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Why Invoice Approval Cycles Slow Down in Mid-Market Companies

Why Invoice Approval Cycles Slow Down in Mid-Market Companies

By:

Maninder Sidhu

Published

Factory workers wearing safety helmets and face masks reviewing manufacturing operations on a production line.

Three weeks. That's how long invoice processing can stretch for organizations requiring six or more approvals before a bill clears, according to DocuClipper's invoice automation benchmarks, and nearly 30% of enterprises fall into exactly that bracket. Mid-market companies sit in an uncomfortable middle ground here: too large to run approvals on a single person's say-so, not yet equipped with the workflow infrastructure that keeps a longer approval chain from turning into a bottleneck. 

2021 QuickBooks survey found mid-sized US businesses owed an average of $300,000 in late payments, with 89% saying it was actively holding back growth. That's not a vendor problem. Most of that delay sits inside the company's own approval chain, not on the other end of the invoice. 

Where the time actually goes

It helps to separate two numbers that get treated as one. Cycle time is the total days from invoice arrival to payment; touch time is how many minutes a human actually spends on it. The industry average cycle time runs 10 to 20 days, while best-in-class teams compress it to roughly 3 days; the gap between those two numbers almost never comes from typing faster. 

A long approval chain adds days before anyone even looks at the dollar amount

A three-tier approval chain where each approver takes a full business day to respond adds three days before payment is even considered, regardless of how quickly the invoice was captured or how clean the data is. Add a single approver who's travelling, in back-to-back meetings, or simply slow to check email, and those three days become a week without anyone doing anything wrong. 

Exceptions eat the time savings automation was supposed to deliver

Mid-market AP departments commonly see exception rates between 20% and 30%, invoices that don't match a PO cleanly, arrive with missing fields, or trigger a pricing discrepancy. A lot of that, in practice, traces back to vendor and customer data that's inconsistent across systems, one spelling of a vendor name in the accounting platform, a slightly different one on the invoice itself. The Forwardly Business Network connects buyers and vendors directly across accounting systems, so invoice and vendor details sync from the source instead of getting keyed in fresh each time, which removes a meaningful share of exceptions before they ever reach an approver's queue. 

Too many invoices route to too few approvers

This is the structural mistake underneath most of the above. If one finance director personally signs off on every invoice above a modest threshold, that's a guaranteed bottleneck every time they're on leave, in a board meeting, or just buried. The team picks up the slack, fielding "where are we on this invoice" questions all week, and finance becomes the department everyone blames for slowness it didn't actually cause. 

The cost isn't just an annoyance; it's money walking out the door

Missed early payment discounts are the most direct casualty. A company processing $500,000 a month in invoices that misses a 10-day window for a 2% discount because its average cycle runs 12 days is leaving something like $30,000 a year on the table, money that required no negotiation to capture, just a faster yes. Vendor relationships take a quieter hit too: suppliers who get paid late once start pricing that risk into the next quote, which shows up as worse terms long after the original delay is forgotten. 

What actually fixes it, and what doesn't

The instinct is usually to add more oversight, another approval layer, a stricter sign-off rule, when the chain is already the problem. What works instead is routing by rule rather than routing by person. Most invoices, the routine ones from approved vendors under a reasonable threshold, don't need a senior signature at all; they need a consistent rule that clears them automatically and reserves human attention for the invoices that are actually unusual. Forwardly's approval workflows work this way, routing bills automatically by amount, vendor, or department, and escalating to a deputy approver when someone in the chain doesn't act within a set window, so a single person's calendar stops being the rate limiter for the entire process. 

That still leaves the question of how an invoice gets clean enough to route automatically in the first place. Forwardly's AI-powered AP inbox captures and codes bills as they arrive, applying the same coding logic a finance team has used on past invoices to hundreds of new line items without anyone retyping them. On top of that sits the Forwardly AI Agent, which reviews each bill before payment and flags anything that looks unusual, an off-pattern amount, a changed vendor detail, for a person to actually look at, rather than routing every invoice through a human regardless of risk. That's a meaningfully different model than a fixed rule that only checks whether an amount crosses a threshold; it catches the kind of anomaly a static rule would miss while still leaving the routine 70 to 80% of invoices to clear without anyone's attention. 

None of this requires restructuring who's allowed to approve what. It requires making sure the rules and the AI watching for what the rules miss decide where an invoice goes next, instead of leaving that decision to a person's calendar and an inbox full of forwarded PDFs. 

See how Forwardly's approval workflows keep invoices moving without adding another layer of sign-off. 

FAQs

How do manual accounts payable processes slow down invoice approvals? Manual AP slows approvals in three main ways: invoices route through people instead of rules, so an approver's calendar becomes the bottleneck; exceptions like mismatched data require manual investigation instead of automatic resolution; and there's no system flagging unusual invoices, so every bill needs human review regardless of risk. Mid-market AP departments see exception rates of 20% to 30% when this data isn't cleaned up automatically.

Why do invoice approval cycles take longer in mid-market companies? Mid-market companies are large enough to require multi-tier approval chains but often lack the automated routing that prevents those chains from stalling. A three-tier approval process where each approver takes a full day to respond adds three days before payment is even considered, and that gap widens any time an approver is traveling, in meetings, or simply slow to respond.

What's the difference between invoice cycle time and touch time? Cycle time is the total number of days from when an invoice arrives to when it's paid. Touch time is the actual minutes a person spends working on it. Industry average cycle time runs 10 to 20 days even though touch time is a fraction of that; the gap comes from invoices waiting in someone's queue, not from data entry.

How can mid-market companies speed up invoice approvals without adding oversight? Routing invoices by rule rather than by person is the most effective fix. Routine invoices from approved vendors under a set threshold can clear automatically, while only unusual or high-value bills get sent to a human approver. This reserves attention for the invoices that actually need it instead of running every bill through the same manual review.

What's a healthy invoice approval cycle time? Best-in-class AP teams process invoices in roughly 3 days, compared to an industry average of 10 to 20 days. Companies running closer to the 3-day benchmark typically use automated routing and AI-based exception handling rather than relying on manual, person-by-person approval chains.

How much do slow invoice approvals actually cost a business? Beyond strained vendor relationships, slow approvals mean missed early payment discounts. A company processing $500,000 a month in invoices that misses a 10-day window for a 2% discount because its cycle runs 12 days is leaving roughly $30,000 a year on the table, with no negotiation required to capture it.

By:

Maninder Sidhu

Published