Manufacturing Made Simple Podcast
Sep 23, 2026 · 30 min · 13 segments
Automation, AI, and digital tools reshaping personal care and pharmaceutical manufacturing such as MES, ERP, and LIMS systems in context, AI for defect detection and process optimization, predictive…
Andrew CheungHost
Now, before I go into specific technology categories, I want to give you the framework I use for evaluating any manufacturing technology investment, because I think it's more useful than any survey that you would use for available tools.
The first question, and I really mean the only first question is, what specific measurable problem are you trying to solve? Not the, we want to be more digital or we want to improve quality or our competitors are investing in automation and we should too.
Our visual inspection process generates a false rejection rate of 12%, which is costing us X in scrapped product every single year.
Or our batch cycle time from pre-weigh to release takes 11 days, and 7 of those days are waiting periods between steps.
Or even, our lab analysts are spending 40% of their time on data transcription that creates transcription error risk and consumes capacity we need for actual analytical work.
When you can name the problem that specifically, you can evaluate whether a technology actually addresses it.
And you can calculate whether the cost of the technology, including implementation to integration, validation, and even change management, is justified by the value of solving it.
That calculation, done honestly, is what separates good technology investments from impressive looking ones.
The second question is, what does our current process actually look like? And what level of process discipline and data quality do we have today? This question matters because most manufacturing technology systems are amplifiers.
A good process with disciplined execution implemented in an MES becomes a better, more consistent, more traceable process.
A poorly defined process with inconsistent execution implemented in an MES becomes a poorly defined process with a software system running on top of it.
It either amplifies good processes or make bad ones more expensive and harder to change.
The third question is, what is the realistic implementation path? And what does total cost of ownership actually look like? The purchase price of manufacturing software is typically a fraction of the total cost of deployment.
Implementation services, integration with existing systems, hardware, validation for pharmaceutical applications, training, change management, and ongoing license and support fees can easily double or triple the headline number.
Understanding the full cost before committing to the system is not being cynical.
Now, before I go into specific technology categories, I want to give you the framework I use for evaluating any manufacturing technology investment, because I think it's more useful than any survey that you would use for available tools.
The first question, and I really mean the only first question is, what specific measurable problem are you trying to solve? Not the, we want to be more digital or we want to improve quality or our competitors are investing in automation and we should too.
Our visual inspection process generates a false rejection rate of 12%, which is costing us X in scrapped product every single year.
Or our batch cycle time from pre-weigh to release takes 11 days, and 7 of those days are waiting periods between steps.
Or even, our lab analysts are spending 40% of their time on data transcription that creates transcription error risk and consumes capacity we need for actual analytical work.
When you can name the problem that specifically, you can evaluate whether a technology actually addresses it.
And you can calculate whether the cost of the technology, including implementation to integration, validation, and even change management, is justified by the value of solving it.
That calculation, done honestly, is what separates good technology investments from impressive looking ones.
The second question is, what does our current process actually look like? And what level of process discipline and data quality do we have today? This question matters because most manufacturing technology systems are amplifiers.
A good process with disciplined execution implemented in an MES becomes a better, more consistent, more traceable process.
A poorly defined process with inconsistent execution implemented in an MES becomes a poorly defined process with a software system running on top of it.
It either amplifies good processes or make bad ones more expensive and harder to change.
The third question is, what is the realistic implementation path? And what does total cost of ownership actually look like? The purchase price of manufacturing software is typically a fraction of the total cost of deployment.
Implementation services, integration with existing systems, hardware, validation for pharmaceutical applications, training, change management, and ongoing license and support fees can easily double or triple the headline number.
Understanding the full cost before committing to the system is not being cynical.
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