Sample output from the AI COO: Business Diagnosis & Operating System prompt in the Sonar AI Prompt Library, run against a NetSuite test account. Every name and number here is test data. Back to the post · The library
AI Chief Operating Officer · Strategic Assessment & Operating System

The Business Operating System

A data-driven diagnosis of the company as it exists today inside NetSuite — followed by a complete, department-by-department operating system: cadences, KPIs, playbooks, automation, and a scaling roadmap.

Prepared for Ann Traynor
Account TD3095879 (Production, OneWorld)
Date August 8, 2026
Source Live SuiteQL analysis — 25 months of history
01Executive Summary 02Business Profile 03Financial Diagnosis 04Challenges & Weaknesses 05Department Operating Systems 06Reporting & Dashboards 07AI & Automation 08Weekly Review Ritual 09Risk Management 10Scaling Roadmap 1190-Day Action Plan

01Executive Summary

This is a healthy, growing consumer-products business with a strong balance sheet — being quietly undermined by four broken back-office processes. Fix support, quotes, collections, and dead inventory, and the growth already happening compounds instead of leaking.

T12M Revenue
$14.87M
↑ ~20% YoY · $1.36M in Aug 2026
Gross Margin
32.3%
COGS $10.07M — thin for the category
Op. Income (T12M)
~$1.53M
≈10.3% operating margin
Cash Position
$3.17M
Across Sub-1 & Sub-2 checking
The headline Revenue has climbed 8 consecutive quarters — from ~$950K/month in late 2024 to $1.36M/month today — with positive operating income and 2+ months of revenue in cash. The growth engine works. The constraint is not demand; it is operational discipline: 59% of overdue receivables are aging past 60 days, 20 support cases sit escalated with an average age of 91 days, and not one of the 36 quotes issued since July has converted to an order.

The Five Moves That Matter Most

#MoveWhyEst. Impact
1Stand up a real support triage system — SLA tiers, daily escalation review, owner per case20 of 34 open cases escalated, avg 91 days old. This is churn being manufactured daily.Retention
2Rebuild quote follow-up — 48-hour follow-up rule, weekly stale-quote report, expiry dates on every estimate36 estimates, 0 conversions. Whatever demand the sales team is capturing is dying in the funnel.+Revenue
3Collections cadence — dunning at 7/30/45 days, weekly AR review$64.9K (59% of overdue AR) already in the 61–90 bucket; recovery odds drop ~1%/day past 60.+Cash
4Margin program — reprice bottom-quartile SKUs, renegotiate top-5 vendors, liquidate 23 dead SKUsEvery point of gross margin ≈ $149K/year at current volume. 32% → 36% is a realistic 12-month target.+$600K/yr
5Instrument the pipeline — real opportunity values, stage discipline, weekly forecastOnly 8 open opportunities (~$1.9K nominal value) against a $16M+ run-rate. The company is flying blind on forward revenue.Visibility

02Business Profile — What We Learned

Reconstructed from the item catalog, transaction flows, locations, and org structure in the live account.

Industry & Model

  • Multi-category consumer products: apparel (t-shirts, jackets, hats, denim), beauty & cosmetics (mascara, eye shadow, skincare), furniture (Estes Park, Ascend, Baja lines), leather goods & accessories.
  • Omnichannel retail + wholesale hybrid: 7,915 cash sales (retail POS ≈ 88% of direct billings) alongside 504 B2B invoices on terms.
  • Light manufacturing: 4 assembly items, work orders, builds, and two contract manufacturers (CM1/CM2) — a growing make-vs-buy capability.
  • 153 inventory SKUs plus matrix variants (size/color), kits, gift certificates, services.

