Every decision has a latency: the time between when the information required to make the decision arrives and when the decision is executed. In most companies, this latency is unmeasured, unmanaged and, when quantified, one of the largest unrecognised costs in the operating model.
A pricing adjustment that takes three weeks to approve loses three weeks of margin improvement across every transaction during the delay. A hiring decision that takes two months to execute leaves productive capacity idle for two months. A procurement decision requiring four sequential signatures misses the early-payment discount the supplier offered for seven days. A credit decision that takes ten days to process loses the customer to a competitor who approved in two.
None of these delays are caused by analytical complexity. The information was available. The decision was clear. The delay occurred in the space between knowing and acting: the approval chain, the escalation path, the availability of the decision-maker and the organisational ritual of seeking permission from people who will add a signature but not a judgment.
Mapping the Decision Chain
Information arrives → analysis prepared → approver identified → approval requested → approval granted → execution begins
At each step, measure elapsed time. The total is the decision latency. The cost is the economic value lost during the delay.
For most mid-market companies, the largest source of decision latency is the approval architecture: multiple approvers in sequence rather than parallel, unclear escalation paths, decision-makers whose bandwidth is consumed by other decisions queued for the same approval, and a cultural expectation that no decision should be made without senior sign-off, regardless of its magnitude or reversibility.
Quantifying the Cost
Map the five most frequent high-value decisions: pricing changes, procurement above threshold, hiring, customer credit, capex requests. For each, measure the average latency.
Pricing latency: A 3% pricing increase delayed by 21 days on Rs 500 crore of annualised revenue costs approximately Rs 86 lakh in forgone margin. The analysis was complete on day one. The remaining 20 days were approval latency.
Hiring latency: A revenue-generating role left unfilled for 60 days beyond the decision point represents 60 days of lost productivity at whatever rate that role generates. For a salesperson generating Rs 1 crore per quarter, the 60-day delay costs approximately Rs 67 lakh.
Procurement latency: A 2% early-payment discount missed because approval took 15 days costs 2% of the procurement value. On a Rs 10 crore purchase order, that is Rs 20 lakh.
Credit latency: A customer requiring a Rs 50 lakh credit limit who receives approval in ten days when the competitor approves in two may not become a customer at all. The lost revenue is the permanent cost of a temporary delay.
The aggregate cost of decision latency across all high-value decisions frequently exceeds 1% to 2% of revenue. For a Rs 500 crore company, that is Rs 5 to 10 crore per year of value lost not to poor decisions but to slow decisions.
The Root Causes
Too many approval layers
A decision requiring four signatures takes four times as long as a decision requiring one, not because four people analyse it, but because four people’s calendars, priorities and availability must align.
Sequential rather than parallel processing
Three approvers reviewing in sequence consume three time windows. The same three approvers reviewing in parallel consume one. Most approval architectures are sequential by default, not because sequential processing adds analytical value, but because the architecture was never designed for speed.
Unclear escalation paths
When the designated approver is unavailable, what happens? In most companies, the decision waits. The escalation path is either undefined or requires a separate approval to escalate, creating a meta-delay: the delay in deciding who should decide.
Cultural risk aversion
A culture that penalises bad decisions more harshly than it penalises delayed decisions will produce organisational behaviour that optimises for caution over speed. The rational response of any individual in this culture is to seek more approval, more sign-off and more cover before acting, even when the decision is routine and the risk is minimal.
The Redesign
In Northrop Management Private Limited’s performance improvement work, decision-latency reduction follows four principles:
Pre-approved parameters: For recurring decisions within defined parameters (procurement from approved vendors below Rs X, pricing within Y% of list, credit within Z% of policy limit), eliminate the approval entirely. The parameters are the control. Individual transactions within them do not need separate authorisation.
Parallel processing: Where multiple approvals are genuinely required, route them simultaneously rather than sequentially. Three approvers in parallel consume one day. The same three in sequence consume three.
Delegation with accountability: Delegate decisions to the lowest competent level, with clear accountability for outcomes. A mid-level manager who is empowered to approve within defined limits and held accountable for the results will make faster and often better decisions than a senior executive who approves based on a one-paragraph summary without operational context.
Exception-based escalation: Approve by default within parameters. Escalate only exceptions. The control shifts from universal pre-approval (slow, high-volume, low attention per item) to exception-based review (fast for standard items, concentrated attention for unusual ones).
Ashish Chaudhary, Founder and Managing Director of Northrop Management Private Limited, frames the diagnostic directly: “Speed is not about working faster. It is about deciding faster. A company that generates information quickly but approves decisions slowly has optimised the wrong part of the chain. The information has no value until someone acts on it.”
Questions for the Boardroom
- What is the average elapsed time from information availability to execution for our five most frequent high-value decisions?
- Where in the decision chain does the most time accumulate: analysis, approval or execution
- Could any approval layers be removed, combined or converted to pre-approved parameters without increasing risk?
- What is the quantified annual cost of decision latency across our top five decision categories?
- If we halved the decision latency for our slowest approval process, what would the financial benefit be?
Closing Implication
Decision latency is an invisible operating cost. It does not appear on the P&L. It does not feature in the management report. It is not measured, benchmarked or governed. And it costs most mid-market companies more than many of the line items they scrutinise quarterly.
The fix does not require faster people. It requires fewer approval steps, clearer delegation, pre-approved parameters and a governance architecture designed for speed at the levels where speed matters.
