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Product Support Data Analytics

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Alternate Definition

Product Support consists of the package of support functions required to field and maintain the readiness and operational capability of covered systems, subsystems, and components, including all functions related to covered system readiness. Data Analytics (DA) refers to the process of examining datasets to draw conclusions about the information they contain. Data analytic techniques enable users to take raw data and uncover patterns to extract valuable insights from it. 

Alternate Definition Source

Product Support - DAU Glossary

Data Analytics - OUSD A&S Data and Analytics Strategic Implementation Plan 

General Information

The 2018 National Defense Authorization Act (NDAA) calls for increased use of data analytics to improve acquisition outcomes and promote collaboration across military Services and agencies internal and external to DoD.  Strategic pathways and goals for data and digital modernization within DoD were originally developed in the 2018 DoD AI Strategy, the 2020 DoD Data Strategy, and other related documents.  The DoD Data, Analytics & Artificial Intelligence Adoption Strategy builds upon and supersedes the 2018 AI Strategy and the 2020 Data Strategy to continue the Department’s digital transformation.

"Big Data Analytics" applications enable analysis of volumes of structured data, plus other forms of data (semi-structured and unstructured) that are often left untapped by conventional business intelligence (BI) and analytics programs. Data mining tools sift through data sets in search of patterns and relationships enabling aggregation, correlation, historical trending, and forensic analysis against the data. Machine learning algorithms can analyze large data sets and perform deep learning, a more advanced offshoot of machine learning to support predictive analytics that forecast behavior and other future developments.

DA is one of six processes in DoD’s Data and Analytics Value Chain to enable improved acquisition outcomes by linking acquisition data to decision makers. DA aids OUSD A&S, OSD Staff, and components in examining and answering questions, reducing cost of analysis, improving reliability of findings, and better informing policy decisions associated with the Adaptive Acquisition Framework (AAF). 

Data Analytics for Product Support provides insights to aid decision makers in managing lifecycle costs, system availability, and support for acquisition programs among others. The Product Support Manager (PSM) Guidebook provides the PSM with the tools needed to develop and implement a comprehensive Product Support Strategy (PSS), as well as procedures for Program Managers, PSMs, and life cycle logisticians to implement the AAF tenets to make data-driven decisions.

Data used for Product Support should come from authoritative sources that, as much as possible, rely on automated data collection. A robust, integrated data environment is a fundamental component in the PSS as the system’s authoritative source of truth.

Tools and Data Repositories.  DoD is increasingly committed to building DA platforms that involve data storage and standardization (data warehouses, data lakes, cloud data) and data tools (R programming, Python, Power BI, and Qlik), all of which are part of an entire DoD pipeline of resources. These resources support analytics and visualization of outputs to improve decision-making quality and speed by providing deeper insights than previously possible with legacy tools and processes. These include but are not limited to examples such as:

  • The Defense Acquisition Visibility Environment (DAVE) provides timely access to accurate, authoritative, and reliable data for acquisition reporting, analysis, insight, and decision-making. DAVE information is available to organizations across OSD and the Military Services to enable data analytics and use of data in decision-making.
  • ADVANA is DoD’s big data analytics platform that supports users at all skill levels across a wide variety of National Defense use cases. ADVANA makes data accessible, understandable, and useful to leaders, commanders, analysts, mission owners, and developers throughout the Defense enterprise to describe, predict, and optimize mission and business performance. 
  • CBM+ provides decision support and analytical capabilities for fielded systems while using diagnostics and prognostics along with automated maintenance information generation and retrieval. CBM+ seeks to improve maintenance performance across a broad range including greater productivity, shorter maintenance cycles, lower costs, increased quality, better availability, and enhanced reliability of materiel resources.
  • Maintenance and Availability Data Warehouse (MADW) contains records from 46 authoritative data systems used by the military services for more than 12 years.

Other authoritative data sources include Navy Visibility and Management of O&S Cost (VAMOSC), Air Force Total Ownership Cost (AFTOC), Army Operating and Support Management Information System (OSMIS), and Component Enterprise Resource Planning (ERP).

The military Services have increased their focus on data and embraced DA in various ways to support their respective needs. See the following articles for relevant content.

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