Spiese Fluid Power
The Operating Profile - Last Updated: September 4th, 2026
Spiese Fluid Power is fictional – a composite mid-market manufacturer used throughout this series so that every claim we make can be checked. This page is the audit trail behind it.
Most figures here are credible, not measured. They are built to be plausible enough that you recognize your own shop in them – and then the point is that you swap in your own numbers and run them through the same arithmetic. Nothing here is a claim about a real company. It is a worked example you are invited to check, and to copy.
How to read the "Basis" column
Every figure carries a basis, so you can see exactly how much weight it can bear.
| Basis | Meaning |
|---|---|
| SOURCED | Traced to a named public benchmark – SEC filings, BLS, Census, or a published study – cited in full under Sources. |
| DECISION | A deliberate, credible choice – not sourced, and not meant to be. This is a number you should replace with your own. |
| DERIVED | Computed from other inputs. It is never typed, and cannot be set inconsistently. |
| ASSUMED / SET | Below the level where it would change the argument, or a chosen size point or convention. Not a claim about the world. |
The company
Spiese Fluid Power of Racine, Wisconsin. It manufactures hydraulic power units, custom manifolds, and hose assemblies to order (80% of revenue), and also distributes components from a stocked catalog. Two facilities, twenty-two years on the same ERP.
| Figure | Value | Basis |
|---|---|---|
| Revenue | $85,000,000 | SET |
| Manufactured share of revenue | 80% | DECISION |
| Manufactured revenue | $68,000,000 | DERIVED |
| Distributed revenue | $17,000,000 | DERIVED |
| Gross margin — manufactured | 35.0% | SOURCED |
| Gross margin — distributed | 29.0% | SOURCED |
| Blended gross margin | 33.80% | DERIVED |
| Cost of goods sold | $56,270,000 | DERIVED |
| Gross profit | $28,730,000 | DERIVED |
| Employees | 190 | SET |
| Active customers | 4,200 | ASSUMED |
| Stocked SKUs | 12,000 | DECISION |
| Manufactured assemblies with BOMs | 2,400 | ASSUMED |
Order volume — two streams
Spiese runs two very different order streams: a few large engineered builds, and many small parts orders. Modeling them separately is what makes the order count credible – and it reveals that the parts arm, only 20% of revenue, is 82% of order transactions. That is why order-entry keying (Part 2) is a real cost.
| Figure | Value | Basis |
|---|---|---|
| Average order value — manufactured | $8,300 | DECISION |
| Average order value — distributed | $450 | DECISION |
| Manufactured orders / year | 8,193 | DERIVED |
| Distributed orders / year | 37,778 | DERIVED |
| Orders per year | 45,971 | DERIVED |
| Blended average order value | $1,849 | DERIVED |
| Parts orders as % of order volume | 82.2% | DERIVED |
| Orders per business day | 183.9 | DERIVED |
| Lines per order | 4.2 | ASSUMED |
| Order lines per year | 193,076 | DERIVED |
Where the order work is
| Channel | Share | Orders/day | Basis |
|---|---|---|---|
| EDI | 22% | 40.5 | DECISION |
| Web / customer portal | 18% | 33.1 | DECISION |
| Email / PDF attachment | 34% | 62.5 | DECISION |
| Phone | 21% | 38.6 | DECISION |
| Fax | 5% | 9.2 | DECISION |
| Hands-off (EDI + web) | 40% | 73.6 | DERIVED |
| Human-touched | 60% | 110.3 | DERIVED |
| Keyed orders per inside sales rep per day | — | 18.4 | DERIVED |
Manufacturing load
| Figure | Value | Basis |
|---|---|---|
| Work orders released per year | 9,500 | ASSUMED |
| Work orders per business day | 38.0 | DERIVED |
| Component issues per year | 104,500 | DERIVED |
| Net new MRP action messages per week | 1,850 | DECISION |
| MRP messages per business day | 370 | DERIVED |
| MRP messages per planner per day | 61.7 | DERIVED |
| Hours per day to action every message | 15.4 of 46.8 available | DERIVED |
| MRP triage as % of planner capacity | 32.9% | DERIVED |
| Annual planner-time to action every message | $174,722 | DERIVED |
Actioning every message costs a third of the entire planning team's capacity – 32.9%, or about $175,000 a year in planner time (15.4 of 46.8 available planner-hours) – spent mostly on messages that turn out to need nothing. That is Part 5.
Inventory and working capital
At 80% manufactured, inventory is mostly raw and work-in-process, not finished stock – the profile of a build-to-order shop.
| Figure | Value | Basis |
|---|---|---|
| Inventory turns — manufacturing | 3.5 | SOURCED |
| Inventory turns — distribution | 3.8 | SOURCED |
| Manufacturing inventory | $12,628,571 | DERIVED |
| Distribution inventory | $3,176,316 | DERIVED |
| Average inventory | $15,804,887 | DERIVED |
| Raw material | $5,805,588 (36.7%) | SOURCED blend |
| Work in process | $3,065,929 (19.4%) | SOURCED blend |
| Finished goods + distribution stock | $6,933,369 (43.9%) | SOURCED blend |
| Blended inventory turns | 3.56 | DERIVED |
| Inventory as % of revenue | 18.6% | DERIVED |
| Accounts receivable (42 days) | $9,780,822 | ASSUMED |
| Accounts payable (38 days) | $5,858,247 | ASSUMED |
Productivity and labor
| Figure | Value | Basis |
|---|---|---|
| Revenue per employee | $447,368 | DERIVED |
| Revenue per direct employee | $965,909 | DERIVED |
| Revenue per customer | $20,238 | DERIVED |
| Orders per customer per year | 10.9 | DERIVED |
| Inside sales loaded rate | $51.67/hr | SOURCED |
| AP clerk loaded rate | $34.67/hr | ASSUMED |
| Planner loaded rate | $45.33/hr | ASSUMED |
| Productive hours per FTE per day | 7.8 | SET |
Accounts payable load
| Figure | Value | Basis |
|---|---|---|
| AP invoices received per year | 25,000 | DECISION |
| AP invoices per business day | 100.0 | DERIVED |
| AP invoices per clerk per day | 50.0 | DERIVED |
| Hours required per day | 13.3 of 15.6 available | DERIVED |
| AP clerk utilization | 85.5% | DERIVED |
Above 80% utilization with variable arrival rates means a permanent backlog and a month-end scramble. Two clerks is not quite enough – a tension that emerged from the arithmetic, not the narrative. That is Part 6.
