Know the quarter before it ends.
Load targets at scale, measure attainment down to the SKU, see coverage down to the doctor — and get a forward-looking quarter projection with reasons, computed with pure math at zero AI cost.
Five thousand targets in one upload.
Set net-value targets per territory, period, and SKU — singly or in bulk up to 5,000 rows per upload, idempotently. Authorization follows the org tree: a manager can only ever touch targets inside their own subtree.
Per territory × period × SKU · re-upload safely (idempotent).
Goals that cascade — and reconcile.
Set a top-down net-value goal on any org unit — Area, Province, National, BU — distinct from per-territory targets. Then check whether a manager’s territories actually sum to their goal, before the quarter answers the question for you.
-₨ 6M gap territories don’t yet sum to the goal.
"Are we hitting target on this brand, in this territory?"
Product-stamped sold lines join to per-SKU targets for a precise sold-vs-target answer — with an explicit coverage caveat showing how much sold volume was crosswalk-matched. The number tells you its own confidence; it is never over-promised.
Coverage caveat: 92% of sold volume was crosswalk-matched.
Every person. Every level. No double counting.
Your org subtree as a tree: each node carries its own and cumulative sold-vs-target and an attainment ratio, with a guard against double-counting reps who share a territory. Evaluate the individual and the rolled-up team in the same view.
- National · cumulativeΣ all territories96%
- Punjab · Areaown + cumulative82%
- Lahore-North · repshared territory guard58%
The doctors you're missing, by name.
Per-rep frequency coverage is driven from the doctor list itself — so a zero-visit doctor surfaces as “behind,” not as silence. It’s the daily coaching tool: exactly which customers are under-visited against their required call frequency.
- Dr. Bilal · 0 of 4 visitszero-visit → behindbehind
- Dr. Sana · 2 of 4 visits50%
- Dr. Omar · 4 of 4 visitscovered
The whole fleet in one fast call.
One server-side pass walks the entire subtree: every rep’s coverage, visits, unique doctors, adherence, and no-shows; every territory’s secondary sales — aggregated with correctly weighted coverage percentages, sorted most-behind-first, and folded together with the forecast outlook. One payload. One screen. Who needs attention today.
- Lahore-North · Ahmed R.58%
- Karachi-East · Sana M.74%
The quarter, projected — with reasons.
Dexor projects full-quarter attainment from quarter-to-date run-rate, computes month-over-month momentum, and issues a risk verdict — critical below 60%, warning below 85% — that escalates only when a real signal opens: negative momentum, declining coverage, rising no-shows. Pure math. Zero model cost. No black box.
- Verdict: warning< 85% projectedat risk
- Momentum -6% MoM · no-shows upescalation signals openescalated
Pure math · zero model cost.
What needs attention, ranked.
Plain-language findings and at-risk territory flags derived from the same team-performance data — attainment thresholds, momentum, escalation signals, statistical anomalies — plus an optional pre-computed AI executive summary on top. Managers get the single highest-priority action without any AI spend.
- Lahore-North below 60% — act firstcritical
- Coverage declining in Karachi-Eastwarning
- Faisalabad ahead ≥ 100%ahead
Deterministic · $0 per-use. Optional ✦ AI summary sits on top.
Dexor intelligence
Layer grounded AI — Ask Dexor, weekly executive summaries, and targeted notices — on top of the free deterministic baseline.
Dexor intelligenceSell-out intelligence
Feed reconciled net secondary sales into SKU-precise attainment and territory rollups.
Sell-out intelligence