Multi-Hub Distribution Network Software

Multi-Hub Network Management is one map and dashboard over the stores, suppliers, hubs, links and routing tables a delivery network is made of. It shows network status, shipment flows and resource utilization, identifies bottlenecks and suggests changes rather than making them, and balances workloads across facilities and routes within the service level agreements you have made.

A distribution network is not a list of buildings. It is nodes that each do a different job, links that run on their own days and cut-offs, and rules deciding which node serves which order. Most operations hold that model in three places at once: a spreadsheet of sites, a routing tool that knows lanes but not stock, and somebody's memory of the rest.

The objects the network model holds

Four kinds of thing sit on the map — stores, suppliers, hubs and links — plus the routing tables that decide what is served from where. The nodes are not interchangeable, and the difference is operational. A stocking distribution center holds inventory and can absorb a late inbound by covering from stock. A cross-dock node holds nothing for longer than a shift: freight arrives, is sorted to an outbound door and leaves, so a late inbound there does not build a backlog — it produces a missed outbound the same night. A store is a destination and, once returns start, an origin. A supplier is where replenishment enters the network, and the node you control least.

A link is Shyftbase's own word for the edge between two nodes, and the published copy names links without defining them. What a link record has to answer is worth being exact about: which two nodes it joins, which days it runs, what time it closes, how long it takes, and what it costs to run. Those five are what let you plan against a network rather than look at one, and which of them a link stores is worth asking to see rather than assuming.

Routing tables sit above the nodes and links. The routing engine can route by zone, and it can be pointed at part of the day's book instead of all of it — the shape most rollouts take, one region planned automatically while the rest stays manual. Which is why service areas want owners and effective dates rather than a list of ZIP codes in somebody's spreadsheet.

What the map is for on a normal Tuesday

Three classes of live data are surfaced over maps, dashboards and reports: network status, shipment flows and resource utilization. They answer three questions in the order an operator asks them. Is anything late or at risk now. Where is volume moving today against where it normally moves. Which facilities, docks and vehicles are full, empty or idle while that happens. The value of one view is that the third answer arrives with the first, while a load can still be moved.

Reporting is self-managed rather than a services engagement: analysts build and change their own dashboards, and data can be exported or fed into the tools a business already reports in. The grid ships real reports rather than an empty canvas — one is Accounting Overview Per Day, whose columns run Delivery day, Invoiced, Settled, Unconfirmed, Confirmed, Billing, Payable and Margin, filterable and exportable by day. That column list is a tell about the data model underneath: the operational record and the money record are the same record, which is what a network map bolted on top of a TMS cannot do.

What is not published is what real-time means here. No refresh interval is stated and no feed is named, and driver-app pings, a telematics feed and a nightly ERP poll are three different products wearing one adjective. Ask for the interval, the feed behind it, and what the map draws when that feed is late: a stale vehicle position drawn confidently is worse than an honest gap.

Bottlenecks: what it flags, and what it will not decide

The stated mechanic is narrow and worth reading exactly as written: the system continuously analyzes network performance, identifies bottlenecks and suggests optimizations, and balances workloads across facilities and routes while holding to the service level agreements you have set. The verb is suggests. Nothing there says the network re-plans itself overnight, and the honest reading is decision support — something arriving in a queue for a person, not an action taken while the yard is closed.

That decides how it has to be staffed, and it is where these deployments fail. A suggestion with no owner becomes a color on a dashboard: week one it is discussed, week two acknowledged, by week four it is furniture everybody reads past. The fix belongs in the rollout plan — one named owner per class of flag and a response window in hours, so clearing an alert is somebody's shift rather than everybody's intention.

What counts as a bottleneck is not published either, and that definition is the product. Dwell above a threshold, utilization above a level, and predicted breach of a delivery window are three alarms with three different false-positive rates, and only the last is worth waking someone for. Ask which is implemented and what an operator can tune. Execution lives next door, deliberately: re-sequencing a day's stops is route optimization, and moving freight between the nodes is mid-mile movement between hubs. This layer notices, and says which node the problem is in.

Changing the network without waiting for a release

Network structure, routing rules and service areas can be modified directly, and operations then adapt to reflect the change. It is the most useful claim on the page and the one with the most left unsaid. Three questions decide whether it is safe. How fast does a change propagate. Is work already planned or in flight re-pointed, or left on its original plan. Can a change be reviewed, dated and reversed by someone who did not make it. None of the three is published.

