Metabase vs Tableau for Wholesale Distributors: Fill Rate

Fill rate sounds simple, but customers judge it by whether the order they placed shipped complete and on time, not by an aggregate percentage across all line items company-wide. Build the dashboard at the order level first, complete and on-time as a single binary outcome, then let it roll up to a percentage by customer, by warehouse, and by product category. A distributor optimizing for a company-wide fill rate number can still be quietly failing its largest accounts if the shortfalls happen to concentrate there, which an aggregate number hides completely.

This distinction matters most for the accounts a distributor can least afford to lose. A company-wide fill rate of ninety-five percent sounds healthy right up until a sales lead discovers it is being dragged up by dozens of small, easy-to-fill accounts while the three largest customers have been sitting closer to eighty percent for months without anyone noticing.

An overall inventory turns number tells you the business is healthy or it is not, but it does not tell a purchasing manager what to actually do differently next quarter. Break inventory turns down by product category and by supplier, and pair it with a simple aging view flagging SKUs that have not moved in a defined window. Metabase's SQL access makes it straightforward to adjust that "slow-moving" threshold as your product mix and seasonality change, rather than being locked into a fixed report definition someone configured once and never revisited.

A category rolling up to a healthy average turns number can still be hiding a handful of SKUs from one specific supplier that have not moved in months, tying up warehouse space and cash that could be funding a faster-moving line. The category-level number alone will never surface that supplier-specific pattern.

Extending net-30 or net-60 terms to win a large account only works if the receivables actually collect on schedule. A dashboard aging outstanding invoices by customer, updated daily rather than reviewed at month-end close, gives a controller or ops lead time to reach out to a slow-paying account before the balance grows large enough to threaten cash flow, rather than discovering the problem in a stale accounts receivable report weeks after it started.

Most distributors carry a line of credit to fund inventory purchases ahead of demand, priced off the prime rate, which sits at 6.75% as of this writing¹. Sizing that facility correctly depends on seeing inventory turns, receivables aging, and payables timing together, the cash conversion cycle in full, rather than each piece separately. A dashboard combining all three gives a finance lead a real basis for negotiating facility size with a lender instead of a rough estimate based on last year's peak season.

A single-warehouse distributor with one ops manager reviewing all of this directly can run it entirely in Metabase. A distributor operating multiple warehouses, each with its own manager who should see their own facility's numbers without necessarily seeing every other facility's supplier relationships and margin detail, benefits from Tableau's row-level security to enforce that separation cleanly as the network grows and warehouse managers change over time.

Disqualifier: skip Tableau if you run a single facility where the ops lead already sees everything directly. The added governance has no real audience to serve yet.

A well-run distributor's weekly ops review works from three numbers on one screen: fill rate by top account, slow-moving inventory flagged for markdown or return-to-vendor, and receivables aging past the customer's agreed terms. Median pay for the operations managers who typically run this review sits at $105,770 a year nationally², and the argument for automating the underlying data pull is straightforward: that person's time is better spent deciding what to do about a slow-paying account than assembling the report that reveals one exists.

The weekly review works from these views on one screen:

• Fill rate by top account, measured as orders that shipped both complete and on time.
• Slow-moving inventory flagged for markdown or return-to-vendor, using an aging view of SKUs that have not moved.
• Receivables aging past each customer's agreed terms, refreshed daily rather than at month-end close.
• The cash conversion cycle, showing inventory turns, receivables, and payables timing together.