Organizational Issues with Data Sprawl
As organizations grow, they generate and collect more data than they can handle. This presents numerous issues they must address to effectively benefit from these expanding data sets. These issues include difficulty retrieving data, questioning accuracy of internal and external data, and conflicting data undermining decision making.
Difficulty Retrieving Data
Organizations must be able to easily discover and use their data, but when capture methods vary and data are stored independently of one another, retrieving and using the data present becomes difficult.
Questioning Accuracy of Internal & External Data
Similar challenges arise with externally generated data sets. When working with multiple data sets – both internal and external – organizations struggle to determine which source contains the most accurate information. They question what mechanisms exist to correct known errors in externally generated data sets as well.
Conflicting Data Undermining Decision Making
Decision makers need to have real-time data available to base their choices on. Conflicting data within an organization’s infrastructure can cause inefficiencies and undermine desired outcomes during this process. How to ensure the integrity and quality of that data as it makes its way to those decision makers is a critical challenge, requiring continuous efforts to curate and clean data throughout its ingestion, storage, and utilization.
An organization must also effectively control data security and access to maintain a reliable and authoritative source of truth. The U.S Department of Defense (DoD) is acutely aware of these challenges as shown by their Department of Defense Data, Analytics, and Artificial Intelligence Adoption Strategy to address them. Solving these issues is especially crucial when organizations implement Artificial Intelligence (AI) or Machine Learning (ML) initiatives, as the data must be of the highest quality possible and governed properly to yield valuable insights for decision-making.
An organization-wide Enterprise Data Strategy addresses these issues and more to ensure the identification, acquisition, curation, protection, and utilization of ever-increasing amounts of relevant and timely data.
Developing an Enterprise Data Strategy
At EXPANSIA, we leverage our deep understanding of clients’ business and data ecosystems to develop an Enterprise Data Strategy in alignment with the broader DoD data strategy that fits the clients’ unique product lifecycle considerations. Our holistic approach encompasses data governance, infrastructure, analytics, and security to deliver a digital thread.
Defense Acquisition University (DAU) defines digital thread as “an extensible and configurable analytical framework that seamlessly expedites the controlled interplay of technical data, software, information, and knowledge in the digital engineering ecosystem, based on the established requirements, architectures, formats, and rules for building digital models. It is used to inform decision makers throughout a system’s life cycle by providing the capability to access, integrate, and transform data into actionable information.” This digital thread connects stakeholders, systems and processes and ultimately enables data-driven decision-making.
EXPANSIA approaches defining and using digital threads through understanding and defining the core ontology (or attributes and relationships) of the data that exists within a knowledge domain such as aircraft or other platform sustainment. An effective digital thread depends on both the quality of the data and the clarity of the underlying data ontology.
Data Governance
Realizing the digital thread within an Enterprise Data Strategy begins with strong data governance. This requires the adoption or establishment of policies and procedures that ensure data accuracy, consistency, security and compliance. Identifying authoritative data sources and ensuring clean data ingestion with appropriate curation allows EXPANSIA to avoid the pitfalls of unreliable data that lead to poor decision outcomes. The concepts, relationships, and attributes of the curated data are examined against the existing ontology, often redefining that ontology as we discover new relationships and dependencies. These become reusable building blocks suitable across multiple applications.
Infrastructure
Building upon this governance foundation, we then define the systems, tools and technologies required for the digital thread that allow our clients to store, manage and access their data. These form the digital infrastructure that we have previously described as the Integrated Digital Environment. Recall that our preference is to utilize commercially available software to minimize development and maintenance costs, though we do develop custom solutions sparingly when unique client needs arise.
Analytics
Next, EXPANSIA’s cadre of data wizards work shoulder to shoulder with our clients to analyze the elements of the digital thread, using the data to gain insights, identify trends and ultimately make informed decisions. Here, we have found increasing success in the application of artificial intelligence and machine learning techniques including supervised learning algorithms to enable predictive analytics. We are excited to begin applying generative AI and retrieval–augmented generation (RAG) to further harness the creation of new analytic insights for our clients.
Security
Data security and privacy considerations are fully integrated in our data strategy and approach to the digital thread. This goes well beyond basic compliance to the requirements of the DoD’s Risk Management Framework (RMF). We engage EXPANSIA security engineers early and bake in the protections from unauthorized access, use or disclosure that could compromise the confidentiality, integrity, and availability of client data. This allows compliance to RMF requirements to be checked early and continuously (rather than just at the end of implementation) throughout the Continuous Integration/Continuous Deployment (CI/CD) lifecycle of the different components of a digital thread, resulting in less risk over time. More can be said about Development, Security and Operations (DevSecOps) but suffice to say that we leverage automated tools to identify vulnerabilities and ensure continuous improvements to the security posture of our digital thread solutions.
Successfully integrating traditionally siloed tools, processes, and systems requires establishing a robust data strategy and backbone. This enables rapid collaboration, improved decision–making, and process automation, ensuring consistent access to high-quality data across the enterprise. In this way, we are helping customers not just implement a technology stack but to also put in place a strategic approach to data management that underpins an Enterprise Data Strategy.
AGORA's Reusable Data Strategy: Available Now
EXPANSIA is demonstrating our approach to Enterprise Data Strategy development and the implementation of a digital thread through the Always Guaranteeing Operationally Ready Aircraft (AGORA) solution – a collaborative platform developed in partnership with the Air Force Rapid Sustainment Office (RSO) – with the goal of accelerating advanced manufacturing adoption.
Advanced manufacturing (AM) depends heavily on high-quality, well-governed technical data shared among stakeholders across the product lifecycle from development through operations and sustainment. Program offices don’t need to recreate a siloed AM data strategy and can instead utilize the significant investments made by the RSO to develop the governance, infrastructure, analytics and protections that are now available to the enterprise through the use of the AGORA solution.
EXPANSIA engineers are available to aid interested PMOs in the adoption of these enterprise capabilities and to help you uncover your own data insights that may have been previously beyond reach.