LTPlabs is a consulting firm that combines Advanced Analytics and AI expertise with a strong business acumen. We’re committed to transforming companies and empower every decision with Analytics.
Question 1 of 2
Answer two questions and put our thinking to work on your challenges
A predictive model and scenario simulator helped a global luxury fashion retailer assess how a different supply chain setup could influence demand and customer lifetime value.
A consumer goods manufacturer used machine learning, a digital twin, and real-time data to optimize powder distribution across seven production lines.
Scenario simulation helped a major metropolitan bus terminal quantify operational capacity, compare bay allocation strategies and assess its ability to accommodate future demand.
An automotive group analyzed dozens of back office processes across multiple teams to identify where AI, intelligent automation, and platform integration could reduce manual workload and improve operational efficiency. The assessment identified potential to reduce workforce up to 31%, with an estimated impact above 1M€.
LTPlabs helped a large industrial manufacturer reduce production planning lead time from up to two weeks to hours by implementing a Mixed Integer Linear Programming optimization solution.
A food manufacturer centralized master data, digitalized and automatized manually-inserted data, and built a reusable foundation for data governance in six weeks.
Gen-AI adds value across the pricing chain, but only when it works alongside strong data, analytical models and human judgement.
LTPlabs helps companies address these issues by designing a master data management ecosystem adapted to their processes, information and users.
Leadership’s role is to set direction, model practical use, support experimentation, and create the conditions to scale what works.
AI can help supply chain organisations close the gap between planning and execution.
AI projects have a stronger chance of creating value when technology, business priorities, organisational capabilities, and adoption are considered together.
Why organizations that start by asking "how do we automate this?" often end up frustrated and what to ask instead.
