UpSynQ.

The decision layer above the system of record.

Most of your operational decisions are made in spreadsheets, on calls, in DMs. The system below them captures the result, never the rationale. UpSynQ sits above your existing stack and moves those decisions into a layer the system can see.

MAEU 4827 TCLU 3618 CRSU 9114 HLBU 2057 NYKU 8843
The view from above the system of record Illustration: UpSynQ, 2026

Most enterprise decisions are made outside the system of record.

They happen in spreadsheets, on calls, in DMs at midnight. By the time a decision reaches the ERP, the planning tool, or the EMR, it is a record, not a choice. The system captures what was decided. It does not capture how, by whom, against which alternatives, or with what consequence.

One week of operational decisions 14 outside the system
14 outside the system of record 10 captured inside it Hover any cell for the example decision
Pattern observed across the first dozen UpSynQ audits The brick-red cells are how operational work gets done.

The pattern holds across stacks

SAP, Oracle, NetSuite, Dynamics, Infor. The ERP is not the problem. The gap between the ERP and the planning function is.

Six categories of mechanical work

The decisions that fall outside the system cluster into six kinds: forecast overrides, exception chase, reconciliation, status reporting, tool maintenance, scenario calls.

Long-run distribution, not week-to-week

A planner's specific week shifts. The distribution of where their hours go — across months, across an operation — does not.

A single decision, traced through the operation.

Pick a source decision. Watch the cascade. Toggle With UpSynQ to see the same decision when the system can see it — the alternatives that get considered, the downstream cost that does not happen.

One decision · downstream
Pick a source
Operational cost
$0
Without UpSynQ

UpSynQ sits above the stack you already have

UpSynQ sits above the tools you already run. The ERP keeps doing what it does. The planning tool keeps doing what it does. The decision now lives somewhere they can both reference, with the rationale, the alternatives, and the downstream impact captured at the moment of commit.

How it fits No rip-and-replace
DECISIONS · RATIONALE · ALTERNATIVES Q4 forecast rebalance SKU-4471 override Expedite request Capacity swap 15% production lift UpSynQ decision layer CAPTURES RATIONALE · SURFACES ALTERNATIVES · TRACKS DOWNSTREAM · LEARNS FROM OUTCOMES EXISTING STACK · UNCHANGED ERP SAP S/4 Oracle NetSuite Planning Anaplan Kinaxis Excel MES Plex Aveva Rockwell Trading Yes Energy Powerbid In-house EMR Epic Acumen Cerner ↓ DECISIONS COMMIT TO EXISTING SYSTEMS  ·  ↑ OUTCOMES FEED BACK TO LEARN
Read-only integrations to begin. Bidirectional learning loop after pilot. No cutover required.

Where we run today

We work in three places where the gap between “system of record” and “system of decision” is structurally large.

SCM / S&OP

Supply chain & demand planning

For enterprise teams running SAP, Oracle, NetSuite, or Dynamics with planning on Excel. The next Demand Planner you hire will spend ~60% of the week on data reconciliation, not planning.

The planning audit →
ENERGY MARKETS

Energy markets & power desks

For battery IPPs, merchant generators, retail providers, VPPs. Half the imbalance cost lives in the handoff between forecast, dispatch, and the bid stack, not the model.

The power audit →
CHRONIC CARE OPS

Chronic care scheduling

For multi-site dialysis, oncology infusion, IV biologics, PT networks. The typical center silently moves 15–25% of weekly visits to days the patient did not choose.

The throughput audit →

What we found in three different operations

Three audits, three sectors, three different stacks.

What we found, anonymised 10 weeks to value
Functions
Forecasting, Inventory & Replenishment
Scale
~1,800 SKUs · 2 planners
ERP
SAP S/4HANA
Cutover
None required
Planner reconciliation time per cycle 4–6 hrs → < 15 min
Forecast accuracy, top-200 SKUs +18 pts
OTIF low-60s → 91%
ERP changes required None
The audit surfaced first not a planning problem but a reconciliation problem. Two planners, every cycle, disagreed on which spreadsheet was authoritative. The reconciliation gain showed in the first three weeks; the forecast accuracy gains came later.
What we found, anonymised 14 weeks to value
Operator
ERCOT battery IPP
Scale
200 MW operational
Settlement
5-minute, ERCOT
Cutover
None required
Avoidable imbalance cost -32%
Reconciliation overhead per shift 40–50% → < 10%
Trading desk strategic hours per week +10 hrs
Settlement-query volume 60% → 8%
When we walked back from settlement, the model wasn't the issue — 76% of avoidable loss lived in the handoff between forecast, dispatch, and the bid stack. Closing the loop with the existing tools intact moved the number more than three forecast refits had.
What we found, anonymised 4-week shadow pilot
Network
Regional dialysis chain
Pilot scope
One center · 4 weeks
Operational risk
Zero (shadow mode)
PHI required
None
Silent shuffles per week ~78 → 4
Clinical lead-time absorbed ~4 hrs → near-zero
Day-preference adherence → 95%+
Annualised value, single center $120–250k US
Shadow mode — four weeks of parallel scheduling with no operational change — surfaced a Saturday drift the team didn't know they had. 78 patients/week silently moved off their day preference. The parallel schedule resolved 95%+ of those shuffles in the planning step.

Which audit fits your operation?

Each is 45–60 minutes on a call, a 3- or 4-page written diagnostic returned within 48 hours, and one honest paragraph on whether UpSynQ would actually help. Founder-delivered. Free.

PLANNING

The planning audit

45 minutes · 3-page diagnostic. For SAP / Oracle / NetSuite / Dynamics teams running planning on Excel.

Request →
FORECAST

The power audit

60 minutes · 4-page diagnostic with imbalance-cost attribution. For battery IPPs, merchant gen, REPs, VPPs.

Request →
THROUGHPUT

The throughput audit

60 minutes · 4-page diagnostic plus shadow-mode pilot spec. For dialysis, oncology infusion, IV biologics, PT.

Request →