Questionnaire - yts-consulting.com

1

Company identity & structure

9 questions

Legal company name *

Trading / brand name (if different)

Country of registration *

Year founded *

Legal entity type *

Total full-time employees *

Number of office / branch locations *

Core product categories (list all) *

Number of active SKUs / product lines *

Ownership / governance model *

Founder / family owned — informal governance Owner-managed with board oversight Private equity or institutional backed Publicly listed Subsidiary — strategy governed by parent

2

Financials, scale & market position

7 questions

Annual revenue (last fiscal year) *

Gross margin range *

Revenue split — import vs. domestic sourcing *

Import-sourced: 50%

Revenue split — export vs. domestic sales *

Export sales: 30%

Number of active B2B customers / accounts *

Average order value (AOV) *

3

Import & export operations

10 questions

Primary import source countries *

Primary export destination countries *

Number of active import suppliers *

Number of active export customers *

Customs clearance handled by *

Entirely in-house customs team Licensed external customs broker Mixed — some in-house, some outsourced Freight forwarder manages end-to-end

Average customs dossier preparation time (hours per shipment) *

Typical documents processed per import shipment *

Average lead time from purchase order to goods received (days) *

Biggest bottleneck in import/export process *

4

Warehouse & inventory management

10 questions

Total warehouse area (sq m) *

Number of warehouse sites *

Average daily shipments out *

Warehouse management system (WMS) in use *

Inventory identification technology used *

Current inventory accuracy rate *

Accuracy: 80%

0% (chaotic)50%100% (perfect)

Stock counting method *

Annual full physical count only Quarterly cycle counts Monthly rolling counts Perpetual inventory (real-time) Continuous cycle count (automated)

Average picking error rate (%) *

Average put-away time per pallet (min) *

Warehouse automation equipment present *

Conveyor belt systems Automated storage & retrieval (AS/RS) Autonomous mobile robots (AMRs) Forklift fleet (manual) Automated palletisers / shrink wrappers None — fully manual

Biggest warehouse inefficiency today *

5

Order management & sales operations

8 questions

Average purchase orders received per day *

Average order processing time (hours) *

Order intake channels used *

Order-to-invoice process *

Fully manual — staff key data into multiple systems Partially automated — some steps require manual input Mostly automated — exceptions handled manually Fully automated — straight-through processing

Order error / correction rate *

Error rate: 5%

0%15%30%+

CRM system in use *

Accounts receivable — average DSO (days sales outstanding) *

Main pain points in order management *

6

Technology landscape & systems

9 questions

Primary ERP system *

Additional systems in use *

Dedicated WMS (separate from ERP) TMS — Transportation Management System B2B e-commerce portal Customs / trade compliance platform Demand planning / forecasting tool Product Information Management (PIM) Business Intelligence / reporting platform Document management system (DMS) E-signature platform

Infrastructure model *

On-premises — own servers, own IT team Hosted / private cloud (colocation) SaaS / public cloud (AWS, Azure, GCP) Hybrid (mix of on-prem + cloud)

System integration level *

Siloed — each system is standalone, data re-keyed manually Point-to-point integrations (some CSV/API links) Middleware / iPaaS platform (e.g. MuleSoft, Boomi, Zapier) Well-integrated — real-time data flows across systems

ERP / WMS implementation age (years) *

IT team size (FTE) *

API availability of core systems *

Biggest technology pain point *

7

Data maturity & analytics

8 questions

Data quality self-assessment across key areas

Analytics / reporting capability *

Manual reports — staff compile Excel reports weekly/monthly BI dashboards (Power BI, Tableau, Looker) — batch refresh Near real-time dashboards connected to ERP/WMS Predictive analytics in use (forecasting, scoring)

How many years of clean historical transactional data exist? *

Data governance practices in place *

Designated data owner / steward per domain Data dictionary / schema documentation Master data management (MDM) process Regular data cleanse routines Data access controls / RBAC None of the above

8

Current automation & process efficiency

8 questions

Overall process automation level *

Automated: 25%

0% (all manual)50%100% (fully automated)

Manual effort estimation by process area

Process	Fully manual	Mostly manual	Mixed	Mostly automated	Fully automated
PO / order entry
Invoice processing
Customs documentation
Inventory replenishment
Shipping & carrier booking
Customer communications
Financial reconciliation
Supplier performance tracking

Any existing RPA, AI or ML tools deployed? *

RPA bots (UiPath, Automation Anywhere, Blue Prism) AI-powered document processing (OCR / IDP) Chatbot / virtual assistant Demand forecasting ML model AI pricing or margin optimisation Automated email triage None — no AI/ML deployed

