Real-Time SKU & Inventory Tracking Software
Real-time inventory tracking software that records where each unit was actually seen and when, compares it with where the system says it should be, and routes counts and picks around the difference before a picker reaches an empty bin.
Schematic
Location hierarchy and scan ledger
How a bin's balance is built from the scans that moved stock in and out of it.
Real-time inventory tracking software that can measure its own error
MileSoft Inventory Tracking keeps an observational record of where each unit actually is and when it was last seen, alongside the warehouse's record of where it should be. Handheld barcode scans, RFID, and fixed readers at zone boundaries and on conveyors update that position as stock moves, so the difference between the two records — inventory drift — is visible continuously instead of being discovered at the next count.
When the records disagree, the system raises work rather than a report. A count task is dropped into the queue of a picker already nearby, and a pick about to be issued against a drifted position is re-routed, so pickers stop walking to empty bins. Every move is kept with who made it, when and why, which turns a wrong location from a mystery into a traceable cause.
Locations run from site down to bin, so the same model covers one building or several, and inter-site transfers are ordinary moves. In the published warehouse deployment, a multi-client 3PL moved from about 91% to 99.4% inventory accuracy — one operator, from a manual-bin-check baseline, with no denominator stated.
Real-time inventory tracking
Two ledgers: what the system says should be there, and what was actually seen
There are warehouses where "we have it" means the system says so, and warehouses where it means someone can find it.
Every warehouse keeps two ledgers over the same building. The prescriptive ledger updates when an instruction is issued or confirmed — a putaway completed, a pick confirmed. It is complete about intent and blind to everything else. The observational ledger updates when a unit is seen — a handheld scan, a fixed reader at a zone boundary, a conveyor read. It is complete about coverage and blind to intent. They agree until something moves without an instruction.
A facility keeping only the first ledger owns no instrument that can measure its own error. Its drift set is empty by construction, not because it is accurate — which is why it finds out how wrong it was at the next count.
Neither ledger simply corrects the other. A unit last read at a zone entry three hours ago may have moved twice since, so each observed position carries the time it was last seen, and disagreement is weighted by that age. Staleness is not drift. And because every move is kept with its actor, time and reason, drift becomes diagnosable, not just detectable: "last read leaving zone C at 14:20 by a fixed reader, with no putaway instruction" is a cause.
Where it fits
Inventory tracking, WMS, tagging and control answer four different questions
Each is blind where another sees, which is why a facility usually needs more than one.
| System | The question it answers | Its record |
|---|---|---|
| Warehouse management | Where should this be, and may this movement proceed? | Prescriptive — guarded transitions |
| Inventory tracking | Where is this actually, and when was it last seen? | Observational — sensor events |
| Annual inventory tagging | What is here, exhaustively, as of a stated date? | Periodic census |
| Inventory control | How much should we hold, and what is not moving? | Analytical — over the enterprise record |
The prescriptive ledger cannot detect what moved without an instruction; the observational ledger cannot see where no reader is; the census sees everything once a year. For what real-time SKU tracking means in practice, see real-time SKU tracking, explained.
RFID and barcode
Why a team that scans diligently still has inventory drift
Diligent scanning covers the movements that have process steps. Drift comes from the ones that do not.
The important division is not RFID against barcode but whether a person is involved. An operator scan is an active read: it costs a second and happens where a process step requires it. A fixed reader is a passive read: it costs nothing per event and happens wherever stock crosses an instrumented boundary — including when nobody intended anything. Passive reads catch exactly the movements no process step would ever record.
They fail differently too. A barcode scan fails loudly — nothing is recorded and the operator sees it. A gate read fails quietly, reading fourteen of fifteen tags and producing a record that looks complete.
| Channel | Fires when | Blind to |
|---|---|---|
| Fixed reader | stock crosses an instrumented boundary | movement within an uninstrumented zone |
| Scan on pick | someone picks from that face | slow-moving and dormant stock |
| Cycle count | the schedule reaches that location | everything, between visits |
Worked example: how long a wrong record survives
With cycle counts at 4 per location a year: a fast mover crossing boundaries 90 times and picked 260 times is found in about a day; a slow mover crossing 6 times and picked 9 times in about 19 days; a dormant unit in about 91 days. A single accuracy percentage is dominated by the first case — so a facility reporting 99.4% while holding 15% of its value in dormant stock should be asked for the figure on that 15% alone. It will not be 99.4%.
Pre-emption
Finding drift before the picker walks to an empty bin
Travel dominates picking time, so a failed pick spends the expensive part and gets nothing.
When the two ledgers disagree, the system raises work rather than a report: a count task goes into the queue of a picker already nearby, and a task about to be issued against a diverged position is re-routed. Nobody scans or walks differently — tasks are simply issued against a better estimate of where things are, and counting happens without an operational freeze.
Worked example: what one pre-empted exception is worth
A picker walks 55 m at 1.1 m/s (50 seconds), then spends 3 minutes searching and 90 seconds re-sequencing, with a 12% chance the order ships short at a cost of 240. At 0.09 per second of loaded labour, the exception at the face costs 28.8 in labour plus 28.8 in short-ship risk = 57.6. A lookup at task generation costs almost nothing.
