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Usage accelerates
Current stock can look comfortable while consumption is changing underneath.
STOCKOUT RISK & INVENTORY INTELLIGENCE
See the risk.
Before the
stockout.
The warning signs are already there.
Inventory Watchdog helps you see them.
A practical intelligence layer alongside your existing ERP. For the people keeping mining, industry and operations moving.
EARLIER VISIBILITY. CLEARER PRIORITIES.
THE QUESTION THAT MATTERSWill replenishment arrive
before stock runs out?
before stock runs out?
Illustrative visual · Inventory risk intelligence
01 / THE HIDDEN EXPOSURE
A shelf can look safe.
The pattern tells another story.
Stockouts often leave a trail long before the shelf is empty. Inventory Watchdog brings scattered warning signs into one view.
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Delivery slips
An open purchase order offers little protection if it arrives after the forecast stockout.
≈
Averages reassure
Unstable usage or unpredictable lead times can disappear inside a simple average.
!
Operations feel it
Maintenance and production face the consequences. Earlier visibility creates time to respond.
ONE CONNECTED VIEWFrom a stock position
From a stock position
to a procurement decision.
Combine available stock, consumption, PO coverage, expected delivery, criticality and supplier reliability. Understand what is driving the risk, then decide what deserves attention first.
↗02 / INSIDE THE WATCHDOG
The big picture.
The detail to act.
Explore 12 connected report views from the presentation. Select a view to see how insight becomes action.
MANAGEMENT VISIBILITY
Executive Control Tower
Original Power BI screenshots from the supplied deck. These are report previews, not a live client connection.
URGENCY HAS A LANGUAGE
P1 Immediate action
P2 Urgent follow-up
P3 Watch closely
P4 Information only
03 / BEYOND THE AVERAGE
Same average.
Very different risk.
An average tells you the centre of a pattern. Variability tells you how much confidence to place in it. Try the examples from the presentation.
Can you trust the average?
Standard deviation measures the spread. The coefficient of variation (CV) expresses that spread relative to the mean.
CV = standard deviation ÷ average × 100%
Illustrative examples use sample standard deviation (n − 1), calculated from the deck’s five observations. CV is undefined when the average is zero.PRESENTATION’S INDICATIVE CV GUIDE
0–25%Stable
>25–50%Moderate variability
>50–100%High variability
>100%Very unstable
Review thresholds against item criticality, data history and your operating context.04 / A WINDOW TO RESPOND
Stock on hand.
Time running out.
Move the assumptions. See how a comfortable stock position can become a replenishment gap.
Illustrative scenario only. Starts with 200 units, constant daily consumption and no receipts before delivery. It demonstrates the timing question, not the full Watchdog model.
REPLENISHMENT SCENARIO
Stock cover20 days
Timing margin5 days
Projected stock Expected delivery
05 / THE STORY IN 3:44
Spot the danger.
Before the stockout.
Watch Tara Nawa’s introduction to inventory risk intelligence, then explore the chapters that matter to your team.
JUMP TO AN IDEA
Watch on YouTube ↗Video loads from YouTube when you press play. You can also open it directly if embedded playback is unavailable.06 / INSIGHT WITH A NEXT STEP
Every signal should
lead somewhere.
The value is in the follow-through. Give buyers, stores and management a clear place to focus the next conversation.
Create an RFQ
or purchase order.
Where stock cover is weak and replenishment is missing, start the procurement review.
Expedite an
open order.
Where expected delivery follows the stockout date, confirm dates and follow up earlier.
Review alternative
suppliers.
Where delivery patterns create exposure, discuss supplier reliability and sourcing options.
Strengthen the
source data.
Correct missing criticality, lead times, reorder information and expected delivery dates.
SOCExplore e-Procurement ↗
Recurring risk can reveal a catalogue opportunity.
Identify repeatable, high-value or high-risk items that may benefit from supplier discovery, pricing visibility and Tara Nawa’s Smart Online Catalogue.
07 / YOUR DATA. YOUR RISK PROFILE.
What is hiding in
your inventory?
The strongest demonstration starts with your own approved data sample. Agree a focused pilot, review the evidence and build a practical path forward.
Sample extract
Inventory, consumption, open POs, suppliers and item master data.
Load & validate
Prepare the data and check completeness, history and usable fields.
Client-specific review
Explore your risk profile in Power BI and validate findings with your team.
Production roadmap
Agree refresh, security, alerts, responsibilities and any catalogue integration.
Scope, commercial terms and deployment arrangements are agreed before work begins.