Inside L’Oréal’s Plans to Implement Global Supply Chain Analytics

by   |   July 17, 2013 3:30 pm   |   0 Comments

At L'Oréal headquarters just outside Paris, executives plan to make more precise decisions using a new supply chain analytics system. Photo by Tangopaso via Wikipedia, Creative Commons license.

L’Oréal headquarters just outside Paris. The company plans to share real-time forecasts with suppliers to react more quickly to consumer demand. Photo by Tangopaso via Wikipedia, Creative Commons license.

At cosmetics manufacturer L’Oréal, a pilot implementation of a supply chain collaboration initiative has been given the green light for a global rollout. Sourced from specialist vendor E2open, the introduction of a cloud-based collaboration platform underpinned by an analytics layer will see L’Oréal’s 42 global factories electronically linked to the planning and production systems of thousands of suppliers.

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The goal: real-time sharing of forecasting and planning data, so as to be able to react more quickly to changes in the company’s fast-moving consumer goods marketplace.

“Without contacting suppliers directly to get a view on inventory and production capacity, it can be difficult to get a rapid answer to questions such as ‘Can we increase production of a particular product by X percent?’,” says Richard Markoff, corporate director of supply chain standards and audits at L’Oréal, and the original project sponsor in his previous role as L’Oréal director of manufacturing. “The numbers are just too big: a typical L’Oréal factory might be actively managing over 4,000 packaging and raw material items, sourced from over 250 vendors.”

Just as importantly, the sharing of forecast and planning information will help L’Oréal and its supplier base jointly strip out the excess inventories and excess lead times that currently, in the absence of such shared information, act as a buffer against uncertainty.

Knowing for sure that its suppliers’ plans dovetail with L’Oréal’s own plans, in short, will create leaner and more responsive supply chains—delivering an undoubted boost to the €22 billion company’s bottom line (about $28.9 billion at 1.31 dollars to the Euro on July 17, 2013).

The project to establish global supply chain analytics is a two-phase event. The first phase is arranging systems to collect and organize the data from the thousands of suppliers who share data about their goods and services in varied formats, languages and units. The second phase is putting that data to useful purpose in a supply chain analytics system, to identify opportunities for costs savings and revenue increases.

It’s a set of challenges that is common to supply chain leaders at global brands, where the goal is to wrestle with the complexity of datasets that has grown up over time in an effort to move from understanding not only supply side trends, but also demands from consumers.

North American Kick-Off
Piloted first in North America in September 2012, with a small group of suppliers feeding the company’s North Little Rock, Ark., factory, all six North American plants—stretching from Franklin, N.J. to Redmond, Wash.—are now using the E2open platform in order to exchange demand and production forecast information with at least some suppliers.

Europe is next, says Markoff—and after that, Asia and the rest of the world, where L’Oréal expects to find the one billion new customers that it hopes to capture in the next ten years in fast-growing markets such as China, Brazil, and India. Already, the company’s largest plant in the world is in Indonesia, opened in November 2012 and targeted on producing 500 million products a year for the Asian market.

And after that geographic expansion comes an extension of functionality—a focus on analytics, which Markoff concedes has been left to one side in the push to bring suppliers on board to first build out the data on which analytics can be performed.

For as well as providing collaboration connectivity, E2open offers an analytics layer comprising a data warehouse, pre-written reports and analytics functions designed around multi-enterprise business processes, says Bob Godfrey, E2Open’s European vice president. The system includes a multi-enterprise “intelligence workbench” in the shape of a reporting studio to create custom reports on customer‑specific business metrics from underlying multi‑enterprise business processes.

In other words, says Markoff, not only has E2open developed tools and technologies for many of the various data translation problems that beset collaboration initiatives in practice—differences in language, terminology and data formats—but has also extended that lingua franca into the area of analytics designed to improve multi-enterprise supply chains.

“In Europe, we use commas instead of decimal points,” he says. “As another example, some companies exchange data in units, others in thousands. Such things sound trivial, but across thousands of suppliers they take time and effort to resolve. E2open solved all these problems years ago, offering us a ready-built platform that matched our own vision of what supply chain collaboration could deliver.”

A Different Measure for ROI
That said, the decision push the button on a global rollout was taken in isolation of any metrics that might actually be targeted by such a rollout—an unusual step, concedes Markoff, and one taken very deliberately.

Have lead times reduced? Are inventory levels lower? Are stockouts less frequent? Markoff knows the numbers, but insists they weren’t germane to the decision.

“As project sponsor, I consciously set up project success criteria that weren’t hard metrics,” he explains. “It’s just too easy for supply chain metrics to be confused by events elsewhere—so we deliberately excluded measures such as inventory levels from our evaluation.”

Instead, says Markoff, L’Oréal looked for other signs that supply chains were working more smoothly. Specifically, the company polled planners and other supply chain personnel via attitude surveys, looking for indications that the collaboration platform was making people’s jobs easier and more satisfying to perform.

“Are planners more comfortable in their work? Do they feel more appreciated? How long is it taking them to perform a task? We did the surveys and we probed it intensely—and the results were conclusive,” he reports. “We’ve got very hard metrics, and to us, they’re the metrics which matter.”

Malcolm Wheatley, a freelance writer and contributing editor at Data Informed, is old enough to remember analyzing punched card datasets in batch mode, using SPSS on mainframes. He lives in Devon, England, and can be reached at editor@malcolmwheatley.co.uk.








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