Supply Chain science and tech

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Naked Forecasts Considered Harmful

Here at Lokad, our commitment is to deliver the best forecasts that technology can provide. As a result, potential clients often ask if we can provide forecasts alone instead of a full managed solution. In this episode of LokadTV, we explain why these "naked forecasts" invariably introduce a whole host of different problems and how, even with better forecasts, a practitioner usually end up degrading the performance of a supply chain.

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Software Design for Supply Chains

Lean Supply Chain Management (Lean SCM) starts with a lean applicative landscape to support the supply chain. However, 'lean' in software is primarily a matter of architectural choices. Those choices define the class of problems where the chosen software design is a good fit, and where it isn't. Many supply chain problems stem from broken-by-design situations where core design choices conflict with real-world requirements.

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Bad Data in Supply Chain

The proper preparation of data is critical to achieve success with difficult undertakings such as accurate demand forecasting. Bad data is usually the scapegoat of failed supply chain initiatives. Yet bad data usually reflects poorly understood software and processes rather than erroneous data entries.

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Willingness to Pay

Willingness to pay is a basic economic concept that determines the maximum amount an individual is willing to pay for a specific good or service. This can be affected by many factors such as marketing and trends, and can often vary massively from consumer to consumer. While this notion is essential to understand market demand, it is too frequently ignored by supply chain practitioners.

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Pseudo-Science in Supply Chains

Like most complex systems, supply chains are difficult to comprehend. Most naive measurements, such as the forecasting accuracy, only give a partial view of the problem. As a result, during the 90's and 2010's, multiple methods like ABC analysis or safety stocks have persisted while they had neither theoretical grounding nor empirical results to support them.

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A/B Testing, Exploration vs. Exploitation

A/B testing is a method of comparing two options, or more, in order to assess which one yields the best outcome. Unfortunately, A/B testing performs poorly when confronted with supply chain challenges. In this episode of LokadTV, we learn why this type of testing is currently being used in a number of industries and why it has historically been so popular. We learn more about how this approach is profoundly weakened when applied to a supply chain and the complexities that mean that alternative approaches work much better.

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Shadow IT in Supply Chains

The predictive optimization of supply chains relies on data that can usually be found somewhere in the company's existing applicative landscape. However, many of these systems may not be managed by IT as they arose from immediate operational needs that weren't covered by the 'official' systems. Shadow IT is the name given to IT systems that are created within a company without the explicit approval of the management.

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Why SKUs Aren’t That Simple

The Stock Keeping Unit (SKU) refers to a specific product stored in a specific location. SKUs are central in most inventory control sytems. Many inventory methods are geared around the notion of SKUs. However, the SKU perspective is sometimes detrimental to the very problems that the supply chain is trying to address.

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