Half that cost falls outside the building — on a customer, a service level, a penalty clause. A model counting only picker time undervalues pre-emption by a factor of two. At 91% accuracy and 4,000 picks a day, about 360 picks meet a drifted position; pre-empting 80% of them is worth roughly 16,600 a day in this model.
Reader placement
Where a fixed RFID reader should go, and where no reader will help
Coverage of the movement flow is the design variable, not the number of readers.
A facility records 240,000 unit-movements a year: 96,000 cross four zone boundaries, 62,000 cross the conveyor, 82,000 are relocations within a zone. Readers on the zone boundaries cover 40% of movement; adding the conveyor takes it to 66%. Detection improves in proportion to coverage, so the conveyor readers are worth about two thirds of the zone readers and should be priced against that, not against their unit cost.
The within-zone third is the honest limit. No boundary reader reaches it; those movements are found by pick scans and counts. A facility whose drift is mostly within-zone relocation is buying the wrong instrument if it buys more readers.
Field evidence
The published accuracy result, and the three caveats that belong with it
The clearest single-product attribution in the warehouse suite, reported carefully rather than enthusiastically.
A multi-client third-party logistics operator ran inventory accuracy at about 91% — roughly one pick in eleven involving an exception, with service-level penalties from an anchor client eroding margin. After deployment it reported 99.4%. The published account attributes this to this module: handheld and RFID capture replaced manual bin checks, counts ran as exceptions alongside picking, and drift was flagged before a picker reached an empty bin.
One operator, low starting point
The 91% baseline describes a facility doing manual bin checks.
No denominator published
Accuracy over locations, over units and over picks are three different measurements, and the account does not say which.
Detection is uneven
Continuous detection concentrates on what moves, so a figure weighted toward frequently visited faces overstates accuracy on dormant stock.
The same deployment's dock idle, truck dwell and client onboarding results belong to other modules and are not claimed here. The full account is in the warehouse case study.
Evaluating tracking software
Eight questions to put to any inventory tracking software
Each is answerable by demonstration — including by us.
| # | Dimension | Ask the vendor to demonstrate |
|---|---|---|
| D1 | Two independent records | Is the observed position derived independently, or written by the same transaction? |
| D2 | Drift reported | How many units are currently in the drift set, and what is that as a percentage? |
| D3 | Observation age | Does a position carry the time it was last observed, or only the position? |
| D4 | Passive coverage | What fraction of movements cross an instrumented boundary? |
| D5 | Pre-emption | Move a pallet without an instruction. Is the next task issued against the old position? |
| D6 | Quiet-failure detection | Does the system notice a gate reading fourteen of fifteen tags? |
| D7 | History with cause | For one drifted unit, can it show the last observation and the missing instruction? |
| D8 | Stratified accuracy | Report accuracy separately for fast, slow and dormant stock. Do the three agree? |
D1 decides whether the product is real. A tracking layer written by the same confirmation that updates the warehouse record is not a second observer — it is the same ledger with a second name, and its drift set is empty by construction.
Standards referenced: ISO/IEC 19987 (EPCIS) and 19988 (CBV), GS1 General Specifications and SSCC, ISO/IEC 15459-1, ISO 5725-1 and -2, ISO 22400-2, IEC 62264-3. Derivations are in the inventory tracking method paper.
Features
Key Features
Built-in capabilities that set our software apart
Observational location record
SKU-to-bin position with the time each unit was last seen
Barcode and RFID capture
handheld scans plus fixed readers at zone boundaries and conveyors, mixed by zone
Drift detection
disagreement between expected and observed position, weighted by observation age
Counts as exceptions
count tasks inserted into nearby pickers' queues, with no operational freeze
Pre-emptive re-routing
picks issued against the observed position rather than a drifted one
Movement history
every move with actor, time and reason, and velocity data for re-slotting
Multi-site locations
site down to bin, with inter-site transfers as ordinary moves
Benefits
Key Benefits
What your team gains from adopting our platform
Testimonials
What Our Clients Say
Trusted by industry leaders across manufacturing, HVAC, and logistics.
"The software features, such as real-time monitoring and alerts, have proved invaluable in optimizing machine operations. MileSoft team's professionalism, technical expertise, and dedication to meeting our requirements have been impressive."
FAQ
Real-Time SKU & Inventory Tracking Software — FAQs
Answers to the most common questions about this product. Need more? Book a demo or reach out via Contact.
How is tracking different from a WMS?
Do we need RFID, or will barcodes do?
Why do we still get errors when the team scans everything?
Can we track stock across multiple sites?
How current is the data?
What is real-time SKU tracking?
Can we see inventory location in real time across sites?
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Related Reading
Go deeper
Explore the long-form story behind this product.
What Should Be There and What Is: The Two Ledgers a Warehouse Keeps, and the Drift Between Them
Architecture, Computational Methods, and Field Evidence from MileSoft Inventory Tracking
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Ask any tracking system the eight questions, starting with ours
Bring a week of pick exceptions. We will show where drift is coming from, which movements a fixed reader would catch, and what accuracy looks like for your dormant stock.