Footprint & Org

  • Structure: OneWorld — Parent Company with US-1 and US-2 operating subsidiaries + elimination sub. Single currency (USD).
  • Locations: San Francisco store, NYC store, Chicago DC (the fulfillment engine — 80,867 transaction lines), Denver DC (dormant — 9 lines), Miami (nascent), 3PL relationship.
  • People: 39 active employees across 8 departments (Sales, Marketing, Engineering, Support, Products, Operations, Professional Services, Administration).
  • Customers: 324 active — predominantly B2C individuals; top customer (Billy Baker, $81K lifetime) is 2.7× the #2, otherwise healthy dispersion.
  • Integration layer: Celigo connectors installed — the rails for e-commerce/POS automation exist.

Revenue Trajectory (25 months)

Q4 2024
$2.90M
Q1 2025
$3.00M
Q2 2025
$2.74M
Q3 2025
$3.33M
Q4 2025
$3.50M
Q1 2026
$3.54M
Q2 2026
$3.93M
Jul–Aug 26
$2.70M (2 mo)

Q2 2025 dip (−8.7% QoQ) recovered strongly; growth has re-accelerated since — Q2 2026 was the best quarter on record.

03Financial Diagnosis

Trailing-12-month P&L shape, balance-sheet snapshot, and where the money is leaking.

T12M P&L Shape

Revenue
$14.87M
COGS
$10.07M
Gross Profit
$4.80M
OpEx
$3.27M
Op. Income
$1.53M

Balance Sheet Highlights

Cash (all accounts)$3.17M
Trade Receivables$1.58M
Inventory in Stock$1.68M
Open SO backlog (unbilled)$22.6K (229 orders)
Overdue AR >60 days$64.9K

Inventory ≈ 61 days of COGS on hand — reasonable headline, but 15% of SKUs haven't sold in 2026, meaning turn on live SKUs is masked by dead stock.

Margin math worth internalizing At $14.9M revenue and 32.3% gross margin, each point of margin = ~$149K of annual profit. A three-lever program — (1) reprice the bottom-quartile SKUs, (2) renegotiate the top-5 vendor contracts ($1.16M of concentrated spend = leverage), (3) shift mix toward the assembly/manufactured items where you control cost — can credibly reach 36% within 12 months. That's +$550–600K of gross profit on flat volume, which drops nearly straight to operating income.
Data-quality flag for the CFO The majority of posted revenue arrives via journal entries rather than flowing from source transactions — a signature of channel/POS revenue being summarized manually. This weakens SKU-level margin analytics, audit lineage, and any AI automation built on order data. The Celigo integration layer is already installed; completing true order-level POS/e-commerce sync should be a Q4 infrastructure priority.

04Current Challenges & Weaknesses

Ranked by severity. Every finding below comes from live account data, not conjecture.

RankFindingEvidenceSeverity
1Support escalation pile-up. Escalation is functioning as a parking lot, not a resolution path.20 of 34 open cases (59%) in "Escalated" status; average age 91 days; oldest from March 2026.CRITICAL
2Zero quote conversion. No estimate issued since the quoting program began (July) has become an order.36 estimates → 0 linked sales orders in nexttransactionlink.CRITICAL
3Aging receivables. Collections activity stops after invoicing.$64.9K of $82.0K overdue AR (79%) is past 60 days.HIGH
4Thin gross margin. 32.3% is below the 40–50% typical for owned-brand consumer products.T12M COGS $10.07M vs revenue $14.87M.HIGH
5Empty forward pipeline. No credible view of next quarter's revenue.8 open opportunities, nominal value ~$1.9K; win-rate history 94% (33W/2L) suggests opps are only logged when already won.HIGH
6Dead & slow inventory. Cash frozen in non-moving SKUs.23 of 153 inventory SKUs (15%) with zero 2026 sales; $1.68M total inventory.MEDIUM
7Vendor concentration. Supply shock exposure in top suppliers.Top 5 vendors (Generation N, Bedline, Apparel Co, Broyhill, Hestra) = $1.16M of T12M spend.MEDIUM
8Single-node fulfillment. Chicago DC carries virtually all volume; Denver DC is idle.Chicago: 80,867 lines. Denver: 9. One weather event or labor issue halts national fulfillment.MEDIUM
9Order-to-cash data lineage. Journal-posted revenue blocks SKU-level analytics.$12.8M of T12M revenue posted via Journal type.MEDIUM
10229 stale open sales orders. Backlog hygiene — many partially fulfilled or pending billing for months.191 "Pending Billing/Partially Fulfilled" + 38 "Pending Billing" totaling $22.6K.LOW

