Modelling, Simulation & Optimisation for Supply Chains
SIMCEL is a powerful business decision support tool. It simulates supply chains. And it does it very well.
Whether you are running a shop, a retail chain, a distribution business, a manufacturing plant, a multinational firm, a farm or a ministry, you may have witnessed that important decisions are often based on loose perceptions. Decisions are rarely the outcome of a comparison of solid alternatives, options, and variants. Instead, intuitions and beliefs prevail and the system underperforms, often becoming erratic. Everyone has a different understanding of the same reality, the way "what if" questions are addressed is weak, and assumptions are unclear.
SIMCEL helps to model and simulate the flows of goods in a supply network. From the source to the consumption point, a given product goes through an exhilarating operational adventure that SIMCEL replicates most accurately in the digital world. A pair of sport shoes or a bag of cement, a motorbike spare part or a fresh mango, a pack of fresh milk or a 18-year whiskey bottle, a winter jacket or a dose of vaccine. Thanks to over 10 years of R&D, SIMCEL has become a very powerful decision tool allowing the testing of "what if" scenarios in a fraction of time. Simulating a change in demand or supply would result in a financial, commercial, operational, and environmental impact. Precisely quantified. At any point of time in the future.
What if raw material prices surge?
To what point should we maintain inventory?
What stock turnover would allow an optimum balance between risks and financial performance?
Supply Chain Resilience
Value Chain Transformation
Demand & Supply Planning
Route to Market Strategy
Product Portfolio Rationalisation
Infrastructure, Industrial Policies
Investment Business Case
Industrial and Commercial Merger
Manufacturing Footprint Optimisation
Emission Footprint Reduction
Supply Chain Network Design & Optimisation
SIMCEL IS USED BY
Senior executives to support their business planning S&OP / IBP / FP&A processes with demand & supply scenario simulation (SIMCEL Augmented Business Planning)
Corporate strategy teams to prepare for mergers involving the consolidation of industrial, logistic or commercial assets
Network design teams - corporate or consultants - for optimisation or design purposes by allowing them to test different network configurations, different demand profiles and create advanced business cases.
Industrial property management firms to help their clients to consider different facilities and locations with full understanding of the supply chain benefits and financial impact of each.
Research institutions to study supply chain behaviour under specific conditions, to train and test machine learning algorithms in a virtual environment.
Policy makers that want to precisely quantify the impact of a regulation or an infrastructure investment on certain industry sectors or industrial clusters.
Education organisations to educate on business decision making, supply chain management, logistics, and demand dynamics
What better example than the Covid crisis. What model would have predicted what happened? None. The future will never be predictable, but it can be simulated. With scenario based decisions integrating the end-to-end supply chains, we may not have seen so many shortages of masks, tests, vaccines all over the world, we may not have seen so many company failures, there may not have been so much price volatility in many commodities. It is not about predicting, it is about preparing for what could happen, constantly evaluating trade-offs and thus better reacting when events actually do happen. In that sense the Covid crisis has been a demonstration of the impact of loose, disconnected, local and late decisions.
SIMCEL doesn't predict the future, it helps to anticipate it.
SIMULATION VS. OPTIMISATION?
One optimal result, no context, no capacity to understand the sensitivity orthe behaviour of the system. If the optimum is unrealistic to implement, then no other alternatives are available.
Thanks to multiple simulation experiments, the system behaviour can be explored to identify the optimum as well as more realistic alternatives. Simulation is more appropriate for real life problems and offers a much stronger support to decision-making.
When combined, simulation and optimization provide the most versatile and effective way to answer business questions, whether they are strategic, tactical or operational.
WHAT MAKES SIMCEL UNIQUE?
The beauty is that SIMCEL keeps the finest details of what happens in the demand and supply chain: no average nor aggregation, but a precise model of a reality. Business logics and rules drive simulation experiments so that we can trace and understand the causality behind certain complex behaviours. Every order from every customer, for every product, at every location, generates a cascade of interdependent activities (purchase, movements, transformation, transfer, delivery, storage, etc) for each of which a value and timing is associated dynamically over time. That is what makes a true Supply Chain Digital Twin.
SIMCEL is also extremely fast. It simulates years of business operations in seconds, millions of orders in a blink of an eye. So instead of just getting a figure answering a specific business question, SIMCEL scans a range of possible realities, and computes hundreds of scenarios to map the response profile of the holistic system. What alternative is safest, the most ambitious - and all the points in the middle? What are the limits of what is realistic to expect in terms of performance? How sensitive is the impact of a decision to external market conditions?
The future will never be predictable, but as it can be simulated. We can prepare for it.
SIMCEL & ARTIFICIAL INTELLIGENCE
Because it is precise and fast, SIMCEL helps companies consider Artificial Intelligence applications on a much broader and impactful scale. Generally, to become adequately accurate, Machine Learning models need a large amount of data to learn from. Data that most organisations don't actually have. And even years of clean historical data would not allow the building of a machine intelligence that would be reliable enough to support planning decisions.
However, SIMCEL can compute thousands of scenarios in a few days. Scenarios with different costs, different prices, different demand volume and mix, different supply parameters, different configurations... It explores the edge of what is possible and deepens the understanding of what is likely to happen. These multiple simulation experiments generate data of the same nature you would find in the real world. It becomes possible to create prescriptive algorithms in a few weeks instead of years. It becomes possible to shape the algorithm without being dependent on the quality or availability of data. It becomes possible to dream about Machine Learning as a decision companion for business leaders. We are currently experimenting with what we call "Autonomous Supply Chain" where algorithms will take most of the tactical decisions autonomously to maximise the returns of the entire system with the complete picture "in mind". We believe we are paving the way to a new paradigm in the decision making process where the role of humans will change, more and more leaving the business operations decisions to machines and algorithms.