Locus Technologies Case Studies Environmental Data Flow Six Sigma Process Improvement Savings Overview

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	Environmental Data Flow Six Sigma Process Improvement Savings Overview Locus Technologies

Environmental Data Flow Six Sigma Process Improvement Savings Overview

Locus Technologies

Technology Category	Analytics & Modeling - Process Analytics Infrastructure as a Service (IaaS) - Cloud Computing
Applicable Industries	National Security & Defense
Services	Cloud Planning, Design & Implementation Services Data Science Services
Challenge	The Environmental Data Flow Six Sigma improvement project was initiated in September 2009, driven by a cost-benefit analysis on data validation conducted earlier that year. The project aimed to improve LANL’s environmental data processing following receipt from the analytical laboratories. The project identified thirty-three process improvements, broken into seven subgroups. However, six of the improvements were never implemented, and two of the seven improvement subgroups did not lead to any cost savings but did lead to more accurate sample planning and increased transparency into the system. Read More
About Customer	The customer in this case study is the Los Alamos National Laboratory (LANL), a multidisciplinary research institution engaged in strategic science on behalf of national security. LANL enhances national security by ensuring the safety and reliability of the U.S. nuclear stockpile, developing technologies to reduce threats from weapons of mass destruction, and solving problems related to energy, environment, infrastructure, health, and global security concerns. Read More
Solution	The solution involved implementing a series of process improvements. These included implementing cloud computing, restructuring the data stewards’ jobs, eliminating redundant data reviews, implementing change control on the system, incorporating google maps, implementing automatic electronic validation (auto-validation) of the analytical data, and mapping the data process. The implementation of cloud-based computing was associated with sixteen individual improvements. The improvements reduced the time to deliver data to clients to 1 day (98% decrease) with an uncertainty of 1 day. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Process Analytics

Infrastructure as a Service (IaaS) - Cloud Computing

Applicable Industries

National Security & Defense

Services

Cloud Planning, Design & Implementation Services

Data Science Services

Challenge

The Environmental Data Flow Six Sigma improvement project was initiated in September 2009, driven by a cost-benefit analysis on data validation conducted earlier that year. The project aimed to improve LANL’s environmental data processing following receipt from the analytical laboratories. The project identified thirty-three process improvements, broken into seven subgroups. However, six of the improvements were never implemented, and two of the seven improvement subgroups did not lead to any cost savings but did lead to more accurate sample planning and increased transparency into the system.

About Customer

The customer in this case study is the Los Alamos National Laboratory (LANL), a multidisciplinary research institution engaged in strategic science on behalf of national security. LANL enhances national security by ensuring the safety and reliability of the U.S. nuclear stockpile, developing technologies to reduce threats from weapons of mass destruction, and solving problems related to energy, environment, infrastructure, health, and global security concerns.

Solution

The solution involved implementing a series of process improvements. These included implementing cloud computing, restructuring the data stewards’ jobs, eliminating redundant data reviews, implementing change control on the system, incorporating google maps, implementing automatic electronic validation (auto-validation) of the analytical data, and mapping the data process. The implementation of cloud-based computing was associated with sixteen individual improvements. The improvements reduced the time to deliver data to clients to 1 day (98% decrease) with an uncertainty of 1 day.

Impact #1	Significant reduction in the length of time required to deliver data to clients.
Impact #2	More accurate sample planning and increased transparency into the system.
Impact #3	Implementation of a Change Control Board that authorizes changes to the database that benefit many customers, are cost effective, and fit within the limited budget allowed for improvements.

Impact #1

Significant reduction in the length of time required to deliver data to clients.

Impact #2

More accurate sample planning and increased transparency into the system.

Impact #3

Implementation of a Change Control Board that authorizes changes to the database that benefit many customers, are cost effective, and fit within the limited budget allowed for improvements.

Benefit #1	Phase 1 Savings - $1,000,000.
Benefit #2	Auto-validation Savings - $2,500,000.
Benefit #3	Cloud Computing Savings - $10,000,000.

Benefit #1

Phase 1 Savings - $1,000,000.

Benefit #2

Auto-validation Savings - $2,500,000.

Benefit #3

Cloud Computing Savings - $10,000,000.

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Overview

Environmental Data Flow Six Sigma Process Improvement Savings Overview

Operational Impact

Quantitative Benefit