Rethinking Efficiency: Why Growth Requires Abandoning "Cost-Saving" Mindsets

The 2026 Productivity Forum suggests that efficiency is no longer just about cutting costs. It is a requirement for growth. By moving away from metrics like "shrink" and toward understanding human behavior, businesses can unlock hidden capacity. Traditional cost-cutting often creates unnecessary complexity. In contrast, true efficiency--such as simplifying stock levels or using automation with human oversight--actually improves what people can achieve. Readers who adopt this growth-first framework gain an advantage: they stop solving the wrong problems and start building systems that handle modern peak demand.

The Trap of "Managing Numbers"

Conventional wisdom says that if you have a problem, you measure it and then manage it down. Forum participants argued that this approach often hides the real source of inefficiency. When companies treat shrink as a number to control, they treat the symptom rather than the disease.

> "If you see shrink as a number then you manage that but actually it's about trying to understand root cause, it's not about trying to manage theft."
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> -- James, Productivity Pulse

By focusing on the root cause instead of the metric, leaders move from a defensive position to an offensive one. This is a systems-level change. Instead of adding layers of control to stop theft, you re-engineer the environment to remove the friction that allows it to happen. This requires the patience to look beyond the spreadsheet. It is difficult work, but it creates a lasting advantage because most competitors will not do it.

The Hidden Multiplier: Simplicity as Infrastructure

One of the most counter-intuitive insights from the event was the role of inventory in operational speed. When teams struggle with efficiency, the instinct is to optimize the process--how fast a worker moves, how they scan an item, or how they use a tool.

However, data from Ian at Hartling and Co-op showed that the biggest gain in speed did not come from a new process or faster software. It came from physically reducing the amount of stock held in the store.

> "It's much easier and simpler to be quicker and accurate when you're not dealing with pals and pals or franchises that you have it to move all the time."
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> -- Sue, Productivity Pulse

The result is profound. By reducing the physical load, the system becomes more responsive. This is systems thinking: the environment dictates the outcome more than individual effort. Most teams try to train their way out of a cluttered environment. The smarter move is to remove the clutter so the training becomes secondary.

Technology as a Human Amplifier, Not a Replacement

The discussion on technology at the forum was grounded. While AI and automation were popular topics, the consensus was that technology should amplify human capability rather than replace human judgment.

The danger, as speakers noted, is buying technology for the sake of having it. When technology is deployed without first aligning processes and people, it introduces a hidden cost: complexity. This complexity builds over time, leading to a state where the system becomes too opaque for the team to manage during peak capacity. The competitive edge belongs to those who keep humans in the loop, ensuring that technology remains a tool for simplification rather than a source of new operational debt.

Key Action Items

• Audit your efficiency metrics: Over the next quarter, pick one metric like shrink or task time and stop trying to manage it. Conduct a root-cause analysis to see if the process itself is the source of the friction.
• De-clutter to speed up: Before investing in new software to improve task speed, evaluate your physical or digital inventory. Can you reduce the total volume of stuff to make the remaining work inherently faster?
• Stress-test your peak strategy: Map your business current peaks. Are they shifting? Are they shorter or longer than last year? Use this data to move away from rigid resourcing toward a test and learn model.
• Implement human-in-the-loop protocols: If you are deploying AI or automation, mandate a final human review step. This prevents the black box effect where bad data or logic leads to operational errors.
• Adopt a fail fast mindset: When testing new technology or processes, set a clear time limit for the experiment. If the data does not support the investment, stop immediately. Killing a pet project now creates significant resource availability later.