The Company

Louis Vuitton is a fashion house and luxury retail company founded in 1854. It sells its world-famous products through standalone stores, store-in- stores in high-end retail stores, and through its e-commerce platform. The company’s North American division operates 130 standalone and store-in-store locations across the United States and Canada. This division operates with one in-house facilities manager who oversees a network of some 90 service providers across various trades.

Our goal was to find a facilities management platform that would remove the burden of resolving all the repair and maintenance issues from our stores and regional managers. This sounds simple but doing it for us was huge.
Alan Donohoe
    Facilities Manager, Louis Vuitton North America

 

The Challenge

Before the company’s ServiceChannel deployment, each individual Louis Vuitton store was responsible for managing and fixing all facilities-related issues as they arose. The responsibility primarily fell on the store manager or the regional manager, who were not facilities management experts by training. This led to managers spending up to 25% of their time and energy on FM issues. Related issues with this legacy model included:

  • Less time to devote to serving customers
  • No standards in place for FM operations, with little to no follow-up on work orders
  • Little understanding on whom to source for particular trades and repair types
  • No analytics and reporting, with zero visibility in key areas such as budgeting and cost containment
Our stores loved the easy access, fast response and the ability for them to get back to customers efficiently and quickly. Having analytics is also huge for us in being able to operate more strategically and proactively, including boosting the speed and quality of our decision making.
Alan Donohoe
    Facilities Manager, Louis Vuitton North America

 

The Solution

Louis Vuitton initiated an RFP (request for proposal) among various FM technology providers including ServiceChannel, which ultimately won the business based on a number of criteria such as ease of use for its stores, superior platform features/functionality, its service provider ‘agnostic’ philosophy, the number of service providers already familiar with ServiceChannel and other factors. Louis Vuitton worked closely with the ServiceChannel Implementation team to deploy a wide range of functionality including:

  • Service Automation, the core work order management platform that significantly reduced the time and effort required to initiate a work order for store managers and employees
  • Analytics Custom, which enabled Louis Vuitton to become far more proactive and strategic in its FM operations by providing valuable data & insights in areas such as spending by location or trade, identifying, frequently recurring issues, and addressing outliers in vendor performance
  • Planned Maintenance Manager, to simplify operations by automating routine work orders such as critical lighting replacement, HVAC maintenance or regular pest control
  • Decision Engine and Proposal Manager, enabling Louis Vuitton to leverage the power of machine learning to evaluate proposals from service providers for faster approvals or to challenge vendors according to established NTE (not to exceed) pricing limits
  • Payment Manager, used to expedite invoice processing and vendor payment, which helped enhance Louis Vuitton’s relationships with its service providers
  • Contractor Scorecard, which gave the store managers and employees a “voice” in ongoing vendor performance management with their feedback of vendors accounting for up to 60% of the total score
  • Compliance Manager, used to track insurance compliance (e.g appropriate amounts) and the company’s required Code of Conduct (required of all technicians coming on-site)

 

The Result

Louis Vuitton can now measure its FM performance according to a number of KPIs (key performance indicators), which provides the company a real-time benchmark to improve its performance continually.

Some notable KPI results to-date include:

  • Increasing vendor on-time check-in rate from an estimated 30% to more than 70%
  • Saving the company’s Finance department 41 working days (annually) worth of time due to the expedited invoicing and payment process
  • Reducing the time store managers and employees spend on FM issues by 96% (from 25% of their daily time to less than 1%)
  • Driving pricing concessions from vendors 25 to 30% of the time on their proposals through the power of machine learning-driven recommendations that are based on analyzing historical data and previous decisions