A service leader facing a persistent backlog has a reasonable case for hiring more people. Extra agents may help customers get answers sooner. But if many requests arise from the same product defect, the queue can return even after the team catches up. The next budget decision has two parts: how much capacity the team needs now, and whether this round of work can reduce or improve the work it faces next time.
That distinction matters well beyond service. Repeated investment can make an organization harder to match, but spending and experience do not create that advantage on their own. The gain depends on whether people learn something useful, share it across the work that produces the customer result, and retain it for the next cycle.
What the next cycle inherits
Capacity is how much work a team can handle with its available resources. Competence is how well its people do that work. An organizational capability also depends on the routines, information, tools and relationships that let many people perform reliably over time. More hiring can increase capacity without changing that wider system; coaching can improve competence without ensuring that the improvement survives a departure.
Capability Compounding is the accelerating advantage created when repeated investment, learning and reuse make an organization progressively better at a strategically important capability. It describes a possibility, not a promise that time or spending will produce faster gains. A leader has to ask what each round of work leaves behind and whether that inheritance improves a result customers value.
In a hypothetical service operation, agents repeatedly hear about the same product defect. Hiring could shorten the queue, and coaching could help agents give clearer answers. A further improvement would connect those reports to product specialists who can investigate and correct the defect. Later customers might then have less reason to contact support. The organization would be changing a source of demand, rather than only becoming more efficient at handling it.
That improvement needs more than a request to “share insights.” Agents must record enough detail to distinguish a pattern from unrelated complaints. Product specialists need time and authority to investigate. After a change, both teams need to check whether the targeted contacts fell and whether other problems appeared. If no one closes that loop, experience may improve individual judgment while the organization keeps encountering the same issue.
Michael E. Porter’s Competitive Advantage introduces the value chain as a way to examine the activities behind an offering. Applied to the service example, that lens directs attention beyond the support team: product decisions affect incoming requests, and service observations can inform product decisions. The useful investment may be at the connection between those activities, not wholly within either team. Leaders should trace where learning must travel before deciding which budget owns the solution.
When accumulated practice becomes an advantage
A rival can hire experienced agents or buy similar software. Those purchases may be valuable, but they need not reproduce the way people use records, make product decisions and work across teams. Ingemar Dierickx and Karel Cool explain why some strategic assets develop through accumulation over time: an existing base can aid further development, and assets that depend on one another can be difficult to assemble quickly.
In the hypothetical operation, clearer case records could help product specialists diagnose defects. Successful fixes could, in turn, improve agents’ guidance and sharpen what they report next. If these changes reinforce one another, the organization may become better at preventing repeat contacts in a way that a newly staffed rival cannot immediately buy. This is a plausible path to unequal performance, not evidence that any particular service team has achieved it.
The distinction sharpens the investment question. A new system may remove a genuine bottleneck, but it will not retain learning if people do not use its information to make decisions. An expert hire may solve difficult cases immediately, but the wider capability may remain fragile if colleagues cannot learn from that work. Ask both what the expenditure delivers this quarter and what others will be able to do because of it next quarter.
There is a serious counterargument to continued investment in an established capability: learning does not necessarily last. Linda Argote, Sara L. Beckman and Dennis Epple found rapid depreciation of production knowledge in the industrial settings they studied. Their finding does not establish a rate of forgetting in service work. It does challenge the assumption that accumulated experience remains available simply because the organization once acquired it. A handoff used only by one specialist, or records no one consults, provides little protection against having to learn the same lesson again.
Retention is not enough, either. A service team could become excellent at answering questions about a product customers are leaving behind. Dierickx and Cool’s account also recognizes erosion and substitution: accumulated assets can lose value, and a different approach can become more useful. Leaders should protect the ability to learn and share what works, while remaining willing to change the routine itself.
Make the next investment decision
Start with the customer result the capability is meant to improve. For the hypothetical service operation, that could be fewer contacts about the recurring defect while customers who still need help receive reliable answers. Queue length and response quality remain useful measures. They show something different from the number of defect-related contacts: how well the team handles demand, rather than whether the suspected cause of that demand has changed. A drop in contacts would be a reason to investigate the effect of the fix, not proof on its own that the fix caused the drop.
Then follow a case through the organization. Who recognizes that it resembles other cases? Where is that observation recorded? Who can decide whether to investigate, change the product and check the result? This trace can reveal whether the constraint is staffing, individual skill or a broken connection between teams. If the process works but the queue exceeds the team’s capacity, hiring may be the right decision. If a recurring defect keeps generating requests, adding agents alone leaves that cause untouched.
Finally, decide what evidence would justify another round of investment. Look for newer agents handling cases that once required an expert, recurring issues reaching people who can resolve them, and improvement in the chosen customer result. Watch for unfamiliar requests that the established process fails to recognize. These observations can guide a decision to continue, revise or stop; they should not become a reason to fund the same activity by habit.
At the next budget review, ask what the next team will be able to do because of this cycle’s work. “Handle more requests” may be a sound case for buying capacity. A case for Capability Compounding needs more: learning the organization can retain and reuse, connected to a result customers still value, with evidence that each cycle is making the capability stronger.