Sources
SEC filings — inventory turns comparables
SEC XBRL company-facts API, us-gaap tags CostOfGoodsAndServicesSold and InventoryNet, 10-K filings only. Turns = annual COGS ÷ average inventory. Retrieved 3 August 2026.
| Company (model) | Latest FY | Range |
|---|---|---|
| DXP Enterprises (project/service-heavy) | 13.1 | 10.5 – 13.1 |
| Applied Industrial (engineered solutions) | 6.4 | 6.4 – 6.7 |
| Global Industrial (broad-line) | 5.2 | 5.1 – 5.4 |
| Grainger (broad-line MRO) | 4.7 | 4.4 – 4.7 |
| MSC Industrial (broad-line MRO, deep catalog) | 3.5 | 3.3 – 3.5 |
| DNOW (energy/industrial) | 3.0 | 3.0 – 5.1 |
| Fastenal (inventory held near customer) | 2.7 | 2.5 – 2.7 |
| Richardson Electronics (small specialty) | 1.5 | 1.2 – 1.5 |
| Parker-Hannifin (fluid power mfr) | 4.5 | 4.5 – 4.9 |
| Helios Technologies (fluid power mfr) | 3.0 | 2.7 – 3.3 |
Spiese's manufacturing turns (3.5) sit in the manufacturer band; distribution turns (3.8) sit mid-cluster beside MSC Industrial (3.5), a deep-catalog MRO distributor and the closest analogue to Spiese's parts arm. Distributor turns span 1.5 to 13.1 – set by business model, not size. Fastenal turns 2.7 by design, holding inventory close to the customer for availability.
SEC filings — gross margin comparables
Same API and filings; Revenues and CostOfGoodsAndServicesSold. Gross margin = (revenue − COGS) ÷ revenue, latest three fiscal years.
| Company | Latest FY | 3-year range |
|---|---|---|
| Parker-Hannifin (mfr) | 36.9% | 33.7 – 36.9% |
| Helios Technologies (mfr) | 32.3% | 31.3 – 32.3% |
| Applied Industrial (dist) | 30.3% | 29.2 – 30.3% |
| DXP Enterprises (dist) | 31.5% | 30.1 – 31.5% |
Spiese's 35% manufactured margin sits inside the Parker band; 29% distributed sits at the bottom of the Applied/DXP range, as a regional shop without their scale would.
Census M3 — inventory composition
U.S. Census Bureau, Manufacturers' Shipments, Inventories and Orders (M3), Table 6, Machinery (NAICS 333), seasonally adjusted, May 2026 preliminary. Materials 45.97% / WIP 24.28% / finished 29.75%. The manufacturing half of Spiese uses this profile; the distribution half is 100% finished goods; the two are blended by the derived manufacturing share of inventory (79.9%).
BLS OEWS — inside sales wage
BLS OEWS via the public data API, Milwaukee-Waukesha MSA, SOC 41-4011 (technical/scientific sales), 2025. Annual median $77,500 used (the mean, $90,260, spans field reps and overstates an inside desk). This is total cash wage; employer benefits and payroll taxes are added via the 30% burden driver, so nothing is double-counted.
Published studies — manual data-entry error rate
The order-keying error rate (2.5%) is grounded in the manual data-entry literature. James A. Mays & Patrick C. Mathias, "Measuring the rate of manual transcription error in outpatient point-of-care testing," JAMIA 26(3), 2019, pp. 269–272, measured a 3.2–3.7% mistranscription rate per entry across 6,930 point-of-care results. Kimberly A. Barchard & Larry A. Pace, "Preventing human error: the impact of data entry methods on data accuracy and statistical results," Computers in Human Behavior 27(5), 2011, show that single (unverified) entry is materially more error-prone than double-entry or review. Spiese's 2.5% is an order-level rate (an order that ships wrong); order entry touches several fields, but catching and correcting before shipment pulls the shipped-error rate back down – so 2.5% is credible and conservative against those low-single-digit per-entry figures. Substitute your own credit-memo-to-orders-keyed ratio.
How much you can trust this page
Every figure is computed by formula from a small set of driver inputs, so the page cannot contradict itself: eighteen internal cross-checks run on every rebuild – segment COGS reconciles to total COGS, inventory composition reconciles to average inventory to the dollar, the channel mix and the two order streams reconcile, and twelve ratios fall inside plausibility bands drawn from the comparables above. All eighteen pass.
Where a figure rests on a judgment, we have named the judgment rather than hidden it – that is what the Basis column is for. No number on this page is a placeholder or a guess we are still trying to justify: each is sourced to a public benchmark, derived from ones that are, a stated decision you should replace with your own, or a size point too small to change the argument. That is the whole point of publishing it. If a number here matters to your own case, take ours as a worked example and put your own in its place.
This page backs the series "AI, meet ERP." Every figure cited in the posts about Spiese Fluid Power traces here.