What the research says about smart factory ROI

The return on smart factory technology isn't a theoretical discussion any more. There's a growing body of research behind it.

But research gets quoted badly. A number from one survey turns up on a vendor slide with no source, no date and no context. So here are the figures I find most useful, where they come from, and what they actually tell you.

Manufacturers believe in it, and they're spending

Deloitte's 2025 Smart Manufacturing Survey asked 600 executives at large US manufacturers (over $500 million revenue and 1,000 employees) about their plans (Deloitte, 2025).

• 92% believe smart manufacturing will be the main driver of competitiveness over the next three years.
• 78% allocate more than 20% of their improvement budget to smart manufacturing.

My first question on seeing the 92%: what on earth are the other 8% doing?

The more useful point is the second one. Strategy without investment is wishful thinking. These numbers suggest manufacturers are finally backing their digital ambitions with real money.

The reported returns

The same survey asked respondents what they'd seen from their smart manufacturing initiatives. On average:

• Production output: 10% to 20% improvement
• Employee productivity: 7% to 20% improvement
• Unlocked capacity: 10% to 15% improvement

Those are big numbers, and they line up with what I see in real projects. More output from the same equipment. Less time spent on manual data entry and chasing information. Capacity that was always there, hidden in micro-stops and slow changeovers.

To put capacity in context: what would just a 1% improvement in OEE mean for your business? For most manufacturers it's a very significant number. A 10% improvement can be the difference between building a new line and not needing one.

Most manufacturers haven't started

MarketsandMarkets puts the global MES market, software and services together, at around $16 billion in 2025, growing to almost $26 billion by 2030 (MarketsandMarkets). Software-only estimates are lower: IoT Analytics puts MES software at $5.5 billion in 2024 (IoT Analytics, 2025). IoT Analytics also reports that 54.4% of small and medium-sized manufacturers still rely on manual methods (pen and paper or spreadsheets).

That's the opportunity. If most of your competitors are still running on paper and Excel, investing now is a genuine competitive advantage, not just catching up.

The people problem is driving it

Two more figures explain why investment is accelerating.

• 72% of industrial organisations report negative impacts on operational performance from frontline workforce issues (LNS Research, 2023).
• US manufacturing could need 3.8 million new employees between 2024 and 2033, and 1.9 million of those roles could go unfilled (Manufacturing Institute and Deloitte, 2024).

When you can't hire your way out of a problem, you have to make the people you've got more effective, and make new starters productive faster. That's a big part of the case for connected worker and MES/MOM.

What the research doesn't tell you

Be careful with averages.

• They describe large companies. Deloitte's sample is manufacturers with over $500 million revenue. Your results may differ, in either direction.
• They're self-reported. Respondents say what they've seen. That's useful, but it isn't an audited result.
• They lag. Surveys capture what happened over the last year or two, in a market moving quickly.
• They don't tell you how. The same technology delivers very different returns depending on the processes underneath it, the team running it and whether the data is trusted.

In my experience, the difference between a 2% and a 20% improvement is rarely the software. It's whether the processes were fixed first and the data is trusted. And whether leadership stayed committed after go-live.

Use the research, then build your own case

Research is useful for one thing above all: getting leadership to take the conversation seriously. It won't approve your budget on its own.

For that you need your own numbers. Your downtime, your scrap, your overtime, your late deliveries, translated into money. I walk through how in How to build an MES business case leadership will sign.

Which of these numbers would land best with your leadership team?