Alation Case Studies Transforming Data Complexity into Business Value: A Case Study on FLSmidth

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	Transforming Data Complexity into Business Value: A Case Study on FLSmidth Alation

Transforming Data Complexity into Business Value: A Case Study on FLSmidth

Alation

Technology Category	Analytics & Modeling - Machine Learning Analytics & Modeling - Predictive Analytics
Applicable Industries	Cement Finance & Insurance
Applicable Functions	Procurement Sales & Marketing
Use Cases	Inventory Management Time Sensitive Networking
Challenge	FLSmidth, a multinational engineering company based in Denmark, faced significant challenges in managing its data assets due to its size, history, and the complexity of its data environment. The company, with nearly 12,000 employees worldwide, has been growing for over 130 years, with numerous acquisitions adding to its data complexity. Each acquisition brought in new systems and data assets, which were not readily available to everyone who might need them. Additionally, valuable tribal knowledge often got lost when employees left the company. These complexities posed significant roadblocks to achieving the company's top-line goals of creating a data-driven enterprise and turning data assets into revenue-generating resources. Read More
About Customer	FLSmidth is a multinational engineering company based in Denmark that provides global cement and mineral industries with factories, machinery, services, and expertise. The company has nearly 12,000 employees worldwide and has been growing for more than 130 years, with numerous acquisitions adding to its size and complexity. FLSmidth not only makes money with plant sales but also with aftermarket parts sales. The company's goal is to become a data-driven enterprise and turn its data assets into revenue-generating resources. Read More
Solution	FLSmidth found a solution in implementing a data catalog. A data catalog helps untangle data complexity by enabling faster data discovery, centralizing documentation on data, and fostering collaboration that leads to greater productivity. However, the challenge was to connect the data catalog to tangible business value. FLSmidth did this by finding concrete use cases that demonstrated how the data catalog could improve the bottom line. For instance, they used predictive analytics to identify when a part would fail 90-days beforehand and proactively inform the customer when they should order the part to minimize negative impact. Another use case was improving their ability to sell products by identifying and stocking parts that were needed more often. After an extensive search, FLSmidth chose Alation’s Data Catalog for its collaborative approach and machine learning capabilities. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Machine Learning

Analytics & Modeling - Predictive Analytics

Applicable Industries

Cement

Finance & Insurance

Applicable Functions

Procurement

Sales & Marketing

Use Cases

Inventory Management

Time Sensitive Networking

Challenge

FLSmidth, a multinational engineering company based in Denmark, faced significant challenges in managing its data assets due to its size, history, and the complexity of its data environment. The company, with nearly 12,000 employees worldwide, has been growing for over 130 years, with numerous acquisitions adding to its data complexity. Each acquisition brought in new systems and data assets, which were not readily available to everyone who might need them. Additionally, valuable tribal knowledge often got lost when employees left the company. These complexities posed significant roadblocks to achieving the company's top-line goals of creating a data-driven enterprise and turning data assets into revenue-generating resources.

About Customer

FLSmidth is a multinational engineering company based in Denmark that provides global cement and mineral industries with factories, machinery, services, and expertise. The company has nearly 12,000 employees worldwide and has been growing for more than 130 years, with numerous acquisitions adding to its size and complexity. FLSmidth not only makes money with plant sales but also with aftermarket parts sales. The company's goal is to become a data-driven enterprise and turn its data assets into revenue-generating resources.

Solution

FLSmidth found a solution in implementing a data catalog. A data catalog helps untangle data complexity by enabling faster data discovery, centralizing documentation on data, and fostering collaboration that leads to greater productivity. However, the challenge was to connect the data catalog to tangible business value. FLSmidth did this by finding concrete use cases that demonstrated how the data catalog could improve the bottom line. For instance, they used predictive analytics to identify when a part would fail 90-days beforehand and proactively inform the customer when they should order the part to minimize negative impact. Another use case was improving their ability to sell products by identifying and stocking parts that were needed more often. After an extensive search, FLSmidth chose Alation’s Data Catalog for its collaborative approach and machine learning capabilities.

Impact #1	The implementation of Alation’s Data Catalog transformed FLSmidth's data management operations. The data catalog enabled faster data discovery, centralized documentation on data, and fostered collaboration, leading to greater productivity. It also helped the company to leverage predictive analytics effectively, improving customer service by proactively informing customers about potential part failures. Furthermore, the data catalog improved FLSmidth's ability to sell products by identifying and stocking parts that were needed more often. The data catalog also increased the trust in their data, enabling them to make business-critical calculations on trusted data. Overall, the data catalog helped FLSmidth to connect its data management to tangible business value, thereby making a clear business case for its implementation.

Impact #1

The implementation of Alation’s Data Catalog transformed FLSmidth's data management operations. The data catalog enabled faster data discovery, centralized documentation on data, and fostered collaboration, leading to greater productivity. It also helped the company to leverage predictive analytics effectively, improving customer service by proactively informing customers about potential part failures. Furthermore, the data catalog improved FLSmidth's ability to sell products by identifying and stocking parts that were needed more often. The data catalog also increased the trust in their data, enabling them to make business-critical calculations on trusted data. Overall, the data catalog helped FLSmidth to connect its data management to tangible business value, thereby making a clear business case for its implementation.

Benefit #1	Predictive analytics enabled by the data catalog allowed FLSmidth to identify when a part would fail 90-days beforehand, reducing downtime and potential loss of sales.
Benefit #2	By identifying and stocking parts that were needed more often, FLSmidth was able to increase its sales by up to 4%.
Benefit #3	Despite only being able to create calculations on 60% of their transactions initially, the implementation of a data catalog increased the trust in their data, enabling them to make business-critical calculations on trusted data.

Benefit #1

Predictive analytics enabled by the data catalog allowed FLSmidth to identify when a part would fail 90-days beforehand, reducing downtime and potential loss of sales.

Benefit #2

By identifying and stocking parts that were needed more often, FLSmidth was able to increase its sales by up to 4%.

Benefit #3

Despite only being able to create calculations on 60% of their transactions initially, the implementation of a data catalog increased the trust in their data, enabling them to make business-critical calculations on trusted data.

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Overview

Transforming Data Complexity into Business Value: A Case Study on FLSmidth

Operational Impact

Quantitative Benefit