Technology

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Nov 27, 2019

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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Nov 13, 2019

ERPs and Supply Chains

The ERP (Enterprise Resource Planning) is a misnomer, as it should have been ERM (Enterprise Resource Management). ERPs became prevalent back in the 80's to operate supply chains and remain the 'transactional core' of most larger companies. However, ERPs are now undergoing deep changes to cope with newer supply chain practices as well as newer IT practices that have emerged during the last two decades.

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Aug 7, 2019

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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Jun 18, 2019

A Domain Specific Language (DSL) for Supply Chain

Supply chains are so complex that regular configuration-driven software can't accomodate the sheer diversity of situations faced by practitioners. These limitations apply to inventory control problems as well as demand forecasting situations. Domain-specific languages (DSL) provide an answer to this class of problems.

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Jun 5, 2019

Digital Transformation in Supply Chain

The performance of a Supply Chain Management (SCM) practice is increasingly dependent on software technologies. The concept of digital transformation covers the complex process associated with the roll-out of a software technology into a large organization.In this episode of LokadTV we are joined by the Global Head of Terra Numerata at Roland Berger, Axelle Lemaire.

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Apr 17, 2019

Differentiable Programming in Supply Chain (Part 2/3)

Yann LeCun, the director of AI research at Facebook, argues that ‘Deep Learning’ has out-lived its usefulness and has coined Differentiable Programming as a fresh machine learning perspective. In particular, this perspective proves itself of prime relevance to address supply chain challenges.

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Mar 13, 2019

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.

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Mar 6, 2019

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'.

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Feb 6, 2019

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.

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Jan 16, 2019

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.

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