, compared with the initial situation and optimised with the help of the optimisation algorithms.
Choice of software is crucial
Experience from many projects confirms that the software requirements are frequently underestimated. Numerous attempts at modelling and optimising even less complex supply chains using standard solutions either fail or deliver unsatisfactory results. When selecting the software provider, users should therefore check that it offers sufficiently powerful algorithm technology as well as comprehensive project know-how. This is the only way to ensure that suitable optimisation technology is employed. The choice of the right software is crucial for success, as only a solution which matches the specific requirements can fully identify cost drivers and realise significant savings.