The most common question we get from prospects: "What does a Joust Operating Review actually produce?"
Easier to show than to describe. Below is a walkthrough of a representative engagement: a $200M B2B distributor, three-week senior-led Operating Review, three findings totaling $1.84M in annualized operations tax, and a 12-month implementation roadmap. Sector-anonymized; the pattern is consistent across distributors we've worked with.
What we asked
The CFO's question: where can technology move the needle in our highest-volume operating areas? They had tried two AI initiatives in the prior year, neither had stuck, and the conversation with their board was getting harder.
Our answer, after three weeks: $1.84M in annualized operations tax across three workflows. The biggest single win, exception handling in order-to-cash, is achievable in twelve weeks. We recommended starting there before approving any other AI spend.
How we worked
Three-week engagement covering operations across three business units. Twenty stakeholder interviews, ERP and CRM data review covering eighteen months of transactions, three end-to-end workflow walkthroughs, and a system inventory across finance, operations, and customer-facing tooling. We did not review HR operations, marketing automation, or supply-chain forecasting.
Sources reviewed:
- Stakeholder interviews. Twenty interviews across operations, customer service, finance, and IT leadership.
- ERP and CRM data exports. 18 months of order-to-cash transactions (~340,000 records); 12 months of customer service tickets (~52,000 tickets).
- System and tooling inventory. ERP, CRM, EDI integration layer, customer service platform, BI tooling.
What we found, in three findings
Finding 1: Order-to-cash exception handling carries the largest tax (HIGH)
What we found. 14% of orders go to manual exception handling, averaging 4.7 days of staff time per exception across AR, customer service, and operations. Of those exceptions, 38% classify into one of seven recurring types from the existing data. The exception types are stable across the 18-month window.
Why it matters. At this client's order volume, exception handling carries roughly $1.1M in annual senior-labor cost and contributes about seven days to DSO. The data to classify and route most exceptions automatically is already in the ERP. The gap is the workflow, not the data.
Recommendation. Run a 12-week implementation on the seven-type exception classifier with AI-augmented dispute drafting. Owner: AR Director. Investment: $180K - $240K. Timeline to first measurable DSO impact: 8 weeks from kickoff.
Finding 2: Customer service intake spends senior time on routing (MEDIUM)
What we found. 62% of inbound customer service tickets are routed manually by senior reps before being assigned. Average classification time per ticket is 4.2 minutes; reps spend roughly 28% of their day on routing rather than resolution. Existing tags are accurate enough to train a classifier on the last 12 months of data.
Why it matters. Roughly $440K in annual senior-rep capacity is consumed by routing rather than resolution. First-response SLA is at risk on 11% of tickets, almost all of which are flagged late by the routing process itself.
Recommendation. Add an AI classifier ahead of the existing CS workflow, with senior-rep override and weekly audit. Owner: CS Director. Investment: $80K - $120K. Timeline to first measurable SLA improvement: 4 weeks from go-live.
Finding 3: Sales operations reporting is composable from system data (LOW)
What we found. The weekly sales operations rollup (10 tabs, 27 charts) is hand-built each Friday by two analysts using exports from CRM and ERP. The underlying data is clean and available via API. The report has not changed in structure for 14 months.
Why it matters. About $300K in annual analyst capacity is consumed by report assembly. That capacity is needed for sales analysis, not formatting. Latency between data and decision is currently three business days; with automation, it falls to under one.
Recommendation. Replace the manual rollup with an automated weekly report (system data plus AI narrative summarization, with human review). Owner: Sales Ops Lead. Investment: $40K - $70K. Timeline to first weekly automated report: 6 weeks from kickoff.
The recommendations summary
| # | Recommendation | Owner | Timing |
|---|---|---|---|
| 1 | Build the seven-type O2C exception classifier with AI-augmented dispute drafting | AR Director | 0-90 days |
| 2 | Add AI ticket classifier ahead of the existing CS workflow | CS Director | 30-90 days |
| 3 | Replace manual sales operations rollup with automated weekly report | Sales Ops Lead | 60-120 days |
What the deliverable actually contains
Each Operating Review closes with five engagement deliverables and two governance artifacts:
- Operations Map. Workflow inventory across the in-scope functions.
- Operations Tax Model. Workflow-level cost-and-benefit math your CFO can read.
- Workflow Recommendations Report. The findings above, ranked by impact.
- Implementation Roadmap. Sequenced 12-week build plan with owners.
- Reference Spec. One workflow detailed to the level needed for engineering kickoff.
- AI Governance Charter. Decision rights, oversight, risk policy.
- AI Investment Framework. Build/buy criteria, ROI templates.
What's typical, what's not
Typical for distributors: the order-to-cash exception pattern. We see it across distribution, B2B services, and parts of professional services. The exact dollar number varies; the pattern doesn't.
Less typical: finding three workflows that all clear the implementation hurdle inside three weeks. Some engagements surface six findings; some only one or two. We size each one and let the math drive the recommendation.
What happens next
If you want to see what the operations tax looks like inside your business, book a 30-minute conversation. The Joust Operating Review is three weeks, fixed scope. The conversation is candid: whether you have a problem worth solving, what the Operating Review would cover, and whether Joust is the right fit.
Or email Ron Davis at ron@joustagency.com.
This post is sector-anonymized and based on representative findings from multiple Joust distributor engagements.
Ron Davis
Founder
Three decades building enterprise platforms. Started Joust to close the gap between strategy decks and the work they're supposed to change.