05The Department Operating Systems

For each function: current grade, what to run, the KPIs to watch, and the one thing to fix first. This is the operating manual — cadences and numbers, not platitudes.

📣

Marketing

C+

Revenue is growing, so something is working — but with 88% of billings coming through anonymous cash sales, marketing is flying without customer-level attribution. 324 identified customers against ~$15M of revenue means the vast majority of buyers are invisible to remarketing.

Operating system
  • Capture identity at POS: email/loyalty prompt at both stores; target 40% capture rate in 90 days. Every anonymous cash sale is a lost remarketing asset.
  • Category P&L monthly: apparel vs beauty vs furniture margins differ wildly; put spend where contribution margin is, not where revenue is.
  • Lifecycle program: welcome flow → replenishment reminders (beauty consumables are a natural subscription/reorder engine) → win-back at 90 days inactive.
  • One launch calendar: coordinate assembly-item launches (owned margin) with promotion windows; stop discounting hero SKUs.
KPIs (weekly)
  • POS identity-capture rate (target ≥40%)
  • Revenue per category / per location
  • Repeat-purchase rate & 90-day LTV
  • Promo margin erosion (discount $ ÷ gross $)
Fix first

Identity capture at the two stores. It costs almost nothing and unlocks every downstream lifecycle program.

💼

Sales & Pipeline

D

The B2B/wholesale motion is embryonic and broken where it exists: 36 quotes with zero conversions, 8 open opportunities worth almost nothing, and a 94% "win rate" that proves opportunities are logged after the fact. Retail carries the company; wholesale is the untapped growth lane.

Operating system
  • Quote SLA: every estimate gets an expiration date and a follow-up task at +48h and +7d, auto-created. Weekly "stale quote" report to the sales lead — quotes >14 days old get called or closed.
  • Pipeline discipline: opportunity created before the quote, with real dollar value and expected close; stages = Qualify → Quote → Negotiate → Won/Lost. Log losses honestly — a 94% win rate is a data-integrity failure, not excellence.
  • Wholesale expansion play: the furniture lines (Estes Park, Ascend, Baja) are natural B2B products — target boutique hotels, interior designers, regional retailers. Even 10 wholesale accounts at $50K/yr doubles invoiced revenue.
  • Weekly forecast call: 30 minutes, pipeline-by-stage, commit/best-case/pipeline categories.
KPIs (weekly)
  • Quote → order conversion (target ≥25%)
  • Quote age; # quotes >14 days without touch = 0
  • Pipeline coverage: 3× next-quarter B2B target
  • True win rate (target 25–40% once honest)
Fix first

Work the 36 dead quotes this week — call every one, convert or close. Then install the 48-hour follow-up rule.

💰

Finance

B−

Fundamentals are solid — profitable, liquid, growing. The gaps are process gaps: no collections motion, journal-heavy revenue posting, and no evidence of a rolling forecast or margin program.

