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.
Our expert content about Data & AI transformation
The great data platform race: Why your AI strategy might be missing the mark
Remember Business Objects? If you do, you might see where I'm going with this. We're heading into a period where Large Language Models (LLMs) capable...
Framework Solutions: Empowering Clients for Seamless AI Governance Compliance
Explore our 4-step framework for building a strong AI governance foundation while ensuring compliance and maximize the benefits of AI for your organization. This is...
Consumer data collection in China: How can brands learn what they need to know?
The most common question people ask Edouard de Mézerac, Artefact APAC CEO, is what kind of data a company or brand can access about consumers...
AI and Competitiveness: Five Predictions for Retail by 2030
Jérôme Petit, Managing Partner & Global lead Retail at Artefact, examines the uses of AI to see how it will serve retail by the year...
Generating impact with AI: The human qualities that can make it work better
Despite general agreement that AI will transform most industries in the coming decades, a recent BCG survey of 2,700 companies revealed that only 11% have...
AI in Singapore and China: Opportunities and challenges for multinationals
In a recent weekly video update, Edouard de Mézerac, Artefact APAC CEO, reported that Singapore's Deputy Prime Minister announced “a substantial investment of one billion...
Demystifying digital twins: What they are and how your business can benefit
Discover the value of creating digital twins for each sector, bringing increased productivity, reduced time-to-market, and improved customer satisfaction.
Unveiling the Future of Consumer Engagement: Key Insights from Artefact’s latest breakfast event – “Trailblazing Consumer Engagement with Data, AI, and GenAI”
On 26th April 2024, Artefact Singapore and our Tech Partner, Treasure Data, a leading solutions provider of Customer Data Platform, held a panel discussion where...
The AI ACT: The Importance of Regulatory Compliance – and what’s at stake for Businesses of every type and size
Nathalie Beslay, CEO and co-founder of Naaia, met with Caroline Goulard, journalist and CEO of data visualization companies Dataveyes and Modality, to discuss the new...
Keeping the Promise of AI: The Role of Ethics in developing Responsible, Unbiased Models
Jean-Marie John-Mathews, PhD, Co-founder and scientific director of Giskard AI, and Caroline Goulard, journalist and CEO of data visualization companies Dataveyes and Modality, discuss the...
How can we reinvent the acculturation of data governance projects?
Data governance has become a critical issue for organizations seeking to unlock the full potential of their data. Artefact brought together industry leaders to explore...
Navigating the data governance landscape: Decoding AI governance
As interest in and integration of AI solutions surges, there is a pressing need for businesses to embark on initiatives that ensure the proper governance...
Social housing trends in 2024: leveraging data to improve resident journeys
As advanced data use cases and AI applications increasingly influence how corporations make decisions, we look at what trends are likely to impact the UK...
Where to care: deploying data science to find optimal care home locations
Advanced data science solutions - combined with experienced land agents - increase the likelihood of acquiring high occupancy care home sites.
How Generative AI reinvents data sharing for more personalized, secure marketing
Combining data exchange with generative AI enables banks to manage data more efficiently. This synergy promotes more personalized banking experiences while meeting the trust, legality...
Safeguarding data privacy in a GenAI-driven future
Learn how incorporating Privacy by Design (PbD) principles into GenAI solutions is essential for data privacy.
The role of data and AI in empowering climate action
At the "AI for Climate" networking event held on December 6, 2023, at COP28 in the UAE, Artefact brought together a diverse audience. The event...
Making the most of limited data with AI and modelling
Learn how to leverage a limited amount of first-party data with AI and modelling.
Artefact survey on the impact of generative AI
The data & AI consultancy reveals the impact of AI on business productivity in a new white paper. Read the article in french on Challenge.
Why you should enhance your consumer centric use-cases with conversational data
With the advent of generative AI and tools like chatbots, the volume of conversational data is poised to skyrocket. Already a...
Decentralised Data Governance – The Vanguard of Innovation
In today's digital age, the antiquated idea of centralised data governance is obsolete. Decentralised Data Governance offers agility...
Stress in the NHS: why the UK pharmacy industry needs to embrace data
In the first blog of our series, we explore what the current state of the NHS means for the pharmacy industry...
An expert’s view of data governance
Our Consulting Director Benelux Ties Carbo, recently discovered that Funnel's views on data governance needed some extra polishing and clarification. In an interview with Funnel...
Six weeks to define a data strategy: How Artefact helped a wellness tech leader articulate and align with a company’s data vision.
In the data world, the concept of "data for data's sake" is meaningless. At Artefact, our philosophy has always been that data strategy...
