Supply Chain science and tech
BACK TO LOKAD TV ›
Pricing Optimization and Supply Chain Management
Pricing optimization is typically not considered as part of the Supply Chain Management (SCM) practice. Yet, pricing is a factor that strongly influences customer demand. Thus both production capacities and stock levels are highly dependent on prices, and must be jointly optimized.
Data Lakes in Supply Chain
Data lakes are data storage technologies intended for bulk reads and bulk writes. They are particularly well suited to address supply chain challenges, because many situations require an inspection of the company's entire history of orders and stock movements.
POCs (Proofs Of Concept) Don’t Work For Supply Chains
Supply chains are complex systems made of many moving parts: goods, people, machines. POCs (Proofs of Concept) routinely fail when attempting Quantitative Supply Chain initiatives because problems get displaced instead of getting solved.
Why You Should Subscribe to LokadTV
Keep up with the latest changes in the Supply Chain industry.
Terabyte Scalability for Supply Chains
The relevant amount of historical data when considering large supply chains frequently exceeds one terabyte. As a result, inventory control requires two distinct flavors of software: transactional software (e.g. an ERP) to manage the resources, and predictive software (e.g. Lokad) to optimize the resources.
Why Safety Stock Is Unsafe
Safety stocks are an inventory optimization method that enforces an extra quantity of stock beyond the expected demand in order to maintain a target service level. This method relies on key statistical assumptions about the demand forecast, most notably that the error is normally found in the distribution.
Generations of Machine Learning
Machine learning is an umbrella term that includes diverse algorithmic approaches. In supply chain, the historical way of doing machine learning was time-series forecasting. However, this approach has been superseded by a series of superior forecasting approaches.
Why Lead Times Are Nearly Always Underappreciated
The lead time is the total amount of time, typically counted in days, associated with the inventory replenishment cycle. The amount of stocks that a supply chain needs to operate tends to be roughly proportional to its lead times. Accurately estimating future lead times is critical for accurately estimating the amount of inventory needed to fulfill future demand. However, it is a fundamental factor that is often overlooked by companies, with a far greater importance being placed on forecasting.
Service Level vs. Fill Rate
In supply chain, the service level defines the probability of not hitting a stock-out during the next ordering cycle. However, the fill rate defines the fraction of the customer demand that will be properly served. Service levels and fill rates are distinct, and should not be confused.
The Min/Max Inventory Method Doesn’t Work
The Min/Max inventory method defines two stock levels: first, a replenishment threshold, referred to as the 'min', and second, a replenishment target, referred to as the 'max'. Yet, despite its popularity, this method is not suitable for most modern supply chains.
Is Forecasting High Growth Possible?
Growth, and more generally trends, needs to be taken into account in order to deliver accurate demand forecasts. However, growth; as a statistical pattern, proves to be more difficult and more elusive to capture than other well-known patterns such as seasonality.
How To Forecast Seasonality
Seasonality is one of the major cyclical patterns that can be used to improve forecasting accuracy. Most supply chain processes tend to be seasonal to some degree. Not only because of demand, but also lead times.