6 Proven Steps to Improve Inventory Management and Boost Equipment Uptime

Improving inventory management to boost equipment uptime involves adopting digital tracking, conducting regular audits, and optimizing replenishment to prevent critical shortages. 

We often treat inventory as a safety blanket. But here is the truth the data keeps telling us: More inventory does not equal more uptime. In fact, surplus junk often hides the gaps that kill your availability.

We are going to walk through six concrete steps to fix this. And because this isn’t about guesswork, every single claim here is backed by legitimate sources, from Forrester studies to real-world manufacturing KPIs.

Let’s dive in.

Step 1: Stop Guessing and Measure True Equipment Effectiveness (OEE)

You cannot improve what you don’t measure. But please, do not just track if the machine is running. Track OEE (Overall Equipment Effectiveness) . This is the gold standard.

Here is the reality check that hurts a little. The global average manufacturer runs at an OEE of just 60%. That is considered “Average”. What is considered “World Class”? 85% .

That gap? That is not a technical problem. That is an inventory and management problem. That 25% gap represents roughly a full shift of production lost every four days.

How Inventory kills OEE

The data shows that high downtime forces managers to hoard stock. You build safety stock because you don’t trust the machine to run. But according to experts, high inventory levels actually mask the root causes of downtime.

Actionable Step:
Start tracking the three pillars of OEE:

• Availability: Is the machine there when you need it? (Stop stocking parts for machines that are never fixed).
• Performance: Is it running at speed?
• Quality: Is it making good parts?

Quick Benchmark Check:

KPI	Industry Average	World-Class Target	Why It Matters for Inventory
OEE	60%	85%+	Low OEE drives over-purchasing to “buffer” failures.
MTBF	500-800 hrs	2,000+ hrs	Predictable failures mean predictable spare parts.
MTTR	4-6 hrs	<2 hrs	Slow repairs require storing more parts “just in case”.

Step 2: Differentiate Between “Dead Stock” and “Critical Spares”

I once walked into a warehouse where 40% of the shelf space was filled with parts for equipment that had been decommissioned two years prior. We all do it. We keep it “just in case.”

A study on MRO (Maintenance, Repair, and Operations) inventory put it bluntly: Obsolete motors, degraded belts, or low-priority spares do not improve uptime. Instead, they create blind spots.

The study highlights a terrifying phenomenon: “The only thing worse than not having the part is thinking you do.” If a part has been sitting in a humid environment for three years, bearings can corrode, and electronics can fail. You might have the part on the books, but it is a liability, not an asset.

Running the “Criticality” Test

You need to right-size your inventory. Ask these two questions from the Remsoft framework:

1. If this part fails, does production stop?
2. Can I source this part within my maintenance window?

If you can get a gearbox in 24 hours, but your scheduled maintenance is 72 hours away, you do not need it on the shelf. If the lead time is 12 weeks, you absolutely need to stock it.

Step 3: Fix the “Hidden Warehouse” with Real-Time Visibility

Here is where technology changes the game. For years, we relied on spreadsheets and clipboard audits. That is like driving a car blindfolded. The result is “Cycle Counting” that takes weeks.

A 2025 Forrester study commissioned by Dexory analyzed warehouses that introduced autonomous inventory scanning (robots/digital twins). The results for inventory management were staggering.

Data-Backed Results

The composite organization in the Forrester study saw an ROI of 219% with payback in less than 6 months.

• 99.9% Inventory Accuracy: They stopped losing pallets. Literally. They saved $1 million over three years just by not losing pallets.
• Reduced Stockholding Costs: Because they knew exactly what they had, they reduced buffer stock and saved $1 million.
• Labor Efficiency: They saved $866,867 by automating cycle counting. No more shutting down a forklift to count boxes.

“Real-time visibility is not just about knowing where an item is. It is about knowing where it needs to be.”

Step 4: The “Train Wreck” Principle — Fixing Data Entry

We spend millions on ERP and CMMS systems, but then we let Dave from maintenance type “thingy broke” as the failure code. This is a disaster for uptime.

According to a 2026 guide on Enterprise Asset Management (EAM), inconsistent data is one of the most costly mistakes facilities make. If one engineer logs failure as “Pump Leak” and another logs it as “PR-102 Seal Fail,” you cannot run a report to tell you that your seals are failing every 90 days.

The Human Fix:
Standardize your nomenclature. Create dropdown menus in your system for failure codes. It feels bureaucratic, but it is the only way to spot the trend before the emergency happens.

Step 5: Use Process Mining to Slash Inventory Costs

Sometimes, the inventory issue isn’t in the storeroom; it is in the ordering process. There are blocks in the system causing you to order too much, too early.

A Total Economic Impact study by Forrester on Celonis (Process Mining) found that organizations were able to reduce redundant inventory saving 1% of factory operating costs (valued at $8.9 million over two years).

But the really interesting stat? They fixed the delivery process. By removing credit and inventory blocks, the percentage of deliveries requiring human intervention dropped from 67% to just 14%. When processes move faster, you don’t need to hoard safety stock to cover administrative delays.

Step 6: The “Newman Technology” Case Study — Real Results

Let’s look at a real-world example to tie this all together. Newman Technology, an automotive supplier handling 330,000 components daily, was drowning in spreadsheets. They had no real-time view of their supply chain.

They implemented a modern MES (Manufacturing Execution System). The results are exactly what we are looking for:

• Inventory Cost reduced by 25% (Right-sizing the spares).
• Inventory Accuracy hit 98% (Knowing what you have).
• Time for inventory checks dropped by 62% (Efficiency).

The IT Manager there said the old process of physical inventory was “a nightmare” that took days. Now it takes hours. That is time the team can spend on preventing downtime, not counting the dust on the shelves.

The Takeaway (And a little tough love)

Look, we have been brainwashed to think that a full warehouse is a safe warehouse. But the data—from Forrester, from industry benchmarks, from the shop floor—says the opposite.

Uptime comes from precision, not excess.

Start small. Pick your top 5 critical assets. Run an OEE calculation on them today. I promise you, the data will tell you exactly which part you are missing, and which 50 parts you are hoarding for no reason.