Supply Chain science and tech
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The Problem With Flowcasting
Flowcasting has been previously described as 'The Holy Grail of demand-driven supply chain planning'. But just what is it exactly? 'Flowcasting the Retail Supply Chain', a book published in 2006, presents a series of techniques that were intended to revolutionize the retail industry. In this episode of LokadTV, we learn a little more about this concept and debate why a technique that was published in 2006 is still of interest today.
Data Security in Supply Chain
Data is both an asset and a liability. Supply chains require extensive historical records for tracability purposes and to ensure the accuracy of demand forecasts. However, data leaks are damaging events both for the company and its clients. Supply chains have to protect both their physical and software infrastructures.
Blackboxing and Whiteboxing
Any nontrivial demand forecasting model becomes a black box for supply chain practitioners, that is, an opaque subsystem that produces numbers that are difficult to understand and to challenge. Whiteboxing, as part of the Supply Chain Management practice, is the answer to this problem. Practitioners don't need to understand the 'how' but need to understand the 'why'.
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.
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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.