Fuller
In-stock rate on priority SKUs
Cross-channel real-time demand signal plus DNOVA™ automation — across all channels simultaneously.
“Why are our priority SKUs out of stock online when we have inventory in store?” — answered in seconds, with our recommendations on what actions to take in your channel allocation and systems.
Datanoetic makes cross-channel demand visible in real time — and DNOVA™ automates the responses. Configured to your DC's process steps, your channel SLAs, and your carrier relationships — not a generic retail template.
The improvement, KPI by KPI.
DNAI™ resolves today's incident; DNOVA™ removes the cause for good.
Shorter
Fulfilment cycle time
Cross-stream bottleneck detection from inbound through pick to despatch.
Direction of improvement shown; we model the numbers on your value stream in the first 30 days. Results depend on operational baseline, data connectivity, and deployment scope.
Where omnichannel operations lose value. And how Datanoetic closes each gap.
Gap 01
Inbound throughput drops — and the cross-channel impact is only visible after the stockout.
The challengeWhen Dock B throughput falls 26%, the impact on which channel goes short, and when, is not visible in the WMS. The inbound system knows the delay. The OMS knows the order position.
Neither knows they are connected — or that the online channel for SKUs 1102–1108 will show a stockout in 1.8 hours if nothing changes.
How Datanoetic closes it
DNAI™ KPI Guard monitors every published VSM node continuously. When inbound throughput at Dock B drops below threshold, an Insight Card surfaces on that specific node — identifying the contributing carriers ranked by volume impact, the downstream channel exposure, and a recommend-and-confirm action awaiting operations manager approval.
Gap 02
Your WMS, OMS, and carrier feeds are siloed. No single view connects the cross-channel operation.
The challengeA 3PL DC running omnichannel fulfilment generates data across five or six systems — each knowing part of the story. The WMS knows inbound volumes. The OMS knows channel order positions. The TMS knows carrier ETA.
None of them know how a carrier delay translates into a channel-level stockout — until it has already happened.
Four systems · one cross-channel view
WMS OMS TMS Returns
Dock B · inbound · live
One live view — every feed on the step that owns it.
Read-only connections — your systems stay in place.
How Datanoetic closes it
Datapro-V™ maps your end-to-end DC as a live VSM — inbound docks, sort lanes, channel fulfilment streams, and carrier links all connected. Read-only connectors to WMS, OMS, TMS, and returns systems feed a single tenant-isolated data layer.
Nothing is replaced; the cross-channel view is assembled from what already exists.
Gap 03
Generic AI tools give general answers. They don't know your DC, your carriers, or your channel split.
The challengeGeneral-purpose AI assistants can describe omnichannel best practices. They cannot tell you that Dock B throughput is down 26% because Carrier R-02 is running 79 units late, that this will create a stockout for SKUs 1102–1108 in the online channel in 1.8 hours, and that the operations manager needs to approve a wave-planning adjustment in the next 20 minutes.
Same question, two answers
Generic assistant General industry knowledge
Inbound throughput usually slips because of carrier performance, labour availability or dock scheduling. Reviewing your carrier SLAs and the staffing plan for the shift is a good starting point.
DNAI
Carrier R-02 is running 79 units late — SKUs 1102–1108 go short online in 1.8 hours.
Grounded in your operation — every answer cited to source records.
How Datanoetic closes it
DNAI™ reasons from your Knowledge Graph — every carrier, every dock, every SKU class, every channel SLA threshold — not from general training data. KPI Guard generates hypotheses grounded in your process graph, not retail templates.
DNAI™ Chat answers operational questions in plain language, citing the specific records it used and the lineage behind every figure.
How the workflow changes.
Flagged by the customer — after the impact
Demand shifts channels overnight. Replenishment runs on yesterday's data.
Carrier R-02 runs late and Dock B throughput falls 26%. The first signal is a gap in the online channel — flagged by the customer, not the team.
DNAI™ surfaces the Dock B throughput drop in real time, identifies the carrier delay, and flags the cross-channel stockout window: 1.8 hours for SKUs 1102–1108.
The operations manager confirms the wave-planning adjustment. Stockout prevented before the channel goes live.
Caught in real time — before the channel goes live
The same cross-channel stockout cannot recur.
After eight weeks of DNAI™ data, DNOVA™ identifies the pattern: cross-channel stockouts for priority SKUs (1102–1120 class) occur when Carrier R-02 or R-07 run more than 90 minutes late and online channel sell-through exceeds 40% of available stock.
DNOVA™ proposes an automated cross-channel stock reallocation rule — triggers when both conditions are met, reallocates online-channel stock to the shared pool, notifies store replenishment and online fulfilment simultaneously.
Merchandising director approves. Rule codified and deployed. Next R-02 delay: no stockout. DNOVA™ monitors for new trigger conditions.
Automation design codifies each validated action into a standing rule — every rule gated by human sign-off, never autonomous.
Explore the platform30 minutes. One scenario. Your DC data.
We'll walk your team through the Dock B throughput scenario on a sample VSM that mirrors your omnichannel DC — and one KPI you wish you could explain in real time.