The National Security Private Investment Scorecard

A Practitioner Recommendation for Mobilizing Private Capital
by Wayne Sanders

Business Executives for National Security (BENS) brings practitioner perspectives from the business community to the nation’s most pressing security challenges. Through our Mobilizing Private Capital campaign, we translate that understanding into action.

As the threat environment grows more complex and congressional appropriations remain unpredictable, senior national security leaders are intensifying efforts to attract private investment. The challenge now is helping the broader ecosystem keep pace – ensuring that capital markets, industry, and the federal bureaucracy understand this shift, build the necessary connections, and adapt their practices to accelerate it.

This recommendation comes from Wayne Sanders, Senior Defense Analyst at Bloomberg Intelligence covering weapons systems, emerging technologies, and the defense industrial base. A retired U.S. Army Colonel, Wayne served as one of the Army’s foremost experts in expeditionary cyberspace operations, with extensive experience in intelligence analysis and operational planning. Having spent his career bridging defense operations, advanced technology, and market analysis, he has seen firsthand how the absence of reliable investment data creates blind-spots in policy that undermine efforts to expand the national security industrial base.

---

Establish a National Security Private Investment Scorecard that provides an annual baseline of private capital flows into national security–relevant sectors. The Scorecard would be managed either by an independent steward (such as a Federally Funded Research and Development Center (FFRDC) or a university center operating under federal partnership) or by a federal entity responsible for coordinating private-sector engagement.

The Scorecard would report investment activity by sector, capital-type, geography, and year-over-year trends. It does not replace commercial databases or market research; instead, it provides a shared public baseline with transparent methods and coverage notes. It starts from available data sources and, as partnerships mature, expands to capture a more comprehensive picture of the investment landscape.

---

The Opportunity

With a Scorecard in place, national security stakeholders would no longer have to rely on scattered anecdotes or one-off studies to understand private investment patterns. They would share a recurring, macro-level picture of where capital is flowing, relative to defense-related sectors and priorities. At that level, the Scorecard would function similarly to longstanding statistical series from the Bureau of Labor Statistics (BLS) and the U.S. Census Bureau. Though those are not the only source of insight, they are a neutral backdrop against which arguments are tested. And the Scorecard would complement – rather than compete with – commercial datasets and in-depth market analysis.

Concretely, the Scorecard would estimate aggregate private capital invested each year within its defined coverage – broken out by capital type (e.g., venture capital, growth equity, private equity, private credit, and disclosed mergers and acquisitions), sector (e.g., technology and industrial capacity), and geography (e.g., state, metropolitan statistical area, or equivalent regional rollups). Over time, as data and methods mature, the series could evolve toward more frequent reporting.

Three sets of stakeholders benefit directly from the visibility this Scorecard provides:

• Government policymakers can assess whether capital flows align with stated priorities – a reality check on whether incentives work and where gaps persist.
• Investors can gauge market scale and see where their capital aligns with national security objectives.
• Companies can benchmark investment patterns in their sectors and identify where financing concentrates or remains absent.

The timing is opportune. Federal efforts to mobilize private capital and strengthen the defense industrial base are accelerating. A transparent, methods-led baseline with consistent definitions would enable more effective policy design and capital allocation across government, industry, and investors.

—

The Challenge

Turning the Scorecard from concept into a credible product is feasible, but not straightforward. Five constraints must be carefully managed, which if ignored, would undermine the Scorecard’s analytical value and stakeholder trust.

1. Accessing Private-Market Data

At issue is whether a Scorecard can see enough of the market to produce meaningful estimates.

All segments of the private markets are structurally opaque, but some are more visible in public sources than others. Venture capital activity is more observable through press releases, selected regulatory filings, and voluntary disclosures. Growth equity, buyouts, and private credit – the capital types that finance manufacturing capacity and supply-chain infrastructure – often operate with minimal disclosure. Many transactions never appear in public records.

This asymmetry means the Scorecard will inevitably have better coverage of early-stage technology investments than of the production-scale financings that build resilient industrial capacity. The Scorecard must therefore be explicit about what it captures and where blind spots remain.

2. Defining “National Security–Relevant”

This determines what is in scope. And what is not.

Defense capabilities depend on both end technologies and enabling industrial capacity (manufacturing, materials, logistics, energy systems). The taxonomy must reflect both layers – broad enough to capture real interdependencies, yet focused enough to remain analytically useful.

Defense and commercial technologies increasingly overlap. The semiconductor fabrication facility producing chips for the F-35 fighter aircraft, for example, also serves consumer electronics. The artificial intelligence (AI) talent pool developing autonomous systems works across defense and commercial domains. Cloud infrastructure, advanced manufacturing, and logistics networks all serve dual purposes. Any taxonomy must address where to draw boundaries: when does investment in ostensibly commercial capacity become defense-relevant?

The Scorecard would focus on sector-level and activity-level flows rather than assigning binary “defense” labels to firms. Mixed-use or multi-sector firms would be treated through transparent allocation rules grounded in a combined technology and industrial-capacity taxonomy.

For the technology dimension, it would use the National Science and Technology Council (NSTC) list of Critical and Emerging Technologies as an anchor, while a complementary set of industrial-capacity categories – manufacturing, materials, logistics, energy, and facilities – would capture capital expenditures, mergers and acquisitions, and project-finance activity that enables those technologies to scale. Both layers will require ongoing refinement as technology and supply chains continue to converge.

3. Aggregating Across Sources

The Scorecard must reconcile inputs from numerous sources to prevent inconsistent or duplicative statistics.

