Newpark Resources Inc.
3585a717-e375-4d76-88b0-1e8b8aec332c
PRODUCTION_VERIFIED schema v3.0.0 Inferred last heartbeat: 2026-07-21T05:31:33.135158+00:00

Business Model Classification Tokens

contract_cycle_length
null
Inferred
Pending — BM Dev Shop classification run
enterprise_sales_motion
null
Inferred
Pending — BM Dev Shop classification run
procurement_complexity
null
Inferred
Pending — BM Dev Shop classification run
vendor_lock_coefficient
null
Inferred
Pending — BM Dev Shop classification run
consumption_unit_definition
null
Inferred
Pending — BM Dev Shop classification run
usage_billing_granularity
null
Inferred
Pending — BM Dev Shop classification run
overage_penalty_structure
null
Inferred
Pending — BM Dev Shop classification run
minimum_commitment_floor
null
Inferred
Pending — BM Dev Shop classification run
metered_margin_profile
null
Inferred
Pending — BM Dev Shop classification run
bundle_discount_depth
null
Inferred
Pending — BM Dev Shop classification run
cross_sell_attach_rate
null
Inferred
Pending — BM Dev Shop classification run
bundle_churn_vs_single_churn
null
Inferred
Pending — BM Dev Shop classification run
bundle_margin_blended
null
Inferred
Pending — BM Dev Shop classification run
upsell_pathway_architecture
null
Inferred
Pending — BM Dev Shop classification run

Business Model Archetype Classification

University of St. Gallen — 55 Business Model Navigator (Gassmann et al.)

SG-009 Customer Loyalty WHO High
Direct: monetization_vector contains [Product sales (drilling fluids and additives) plus service fees; revenue tied to rig count and well complexity, not subscription or SaaS-type recurring streams]
SG-014
Flat Rate
VALUE High
SG-037
Product as a Service
VALUE High
SG-049
Subscription
VALUE High

Hybrid Combination

Customer Loyalty (SG-009) WHO provides the core structure, combined with Flat Rate (SG-014) + Product as a Service (SG-037) + Subscription (SG-049) to form the complete business model fingerprint.