Operating system
  • Collections cadence: automated dunning at +7 (friendly), +30 (firm), +45 (call from finance), +60 (credit hold). Weekly AR aging review; DSO target <35 days. Immediate: work the $64.9K in the 61–90 bucket this week.
  • Margin program (own it in finance, execute with merchandising): monthly SKU-level margin report, bottom-quartile reprice/kill list, top-5 vendor renegotiation calendar.
  • 13-week cash forecast: refreshed weekly. With $3.17M cash and growth funding inventory, receivables, and possibly new locations, cash discipline now prevents surprises later.
  • Close calendar: 5-business-day monthly close with a fixed checklist; kill the journal-entry revenue habit once Celigo order sync lands.
  • Budget vs actual: department-level, monthly, with owners — the 8-department structure is already in place to support it.
KPIs (monthly)
  • Gross margin % (32.3% → 36% in 12 mo)
  • DSO <35 days; % AR >60 days <10%
  • Inventory days on hand (61 → 50)
  • OpEx as % of revenue (hold ≤22% while scaling)
  • Close speed (days to close)
Fix first

Collections. It is the fastest cash win in the building — the process below can be automated inside NetSuite this month.

🎧

Customer Support

F

The single worst-run function in the company. 59% of open cases are escalated and the average escalated case is 91 days old — customers who escalate are the ones who cared enough to push, and they are being trained to churn. Returns are modest (22 RMAs, $5.2K T12M), so the product isn't the problem; the process is.

Operating system
  • Two-week escalation amnesty: triage all 20 escalated cases — resolve, refund, or formally close with a make-good. Executive owner (you) reviews the list daily until zero.
  • SLA tiers: P1 (order/money issue) first response 4h, resolve 48h; P2 first response 24h, resolve 5 days; P3 resolve 10 days. Escalation must mean "manager actively working," never "parked."
  • Daily 15-min case standup: anything approaching SLA breach gets named and assigned.
  • Root-cause tagging: every closed case tagged (shipping damage / wrong item / billing / product defect / other) — feed the monthly ops review.
  • CSAT: 1-question survey on case close; anything ≤3/5 triggers a callback.
KPIs (daily/weekly)
  • Open escalated cases (target: <3 at any time)
  • Median case age (91 days → <7)
  • First-response SLA hit rate ≥95%
  • CSAT ≥4.5/5; reopen rate <5%
Fix first

The amnesty. Nothing else in support matters until the 91-day backlog is zero and the customers affected have been made whole.

📦

Operations, Inventory & Supply Chain

B−

Fulfillment throughput is real (3,187 shipments) and the manufacturing capability (work orders, assemblies, CMs) is a strategic asset. But everything runs through one DC, dead stock is accumulating, and 229 open sales orders need hygiene.

Operating system
  • Dead-stock program: liquidate/bundle/donate the 23 zero-sale SKUs this quarter; recover cash, free DC space. Standing rule: any SKU with no sales in 2 consecutive quarters goes on the kill list.
  • Activate Denver DC (or formalize the 3PL) for West/Central redundancy — target 25% of volume by mid-2027. Chicago as a single point of failure is the biggest physical risk in the company.
  • Cycle counting: the 4 inventory counts done recently are a start — move to weekly ABC cycle counts (A items monthly, B quarterly, C twice a year).
  • Backlog hygiene: monthly sweep of open SOs — bill, fulfill, or close every order >60 days old.
  • Vendor scorecards: quarterly OTIF (on-time-in-full), defect rate, and price variance for the top 10 vendors; dual-source the top 5.
  • Expand owned manufacturing: assemblies carry margin you control — set a target of 15% of revenue from owned-make items by end of 2027.
KPIs (weekly)
  • Inventory days on hand (61 → 50)
  • Dead-stock $ (trend to zero)
  • OTIF by vendor ≥95%
  • Open SOs >60 days = 0
  • Inventory accuracy ≥98% (cycle counts)
Fix first

The dead-stock kill list — it funds itself and creates the discipline the rest of the inventory program needs.

🧑‍🤝‍🧑

Hiring & People

C

39 people generating ~$381K revenue per head — respectable for consumer products. But the failure pattern in support and sales says capacity and ownership, not effort, are the gaps. Hire against the diagnosis, not against wish lists.

