Finding the best possible balance is called inventory optimization. Over a hundred years' of scientific research has gone into inventory optimization, but very few businesses are fully taking advantage of that work. Even with the digital tools at our disposal in the 21st century, deciding how much inventory of each item to hold is a challenge.
And yet the benefits of inventory optimization are significant:
- Working capital, production capacity and space are freed up, making organisations more agile and resilient
- Shortages are reduced and customer service levels are improved
- Waste, environmental impact and costs are reduced
Our analytical approach is built on the most advanced scientific research on inventory optimization and informed by decades of experience of working with real supply chains in a wide variety of industries. Unlike Artificial Intelligence-driven approaches, we are not mining data looking for patterns. Rather, we use advanced statistical techniques to identify very specific properties of each and every item stocked. Recurrent challenges like data quality, variability and intermittence are fully mitigated in our approach.
There are a number of things that inventory optimization cannot do. Organisations need to define their supply chain strategy and design a supply chain to deliver on that strategy. For supply chain transformations, this is where we start. In this type of exercise, a heuristic approach to inventories is usually sufficient.
At a strategic level, organisations have a balance to find between cost control and resilience. In a globalised economy, failure to take advantage of low-cost sources of supply and failure to target high asset utilisation can make organisations uncompetitive. Yet low cost supply chains may lack the agility and resilience they need to survive volatile, uncertain, complex and ambiguous (VUCA) market conditions. The very interconnectedness of global commerce presents systemic risks both on the demand and the supply side.
Traditional approaches, based on flat and high safety stock buffering, tie up excessive capital and reduce agility. nVentic’s inventory optimization approach allows companies to go much further in right-sizing their inventories, which in itself, combined with a strategically designed supply chain, facilitates the creation of more agility and resilience.
Where the objective is to improve supply chain performance, we start with the granular empirical inventory data itself. This means we can help our clients identify and target areas with the highest potential for improvement up front. Top-down approaches, which target process improvements from a theoretical perspective with the expectation that inventories should be positively affected, take longer and leave too much potential on the table.
nVentic’s granular data-driven approach provides our clients with exceptional insights into not just their inventories but all of the processes which influence, and are influenced by, inventory. Significant inventory improvements can be delivered within the planning process itself, using optimization techniques. Greatly improved supply chain agility and resilience can be achieved by using those same insights to influence key process areas such as procurement, scheduling, forecasting, capacity management, sales and operations planning, network optimization and ultimately supply chain design itself.
Optimization, when applied scientifically, means calculating the best possible option from a set of alternatives. Within inventory management, this comes down to finding the lowest cost option to deliver a given service level. This is at the heart of what nVentic does and our whole approach to supply chain.
The EOQ model is a well-known deterministic optimization model. nVentic uses a variety of advanced optimization techniques
Most organisations are not unfamiliar with inventory optimization tools and techniques, but find it difficult to apply optimization techniques successfully and consistently to the complexity and scale of real life. This is where nVentic comes in: our mission is to help organisations bridge this gap.
The challenges are various and interrelated. Here are some of the most common, along with our approach to dealing with them:
- Few people in any organisation have a good understanding of inventory optimization techniques. Senior management may mistakenly believe it is safer to maintain high inventory levels. Performance metrics and incentives might work against inventory optimization.
- While most organisations have the large volumes of data necessary for optimization, it is not easy to extract and manipulate in a way to derive the necessary insights.
- Optimization is highly sensitive to a variety of input parameters, like lead times, service levels and forecast demand, as well as the distribution of that demand, meaning that optimization software can be difficult to make work in a significant percentage of cases.
- Variability is a key concept for effective inventory optimization approaches and optimization needs to be done item by item, but this can seem excessively labour-intensive. Blanket approaches, such as targeting X weeks’ cover, actively work against inventory optimization and create both excesses and shortages.
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