Public announcements, regulatory filings, commercial databases, trade associations, and federal program lists all use different definitions. Producing comparable statistics requires data-sharing agreements where appropriate, taxonomy mapping across sources, and documented quality controls. It also requires careful handling of overlapping coverage, potential double counting across sources and rounds, and entity resolution for firms that appear under different names or structures.

4. Protecting Privacy and Competitive Information

Participants must feel confident that sensitive information is protected.

Participants will reasonably expect safeguards. The Scorecard must apply suppression rules, small-n thresholds, and publish only non-attributive aggregates. It will not publish statistics at the individual firm or transaction level. Licensing terms with data providers must be respected in all published tables, and coverage ratios must be reported at a level of aggregation that does not allow reverse-engineering of proprietary datasets.

5. Establishing Methodological Credibility

Users must trust the numbers – and understand their limits – or the Scorecard will not influence decisions.

To be trusted, the product must include a public methods note, a taxonomy crosswalk, coverage notes by capital type, and a revision policy—so users understand its limits as well as its strengths.

Resistance will come from multiple directions, for understandable reasons. Commercial data providers invest significantly in their datasets and may be cautious about efforts that could appear to compete with their business models. Some federal programs may be wary of transparency that reveals whether they catalyze additional private investment. Investors may have concerns about even anonymized reporting creating competitive-intelligence risks. These tensions are real and must be navigated by demonstrating public value while protecting legitimate private interests – not by dismissing concerns or assuming universal cooperation.

A further challenge is governance. Any product that touches on the perceived performance of sectors, geographies, or programs will attract political and bureaucratic scrutiny. Guardrails are required to protect methodological independence and continuity across administrations, even as policy priorities evolve.

These challenges do not argue against building a Scorecard; they simply define the conditions for doing it responsibly.

—

The Path Forward

A pragmatic path is to start with a limited, methods-led product. And expand as data quality and trust improve. Three design choices matter most: how the foundational design work is organized, where the Scorecard ultimately lives, and what it produces in its initial phase.

Build the Foundation and Produce a Macro-Level Product

Establish the taxonomy, scope, and data architecture required for a durable statistical series, while still delivering a macro-level view of investment flows.

Essential design efforts include:

• Taxonomy & Scope: Define a combined technology and industrial-capacity taxonomy, grounded in NSTC Critical & Emerging Technologies for the technology dimension and complementary categories for manufacturing, materials, logistics, energy, and facilities. Clarify what “national security–relevant” means in this context and how mixed-use or multi-sector firms are treated through allocation rules.
• Data Requirements & Source Mapping: Identify the full set of data elements required for the Scorecard (e.g., deal type, sector tags, geography, timing, capital structure), map where those elements reside across public and licensed sources, and assess which can realistically be incorporated in an initial product, versus reserved for future ones.
• Methods & Governance: Specify coverage assumptions, suppression rules, entity-resolution approaches, and a revision policy, along with governance guardrails that protect methodological independence and continuity across federal Administrations.

From the above design, produce an initial product that consists of:

• Sources: Public disclosures and licensed datasets sufficient to produce macro aggregates for totals, sectors, capital types, geographies, and year-over-year trends.
• Methods: A published taxonomy and entity-resolution approach, with coverage notes by capital type and suppression rules. Ensure strict compliance with data-provider licensing.
• Outputs: One annual report, plus downloadable tables. All tables carry coverage ratios – indicating what share of estimated activity is captured from public vs. licensed sources – and plain-English methods notes so users can interpret the statistics as coverage-bounded estimates rather than literal totals.

Organizational Home

A Scorecard needs an institutional home that balances analytical credibility and policy relevance. Two models offer viable paths:

• Independent Steward: An FFRDC or university center operating under federal partnership, supported by an external methods board and annual revision calendar.
• Federal Coordination: A federal entity such as the Department of the Treasury’s Office of Financial Research (OFR) providing secure data infrastructure, standards, and disclosure methodology.

Either model would benefit from an interagency working group – including the Office of Strategic Capital, Office of the Under Secretary of Defense for Research and Engineering (OUSD(R&E)), Office of the Secretary of Defense for Industrial Base Policy (OSD(IBP)), Department of the Treasury, Department of Commerce, Defense Innovation Unit (DIU), Chief Digital and Artificial Intelligence Office (CDAO), and key data partners.

Future Editions

As relationships mature and become more trusted, explore voluntary, anonymized submissions – particularly for private credit and manufacturing-capacity financings – under strict privacy safeguards. Participants would receive benchmarking and early access to aggregated trends. Also, over time, consider limited macro-level indicators of public/private sequencing. Any such indicators must remain non-attributive and carefully contextualized to avoid misinterpretation.

—

Conclusion

Absent a consistent baseline, national security investment discussions remain anchored in anecdotes, incomplete datasets, and isolated studies. This makes it challenging to determine whether capital flows support priority capabilities and even harder to build a shared framework for corrective action.

The National Security Private Investment Scorecard offers a practical way to close that gap: a transparent, recurring view of where capital is flowing, in what approximate magnitudes, and through which channels. By starting with existing data, focusing first on taxonomy, data architecture, and methods, and expanding only as coverage and trust improve, the approach addresses the visibility, scope, privacy, and credibility challenges outlined above.

Done well, the Scorecard becomes part of the shared infrastructure policymakers, investors, and companies use to assess the health of the national security investment ecosystem. It will not answer every question, but it will shift the conversation from anecdotes to a common evidentiary baseline.

---