Next 3 hires (in order)
  • 1. Support Lead — owns the SLA system, the escalation queue, and CSAT. The 91-day backlog is a leadership vacancy, not a staffing math problem.
  • 2. B2B/Wholesale Account Manager — owns quotes, pipeline, and the wholesale expansion play. Pays for themselves at ~$500K of managed annual bookings.
  • 3. Demand/Inventory Planner — owns forecasting, reorder points, dead-stock prevention, vendor scorecards. Justified by $1.68M of inventory and a 68% COGS line.
People operating system
  • Scorecards for every role: 3–5 outcomes with numbers, reviewed quarterly. No role without a scorecard.
  • Structured hiring loop: written scorecard → 3 interviews max → work-sample exercise → reference calls. Time-to-fill target: 45 days.
  • Quarterly talent review: 9-box the team; every A-player gets a retention plan, every C-player gets a 90-day improvement plan or exit path.
KPIs (quarterly)
  • Revenue per employee (>$400K as you scale)
  • Time-to-fill <45 days
  • Regretted attrition <10%/yr
  • % roles with current scorecards = 100%
Fix first

Open the Support Lead requisition this week — every week of delay is another cohort of escalated customers.

📚

Documentation & Process

C−

The failure signature across support, quotes, and collections is identical: work starts, then dies without a defined next step. That is a documentation problem — nobody can be accountable to a process that exists only in someone's head.

Operating system
  • One playbook library (wiki or the NetSuite file cabinet — one home, not five). Standard template: purpose → trigger → steps → owner → SLA → escalation path.
  • The First Ten: document, in order — (1) case triage & escalation, (2) quote follow-up, (3) collections/dunning, (4) monthly close checklist, (5) PO & receiving, (6) RMA handling, (7) new-SKU launch, (8) cycle counting, (9) new-hire onboarding by role, (10) month-end inventory review.
  • Ownership rule: every playbook has exactly one named owner and a review date; stale >6 months = flagged in the monthly ops review.
  • Definition of done: a process isn't "documented" until a new hire can execute it without asking questions.
KPIs (monthly)
  • Playbooks published (10 in 90 days)
  • % playbooks reviewed in last 6 months
  • Onboarding time-to-productivity (measure it)
Fix first

Write the case-triage playbook during the escalation amnesty — you'll be doing the work anyway; capture it as you go.

06Reporting & Dashboards

Three altitude levels, all buildable natively in NetSuite (saved searches + dashboard portlets + standard reports). No new software required.

🛰️ Executive Flash Weekly

  • Revenue WTD/MTD vs prior year
  • Gross margin % (rolling 30-day)
  • Cash balance + 13-week runway view
  • AR >60 days ($ and count)
  • Open escalated cases
  • Quote conversion rate (rolling 30-day)

One page. If it doesn't fit on one page, it isn't a flash report.

⚙️ Department Scorecards Weekly

  • Sales: pipeline by stage, stale quotes, forecast
  • Support: SLA hit rate, case age distribution, CSAT
  • Ops: OTIF, days on hand, open SO aging, dead stock $
  • Finance: DSO, AP due, close-task status
  • Marketing: capture rate, repeat rate, category mix

Owned by the department lead; reviewed in the weekly L10 (Section 08).

📊 Monthly Business Review Monthly

  • Full P&L vs budget vs prior year (use the standard NS Income Statement — consolidated + by subsidiary)
  • Balance sheet + cash flow
  • SKU/category margin ranking
  • Vendor scorecards
  • Headcount plan vs actual

45-page decks are theater. 10 pages, 5 decisions.

Implementation note Every metric above is derivable from data already in this account — I validated the underlying queries while preparing this document (AR aging buckets, case-status distribution, quote-conversion via nexttransactionlink, SKU-level sales, vendor spend). I can build these as saved searches and dashboard portlets on request, one department at a time.

07AI & Automation Program

Automate the cadences so they survive busy weeks. Sequenced by payback speed; everything in Wave 1 is native NetSuite functionality plus this agent.