Estimated FTE hours lost per week to manual, repetitive tasks *

9

Supply chain & supplier management

6 questions

Total active suppliers *

% of spend on top 5 suppliers *

Supplier performance is tracked *

Not tracked — informal / subjective assessments only Manual scorecards updated periodically Systematic KPIs tracked in ERP or spreadsheets Automated supplier performance dashboards

Supply chain risk management *

No formal risk process Dual-sourcing strategy for critical items Geopolitical / tariff risk monitoring Safety stock buffers calculated by formula AI/ML-based demand sensing

Demand forecasting methodology *

Gut feel / experienced buyer judgment Simple moving average on historical sales Statistical forecasting tool (e.g. Excel solver, R) Purpose-built demand planning software AI/ML-based demand forecasting

10

Compliance, risk & security

6 questions

Regulatory / trade compliance requirements *

Export control (ITAR / EAR) AEO / C-TPAT trusted trader status GDPR / KVKK data privacy ISO 9001 / ISO 14001 Anti-money laundering (AML) checks Product-specific (food safety, pharmaceuticals, chemicals) Sanctions screening (OFAC, EU, UN) None that apply

Sanctions & denied party screening process *

Not performed Manual periodic checks using free online lists Compliance software (Amber Road, Descartes, Sayari) Automated screening integrated into ERP/trade system

Cybersecurity posture *

Multi-factor authentication (MFA) enforced Encryption at rest and in transit Regular penetration testing SIEM / security monitoring Documented incident response plan Regular staff security awareness training Cyber insurance in place

Audit trail availability for AI-driven processes *

No audit trails currently Partial logging in some systems Full audit trails in key systems Centralised immutable audit log (SIEM/DLP)

11

People, culture & change readiness

7 questions

Warehouse staff (FTE) *

Admin / back-office staff (FTE) *

Sales & account management (FTE) *

Leadership attitude toward AI / automation *

Sceptical — worried about cost and disruption Cautiously open — would act on a clear ROI case Enthusiastic — already championing automation Strategic priority — board-level mandate for digital transformation

Previous change / technology project success rate *

Poor — most projects fail or go significantly over time/budget Mixed — some successes, some failures Good — most projects delivered on time Excellent — strong track record of delivery

Dedicated digital transformation / innovation role exists? *

No — owned ad-hoc by IT manager or COO Informal champion (part of someone’s remit) Yes — dedicated Digital / Innovation Manager Yes — CDO / CTO with cross-functional mandate

12

AI vision, strategic goals & investment

7 questions

Top AI automation use cases you want to prioritise *

Select all that interest you

Invoice & PO data extraction Customs document automation AI demand forecasting Inventory replenishment AI Order management automation Supplier risk scoring AI email triage & routing Freight rate optimisation Automated HS code classification Predictive maintenance B2B chatbot / self-service Price optimisation engine Accounts payable automation Warehouse pick path optimisation Sanctioned party screening AI Contract review AI

Primary driver for pursuing AI automation *

Cost reduction — headcount or operational savings Revenue growth — faster processing, better customer experience Risk reduction — compliance, accuracy, resilience Competitive pressure — peers already automating Scale — need to grow volume without adding proportional headcount

Annual budget available for AI / automation projects *

Preferred implementation approach *

Quick wins first — isolated pilots under 90 days Platform-led — build unified data/AI platform first Full digital transformation — end-to-end redesign Hybrid — quick wins + parallel strategic roadmap

Constraints or concerns about AI adoption *

Data quality is too poor to train models Existing systems can’t integrate with AI tools Staff resistance or fear of job displacement Lack of internal AI expertise Budget constraints Regulatory / data sovereignty concerns No clear internal sponsor / ownership No major concerns

Anything else you want us to know before the audit (optional)

C

Contact details

Required

Full name *

Job title *

Business email *

Phone (with country code) *

Preferred contact method *

Preferred meeting timezone *

Data domain	Poor	Fair	Good	Excellent
Customer master data
Product / item master
Inventory / stock data
Supplier data
Financial / accounting data
Historical transaction data

Team	Low	Medium	High	Advanced
Warehouse / operations staff
Finance / admin team
Sales team
Management / directors
IT / technical team

Long-term value for all customers

New York Office

B2B Wholesale Company Discovery

Long-term value for all customers

New York Office

B2B Wholesale Company Discovery

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