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The business

A consumer products business selling through several channels and warehouses, with suppliers on different lead times and deposit terms, and a financing line it would rather not draw on.

What was going wrong

Every decision was argued in percentages and settled by seniority. Cut ad spend by ten percent, push a supplier out two weeks, run the Q4 promotion harder: each one sounded reasonable in a meeting and nobody could say what it did to the lowest cash week, or whether the financing line would be needed to survive it.

Working capitalLiquidityResource allocation

The question it answers

If we change demand, price, lead time, promotion or spend, what happens to liquidity and what does it cost?

Nine drivers at the top, and every section below rewrites itself: the liquidity curve, the financing drawn, the cash conversion cycle, supplier exposure, channel returns and the SKUs underneath.

It turns percentages into dollars and weeks

A ten percent change is an opinion. This says what it does to the lowest liquidity week, in money and in timing, which is the only version a board can act on.

It shows what the decision costs elsewhere

Push a supplier out and the cash improves while the stockout risk moves. Both appear on the same screen, so the trade is visible instead of discovered later.

It separates promotion from advertising

One changes demand, the other is spend. Treating them as one number is why promotional plans look profitable and are not.

It briefs you in words first

An executive summary in plain English sits above the charts, because the person who has to defend the decision needs the story, not the axis labels.

Inventory Liquidity Decision Dashboard

Built to answer one executive question: should the business buy, delay, borrow, promote, or rebalance before liquidity gets tight?
Embedded demo dataset loaded
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The past view uses actual demand plus a model-generated baseline forecast. It is not a separate historical forecast file. Liquidity is a modeled planning view, not a historical cash ledger.
Scenario planner
πŸŽ›οΈ Change a driver here, then scan the sections below to see what changed in the story.
πŸ“¦ Demand change0%
πŸ‚ Q4 seasonality change0%
🏷️ Price change0%
πŸ’Έ Cost pressure0%
🚚 Lead time shift0 weeks
🏒 OPEX change0%
πŸ“£ Ad spend change0%
🏦 Financing limit±$0
πŸ›Ÿ Required cash buffer$0
Executive summary
A human briefing first. Numbers support the story, not the other way around.
Modeled liquidity and financing used
This is the main decision chart. Date range, filters, forecast method, and scenario settings all flow into this view.
Past actual vs modeled forecast
This section stands on its own so the chart is easier to read. Blue shows actual demand only in the historical period. Pink shows the forecast baseline across both past and future so you can compare how close the past forecast was to actuals, then continue into the forward view.
Promotion factor and promo drilldown
Promotion is different from advertising. Promotion changes expected demand or conversion by event, date, product, or channel. Advertising is spend.
Promotion treatment
Use this to decide whether promotion should be taken as loaded, ignored, or adjusted.
Promotion uplift override
Only used when Promotion treatment is set to Apply uplift override.
Reduce expected promo uplift by %
Reduces uplift from low-confidence promotion rows so the plan stays conservative.
Cash Conversion Cycle
Use this to understand whether inventory days, collection timing, or supplier terms are creating the real cash drag.
Range translation
Percent changes should translate into dollars, timing, and impact on the lowest-liquidity week.
Inventory by warehouse
Use the side controls to narrow the story, then read where the inventory value is concentrated.
Supplier exposure
Current inventory value, lead time, deposit policy, and concentration in working capital.
Advertising and channel ROI
The scenario engine changes the global story. This table helps explain which channels are carrying the revenue and margin.
ChannelSpendAttributed revROASForecast revCM %
SKU drilldown
This section should answer which products are actually driving the current story after the selected filters and assumptions are applied.
SKUABCSupplierPrimary warehouseOn hand unitsOn hand value13w avg unitsWeeks of supply13w forecast revenuePO risk week
Ask the dashboard
Use natural language to ask what is driving the current story. This is a prototype Q&A layer built from the current slice and assumptions.
This Q&A layer answers from the dashboard logic and current assumptions. It is not a separate LLM chat tool.
Forecast method and model trade offs
This section explains the live browser method, the recommended production method, the data readiness behind that choice, and what to fix when the data is not green.
Assumptions and model boundaries
This section tells the user what the model is for, what it uses, and what it does not use.

What this model is for

What this model is not for

Audit log
Every assumption or scenario change should leave a readable trail.
WhenTypeChangeFromTo
Major business problem solved
This dashboard addresses a high stakes decision problem: leadership must commit to inventory, pricing, promotion, and financing before the cash consequence is fully visible. Once those commitments are made, the business may be trapped in a position that is expensive, slow, or impossible to unwind.
ROI of using this model
The ROI is mainly better decisions, fewer blind spots, and less avoidable cash stress.