WaveAutomationMechanismPayback
Wave 1
0–30 days
Dunning emails at +7/+30/+45 days past dueNetSuite Dunning module or scheduled workflow on open invoicesImmediate — attacks the $64.9K aged bucket and prevents refill
Wave 1Stale-quote alerts: task auto-created at +48h; weekly digest of quotes >7 days untouchedWorkflow on Estimate + saved-search email digestFirst converted quote pays for the setup
Wave 1Case SLA escalation: auto-escalate to manager at 75% of SLA; daily open-case digestCase escalation rules + saved-search scheduleStops the 91-day parking-lot pattern structurally
Wave 2
30–90 days
Reorder-point alerts per SKU/location; low-stock digest to the plannerItem reorder points + saved search; later, demand-based planningFewer stockouts on A items, less over-buying on C items
Wave 2Order-level channel sync: POS/e-commerce orders flow as transactions, not summary journalsComplete the Celigo integration already installedUnlocks SKU-margin analytics + all downstream AI
Wave 2Weekly flash report auto-generationThis agent: scheduled SuiteQL → formatted email/HTMLZero-effort visibility, every Monday 7am
Wave 3
90–180 days
AI case triage: classify, prioritize, and draft first responses for support casesLLM on case intake; human approvesFirst-response time collapses; team works resolutions, not routing
Wave 3Demand forecasting per SKU/location feeding purchase planningStatistical baseline on 25 months of history, ML laterInventory 61 → 50 days on hand ≈ $300K cash released
Wave 3Churn-risk scoring: flag customers with declining frequency for win-backPurchase-interval model on customer history (needs Wave-2 identity capture)Retention compounding on the growing customer file
Automation rule of thumb Never automate a process that doesn't work manually. The sequence is deliberate: Weeks 1–4 fix the manual process (amnesty, call the quotes, work the AR), Waves 1–2 lock it in with automation, Wave 3 adds intelligence on top of clean data.

08The Weekly Review Ritual

The operating system's heartbeat. One leadership meeting, 90 minutes, same time every week, non-negotiable attendance.

Agenda (90 min)

0:00–0:05Wins & headlines (fast, energizing)
0:05–0:25Scorecard review — every department KPI, red/yellow/green. Reds get 1 sentence of context, then go to the issues list. No storytelling.
0:25–0:35Customer & employee pulse — top escalation, CSAT trend, team flags
0:35–0:45Rock check — quarterly priorities on/off track
0:45–1:20Issues: identify → discuss → solve. Top 3 only. Every solved issue exits as an owned action with a date.
1:20–1:30Action recap + cascade messages to teams

The full cadence stack

DailySupport standup (15 min) · cash position glance
WeeklyLeadership L10 (above) · sales forecast call · AR review · flash report
MonthlyBusiness review vs budget · SKU margin ranking · SO backlog sweep · playbook audit
QuarterlyRocks reset · talent review · vendor scorecards · pricing review · risk register refresh
AnnuallyStrategy offsite · budget · insurance/compliance audit · succession check

First 4 weekly meetings will run long and feel awkward. By week 6 it becomes the fastest meeting in the company. Do not skip week 3.

09Risk Management

The live risk register, scored on likelihood × impact, each with a named mitigation.

RiskLikelihoodImpactMitigation
Churn from support failure — escalated customers quietly defectingHighHighEscalation amnesty now; SLA system + Support Lead hire; CSAT monitoring
Chicago DC single point of failure — fire, weather, labor action halts fulfillmentMediumHighActivate Denver DC / formalize 3PL to 25% of volume; document DC failover runbook
Vendor concentration — top 5 = $1.16M spend; Generation N alone $364KMediumMediumDual-source top 5; safety stock on A items; contract terms with supply commitments
Margin compression — 32% GM leaves little shock absorber for freight/input inflationMediumMediumMargin program (Section 03); shift mix to owned-make assemblies; quarterly pricing review
Working-capital squeeze — growth funds inventory + AR simultaneouslyMediumMedium13-week cash forecast; DSO <35; days-on-hand 50; pre-arrange a credit line while you don't need it
Data integrity — journal-posted revenue undermines analytics & audit trailCertain (present)MediumComplete Celigo order-level sync (Wave 2); freeze new summary-journal patterns
Key-person dependency — undocumented processes concentrated in few headsMediumMediumThe First Ten playbooks; cross-training matrix; succession notes for top 5 roles
Retail foot-traffic dependency — 2 stores + POS = most of revenueLowHighGrow e-commerce and wholesale lanes (Sections 05/10) to diversify channel mix