55 Archetypes Evaluated High: 4 Medium: 7 Registry: schemas/sg55_archetype_registry.yaml

Knowledge Graph — All Sections

debt_leverage_profile
Net debt ~$140M, total debt ~$200M, leverage ratio ~2.5x EBITDA; 20% rate rise adds ~$4M annual interest expense on floating-rate tranches
Inferred
Agent_Inference
interest_rate_sensitivity
Roughly 40% of debt is floating-rate; 20% rate increase (~100bps) compresses pretax income by ~$3-4M, meaningful given thin margins
Inferred
Agent_Inference
geopolitical_supply_exposure
High intensity; OPEC+ supply decisions and Russia-Ukraine conflict drive price volatility.
Medium
GICS-commodity-overlay-v1
supply_chain_dependency
Barite sourcing from China (dominant global supplier) and bentonite from Gulf Coast/Turkey; both subject to export controls and geopolitical disruption
Inferred
Agent_Inference
international_expansion_readiness
Top international markets—Middle East, West Africa, Latin America—carry elevated FX risk; NOC-driven payment delays amplify devaluation exposure
Inferred
Agent_Inference
geographic_footprint
Operations in ~20 countries; significant revenue from Iraq, Nigeria, and Brazil—all high sovereign FX devaluation risk with USD-denominated contracts partially mitigating exposure
Inferred
Agent_Inference
commodity_exposure_profile
High intensity; commodities: Crude Oil, Natural Gas, Coal, Refined Petroleum Products, Uranium, Steel (equipment); geopolitical: OPEC+ supply decisions and Russia-Ukraine conflict drive price volatility.
Medium
GICS-commodity-overlay-v1
vendor_lock_dependency_score
No single vendor exceeds 30% of input costs, but barite supply concentration in China creates quasi-lock-in; moderate substitutability risk
Inferred
Agent_Inference
business_model_type_primary
Industrial/oilfield services company; not cloud-dependent—on-premise and field operations dominate; cloud termination would cause minimal operational disruption
Inferred
Agent_Inference
business_model_type_secondary
Back-office and ERP systems may use cloud (likely SAP or Oracle hosted); 30-day termination disruptive but recoverable within 60-90 days
Inferred
Agent_Inference
switching_cost_profile
Low API coupling risk; operational model is physical services and chemistry-based fluids, not software-API dependent; switching cost is relationship/formulation-based
Inferred
Agent_Inference
howey_test_risk_index
Fails Howey Test; revenue model is direct industrial services and product sales—no investment contract, no profit expectation from third-party efforts; near-zero securities risk
Inferred
Agent_Inference
regulatory_burden_tier
High
Medium
GICS-regulatory-overlay-v1
data_sovereignty_risk
Limited GDPR/CCPA exposure; primary data is operational/drilling data, not consumer PII; compliance cost immaterial relative to revenue base
Inferred
Agent_Inference
antitrust_exposure_flag
Low antitrust risk; operates in fragmented oilfield fluids market alongside Halliburton, SLB, and others; no dominant market share in any segment
Inferred
Agent_Inference
regulatory_exposure_profile
High burden; regimes: EPA, FERC, DOE, CFTC, OSHA, SEC; Accelerating emissions mandates and methane rules threaten capex economics.
Medium
GICS-regulatory-overlay-v1
revenue_model_type
Predominantly transactional (~85%); multi-year MSAs with E&P operators provide partial recurrence (~15%), but volumes fluctuate with drilling activity
Inferred
Agent_Inference
monetization_vector
Product sales (drilling fluids and additives) plus service fees; revenue tied to rig count and well complexity, not subscription or SaaS-type recurring streams
Inferred
Agent_Inference
pricing_architecture
Cost-plus pricing with commodity pass-through; limited pricing power in downturns; barite and chemical cost spikes compress margins if pass-through lags
Inferred
Agent_Inference
pricing_power_rating
Low-to-moderate; commoditized fluid systems face price competition; differentiated HPHT and deepwater formulations command modest premium—overall pricing power 4/10
Inferred
Agent_Inference
target_gross_margin_bracket
Gross margins historically 35-42%; industrial fluids segment lower (~30%), industrial minerals segment higher (~45%); blended target ~38%
Inferred
Agent_Inference
churn_vulnerability_index
No free-rider problem; physical product/service model requires direct purchase; churn risk is customer rig count reduction, not product substitution or free usage
Inferred
Agent_Inference
headcount_cost_structure
Revenue growth is largely headcount-linear; field service technicians scale with active jobs; doubling revenue requires ~70-80% headcount increase—limited operating leverage
Inferred
Agent_Inference
marginal_cost_of_growth
Sublinear but not dramatically so; incremental revenue requires incremental field staff, equipment, and inventory; marginal cost of growth ~75-80% of revenue growth
Inferred
Agent_Inference
franchise_compliance_risk
Not a franchise model; null
Inferred
Agent_Inference
customer_acquisition_metric
At 10x scale, CAC efficiency improves modestly via larger MSAs, but market size constrains scalability; unit economics remain tied to rig count, not software-style scaling
Inferred
Agent_Inference
network_effect_present
No meaningful network effects; value proposition is product performance and service quality, not platform scale; network effect durability score: near zero
Inferred
Agent_Inference
asset_efficiency_ratio
AI displacement risk low in near-term; fluid formulation and on-site service delivery require physical presence; AI could optimize formulations but not displace field operations
Inferred
Agent_Inference
recession_resistance_tier
Tier 3 (cyclical); revenue highly correlated with oil & gas capex spending, which contracts sharply in recessions; 2020 revenue fell ~35% YoY
Inferred
Agent_Inference
customer_segment_primary
Major and independent E&P operators (onshore and offshore drilling programs); top 10 customers likely represent 40-50% of Fluids revenue
Inferred
Agent_Inference
customer_segment_secondary
Industrial end-markets (roofing granules, filtration, absorbents) via Industrial Minerals segment; more diversified, less cyclical than E&P segment
Inferred
Agent_Inference
characteristic_occupations
["11-0000 Management Occupations", "13-0000 Business and Financial Operations Occupations", "15-0000 Computer and Mathematical Occupations", "17-0000 Architecture and Engineering Occupations", "19-0000 Life, Physical, and Social Science Occupations", "23-0000 Legal Occupations", "41-0000 Sales and Related Occupations", "43-0000 Office and Administrative Support Occupations", "47-0000 Construction and Extraction Occupations", "49-0000 Installation, Maintenance, and Repair Occupations", "53-0000 Transportation and Material Moving Occupations"]
High
SOC-2018/GICS-overlay
agent_automatable_labor_share
0.33 (HIL — ~33% of characteristic roles agent-automatable)
Medium
SOC-2018 + agentic-exposure-v1
capital_expenditure_profile
Capex modest (~$20-30M/yr); mix shifting toward industrial minerals infrastructure and fluid systems modernization; no major legacy-to-future reallocation underway
Inferred
Agent_Inference
sec_cik
884217
Inferred
Agent_Inference
ticker
NR trades at ~0.5x revenue and ~5-7x EBITDA, reflecting cyclical discount, barite supply geopolitical risk, and E&P spending uncertainty—modest discount to intrinsic value
Inferred
Agent_Inference

Business Model Components

Core Space

> *Pending Turn 2 — Business Model Type Agent population.*

Interaction Modes

> *Pending Turn 2 — Business Model Type Agent population.*

Product Matrix

> *Pending Turn 2 — Business Model Type Agent population.*

Historical Evolution Log

Live Operational Signals

Signal DateSignal TypeSummary
Source

Evaluation Gate — Persona Stress Tests

SKILL_BUFFETT_VAL_03PASS2026-07-21no unmet atoms among this persona's authored questions
SKILL_LEGAL_SEC_01PASS2026-07-21no unmet atoms among this persona's authored questions
SKILL_SHORT_BEAR_01PASS2026-07-21no unmet atoms among this persona's authored questions
SKILL_MACRO_STRAT_01PASS2026-07-21no unmet atoms among this persona's authored questions
SKILL_OPS_PARTNER_01PASS2026-07-21no unmet atoms among this persona's authored questions

Live Status

No Live Status block found.