The consequence is concrete. Move a ZIP code from the south hub's service area to the north hub at 14:10 and there are two possible tomorrows. If in-flight work re-points, freight already staged at the south dock is planned against a truck that will not be there, and the exception surfaces at load time in the dark. If it does not, you run split behavior for a day, which is safer and which nobody has told the customer service desk about. Neither is wrong; being unsure which you have is.

So make structural edits at a cut-off boundary, name the effective date rather than relying on the moment of saving, and keep one person able to reverse it. And check what else the edit touches: the billing module keeps rate tables and zones of its own, so a service area that moves while the rate table stays put becomes an invoice argument a month later about freight delivered perfectly. Whether the two read one definition of a zone is worth confirming against your own configuration — automated billing and the network view describe the same movement.

Where hubs go, and what actually constrains them

Network structure is bounded by three things that do not negotiate — driver hours, weight and time at the dock — and a map invites you to reason in radiuses, which none of the three respects.

Driver hours come first, because whether a link can be a one-driver out-and-back is a legal question before an operational one. Read the day as a budget with two ceilings: a 14-hour shift, which opens only once the driver has had ten consecutive hours off, and no more than 11 hours of driving inside it^[hos]. Dock time, waiting and paperwork spend the shift rather than the driving budget, which is how a hub whose trailers queue at the door quietly shrinks its own catchment. Across a week the ceiling switches to on-duty time — 60 hours in any 7 consecutive days for a carrier not running every day — and a half-hour break falls due once 8 hours of driving time have passed^[hos], unless the driver qualifies under the short-haul exception^[hos]. So a hub's real catchment is the set of nodes reachable and returnable inside that budget, handling included, and it is always a smaller shape than the circle drawn on the map. Line-haul legs beyond it need a relay, a meet point or a night out, each a standing cost line.

Weight comes second, and it is what a consolidation plan runs into. Interstate gross weight is capped at 80,000 pounds, and lower again wherever the bridge formula bites^[weight]. A network consolidating dense freight hits that ceiling long before the trailer is full; one moving light, bulky freight fills to cube and never approaches it. The same hub layout can be right for one product mix and wrong for another, which makes "we will consolidate more" a claim to test against your own weight per cube.

Cost comes third, and the other two feed it. The American Transportation Research Institute measured the 2025 industry average at $2.336 a mile all-in, and $1.854 a mile once fuel is taken out^[atri]. Check the population before borrowing either figure. The sectors that release reports margins for are truckload, refrigerated, tank, LTL and flatbed^[atri]; it names no final-mile or parcel sector, and the survey population itself is stated in the report rather than in the release. For a delivery fleet the number sizes a lane rather than sets a rate. Two lines the network view moves and a fuel report cannot see belong in the same sum: deadhead miles on the return leg, and detention at the dock, where a hub that cannot turn a trailer sets the cost of every link touching it. What a bought lane finally costs, once those accessorials are agreed and paid, is the payables side. If routing rather than network shape is the question, what route optimization actually saves works that arithmetic through.

What this does not do

It is not a network design study. No facility-location solve, no greenfield model, no scenario comparison against a cost objective — a different tool, at a different cadence, run by different people.

It suggests; it does not decide. Every optimization surfaced is a recommendation to a person, and expecting an autonomous network is the fastest way to be disappointed by software working exactly as described.

Supplier self-service is unresolved, and this is where the question lands. Suppliers appear here as nodes: their sites, their lanes, what they feed. The retired supplier-portals page published something more specific — a supplier-facing entry point, supplier data held in one place instead of in email and spreadsheets, automated routine communications, shared portals, supplier performance monitored with analytics and reports, guided onboarding with automated documentation, and externally shareable views with an access-management module behind them. None of that appears in the capability list of any surviving module, and which module owns it is not settled. Ask for it by name, and ask which module it ships in; the absence of a page is not an answer either way.

It is not a warehouse system. Receiving, put-away, pick, pack and cycle counts inside the four walls belong to the warehouse management module; this layer treats a node as a capacity, a calendar and a queue.

Scale and latency are unpublished. No maximum node, link or vehicle count, no refresh interval for the live view, no propagation time for a structural change. Ask for all three against numbers from your own network.

No security or compliance claim is made here. Nothing on this page states an encryption standard, a certification, a data residency or a retention policy, and nothing here should be read as one. Nor is how master data reaches the model from the systems Shyftbase already connects to published. Both are demo questions.