Data & AI for Operations
Demand forecasting and AI-driven supply chain: customized predictive engines to optimise operational processes.
Sell-out forecasting is one of today’s main challenges for most manufacturing companies.
Thanks to our strong technical knowledge of machine learning and advanced AI techniques, we build highly comprehensive and reliable sell-out prediction models able to adapt themselves to market unpredictable effects and industry specifications.
Existing prediction engines have significant limitations due to three main reasons:
1. The complexity of extracting data from most data sources (Excel files such as media plans, PDF reports…)
2. The inability to predict several effects that impact final sales (Social Media, competition…)
3. The incapacity to account for specific industry effects (Global Shoppers effect – Luxury, environmental government initiatives – Car industry…).
We design and deliver concrete actions through an exhaustive framework.
From data management strategy to making sure organizations are GDPR compliant, our team helps and advises executives on how to optimise their data governance to improve their performance.>We believe in creating unique solutions for each of our clients, and we integrate their teams to design a tailor-made and efficient organisation.
Predicting impact of promotions on sell-out
Manufacturers and retailers share the goal of stimulating more shopping trips, so promotional campaigns are often geared towards this mutually beneficial goal. Promotions given by retailers and manufacturers have a complex structure, which includes both monetary and non-monetary components, as well as immediate and long-term effects.
In order to optimize the strategy of promotions (quantity, price, time, product,…) and impact on sell-out, it is necessary to be able to appreciate the value and impact of them.
However promotions have a cost: either the loss of sales for similar products that would have been bought otherwise or the loss of revenue due to the promotion itself. Having a clear and self-learning evaluation of promotions is mandatory to track and optimize the use of it and Artefact is able to build such predictive models to improve promotional decisions.
Pattern and regularity detection
Pattern detection is a fundamental branch of data analysis. It mainly consists of the recognition of patterns and regularities in data to understand specific behaviours.
Identifying an issue inside your supply chain process, detecting frauds operations or exposing suspicious behaviour within a crowd are concrete, high-value use cases. Our Artefact’s methodology is designed to detect this outlier behaviour while avoiding the trap of this scarcity phenomenon.
We make the best use of available raw data (structured data such as operation logs or even images & video recording) before the processing and modelisation steps to expose the desired anomalies.
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