Consultancy

The collaboration between CUF and LTPlabs highlights the effectiveness of data analysis and optimization in enhancing stock management efficiency within a healthcare network.

A case study on assessing maturity and defining a strategic roadmap for Data & Analytics in mass-market retail banking.

How a strategic blend of machine learning and meticulous data consolidation techniques revolutionized CRM data integrity.

A venture capital company augmented its deal sourcing process and perform an agile, smart screening of startups.

An analytical approach to improve pharmaceutical retail operations, reducing waiting lines, and improving customer satisfaction.

An analytical-driven approach to employee compensation design aimed at reducing voluntary turnover

By dynamically determining each site’s battery usage, the overall energy costs are reduced while increasing the networks’ protection against electrical power losses.

With the goal of reducing food loss and waste the retailer turn to analytics and partnered with LTP.

The sellout rate increased compared to previous campaigns, without compromising margin targets.

A case study in improving sales forecasting accuracy through analytical planning methods, in a consumer goods company.

Showcasing how a city performance dashboard can boost insights and enhance decision-making.

The optimization tool greatly reduced the effort and time of the strategic planning team when generating new tax and pricing scenarios.

The developed simulation tool allowed testing of different scenarios, plan structures, and indicator weights to quantify the end-to-end costs and gains obtained with the implementation of an incentive plan.

We transformed trade promotions planning by systematizing the activities and enabling access to data to all key accounts, and by leveraging advanced data analytics to achieve superior plans.

Through an optimization-simulation approach we developed a 10-year roadmap for business expansion.

The project fostered the company’s monitoring culture and ensured effective management of its raw materials inventory.

The adopted methodology allowed the planning team to have a complete view of the network and to obtain efficiency gains.

The delivered methodology and simulation tool allow the retailer’s team to quickly iterate on future adjustments, thus understanding the end-to-end impacts of the proposed changes.

Estimate customers’ preferences for product’s attributes to an effective assortment planning decision-making process.

A simulation tool allows to understand the impact of different compensation schemes on the carriers’ yearly operating margins.

By implementing the proposed distribution strategy, opportunities were identified leading to a 7% potential increase in sales volume.

The main goals were to increase store traffic and conversion rates.

How to increase overall competition

The planning team is now able to rapidly respond to demand fluctuations.

The integrated market model tool radically reduced the time of generating scenarios.

The strategic planning team reduced the average lead time of market planning from one week to a matter of hours

Leading organizations are increasingly using advanced analytics to improve their people management practices.

Developing a prediction-prescription engine capable of increasing the sales volume performed by a call center operation.

Building a market model that compile all information sources into reliable historical demand data.

The main goal was to help this FMCG company to schedule its orders optimally, fast, and allow what-if analysis.

The simulator outputs made clear which sectors of the plant were able to accommodate additional volume and which were not.

A comprehensive approach, focused on maximizing the overall efficiency of the factory, while simultaneously assuring the delivery date.

A simulation tool was designed and implemented to draft a prospective budget for each given scenario.

Analytical-driven processes for assortment and space management.

Technological advances have led customers to look for highly flexible, fast and integrated shopping experiences.

We created a recommendation engine capable of identifying the next best offer that maximizes the return of value for each client.

With the overall decrease of stock levels, there was a significant shrinkage and inventory costs reduction.

New policies included the explicit acknowledgment of a dynamic demand variability, the multi-echelon and multi-site nature of the company.

How to minimize transportation and structure costs without jeopardizing customer service level.

The project has ultimately generated a fully customized decision support system.

The new marketing structure resulted in additional visibility over customers’ preferences and the commercial strategy is more aligned with the customers’ needs.

The project demonstrates that digital twins may help to develop risk-free approaches for testing in an agile way, different layouts and scenarios.