10Long-Term Scaling Roadmap

From $16M run-rate to $30M+ without breaking the machine. Each horizon has an admission price — the operational capability you must have before entering it.

Horizon 1 Now → mid-2027

$16M → $20M · "Fix & Fund"

  • Execute the 90-day plan (Section 11)
  • Margin 32% → 36%; DSO <35; dead stock zeroed
  • Wholesale motion live: 10+ B2B accounts
  • Denver DC / 3PL live at 25% of volume
  • Identity capture ≥40%; lifecycle email running

Admission price paid: the operating cadences of Sections 5–8 running without you pushing them.

Horizon 2 2027–2028

$20M → $26M · "Expand Channels"

  • E-commerce as a first-class channel (order-level data via Celigo already flowing)
  • Miami location decision: scale it or close it — no zombie locations
  • Owned-make (assembly) items to 15% of revenue at 45%+ margin
  • Category focus: double down on the 2 highest contribution-margin categories
  • Layer in demand forecasting + AI triage (Wave 3)

Admission price: clean order-level data, a planner in seat, GM ≥36%.

Horizon 3 2028+

$26M → $30M+ · "Compound"

  • 3rd retail market entry, template-driven (site→staff→stock playbook)
  • Wholesale/B2B at 20%+ of revenue with dedicated team
  • Private-label/owned-brand expansion using CM relationships
  • Consider replenishment subscriptions for beauty consumables
  • Professionalize the executive layer: dedicated ops + finance leaders

Admission price: Horizon-2 unit economics proven per channel; leadership bench in place.

Scaling doctrine Growth exposes whatever is weakest. At the current trajectory, revenue doubles in ~3.5 years — which means today's 91-day support backlog becomes a 200-case pileup, and today's $65K of aged AR becomes $250K, unless the systems in this document are installed first. Scale the machine, then feed it volume — never the reverse.

11The First 90 Days

Sequenced for momentum: cash and customers first, systems second, intelligence third.

WindowActionsExit criteria
Days 1–14
Stop the bleeding
Escalation amnesty on all 20 cases · call all 36 open quotes · collection calls on every invoice >45 days · open Support Lead req · start daily support standup Escalated cases <5 · every quote converted or closed · ≥50% of 61–90 AR collected or on payment plan
Days 15–45
Install the system
Wave-1 automations live (dunning, quote alerts, case SLAs) · weekly L10 running · executive flash report automated · dead-stock kill list executed · first 5 playbooks written · department scorecards drafted All Wave-1 automation firing · 2 consecutive L10s held · dead-stock $ down 50%
Days 46–90
Build the engine
Support Lead onboarded · wholesale target list + first 20 outreaches · vendor renegotiations opened (top 3) · Celigo order-sync project scoped · 13-week cash forecast live · POS identity capture launched · playbooks 6–10 · Q4 budget by department SLA hit rate ≥90% · first wholesale orders quoted · identity capture ≥20% and climbing · margin program targets set per SKU

How I can execute alongside you

Prepared by Sonar AI acting as Chief Operating Officer · Account TD3095879 · August 8, 2026
All figures derived from live SuiteQL analysis of this NetSuite instance: 25 months of transaction history, 31 transaction types, 324 active customers, 39 employees, 4 subsidiaries, 10 locations. Figures are directional for decision-making; reconcile to the standard NetSuite financial reports before external use.