Why Digital Twins are no longer a "nice to have" for lighting manufacturers

AI has dramatically improved productivity in many sectors of the economy, and manufacturing is no exception.

Among lighting manufacturers, the companies with the biggest productivity gains are the ones adopting digital twins.

A digital twin is a virtual representation of your business. For lighting manufacturers, this includes the products, accessories, specs, configuration rules, prices, spec sheets, relationships, quotes, projects, customers, reps, terms & conditions of sale, orders and other fine grain details. More importantly, it’s the relationships and properties between all of these objects.

There are three reasons why having a digital twin is no longer a nice to have:

1. AI is only as good as the context you provide it
2. Your core operations all rely on the same context
3. Agentic AI needs a harness to execute work

1 - AI is only as good as the context you provide it

This is obvious when you use a chatbot. Not even Einstein can produce a good result if he is unclear about what you want and how your business operates.

AI is already genius level in many domains, but you need to be precise when teaching it about your business. For a lighting manufacturer where products, projects, and prices are always in flux, this is an impossible task. Hence, you need a digital twin.

With a digital twin, an AI can stay up to date with the latest context across all aspects of your business. The AI can continuously monitor your sales, quotes, products, documentation, and bring up issues that need your attention.

If you believe that we’re on the verge of an Artificial Super Intelligence (ASI), then you’ll want to hire that ASI as soon as possible and give it the most recent context to improve your business. Otherwise your competitors with ASI will.

“But what happens when everyone adopts the ASI?” Yes, eventually everyone will adopt digital twins to run AI, just like everyone adopted excel. And just like the technology transitions of the past (excel, web2.0) the businesses that executed the best and the fastest, will grow and compound the fastest. It pays to be an early adopter of transformative technologies.

But unlike excel, a digital twin is much harder to implement (as you’ll soon learn).

2 - Your core operations all rely on the same context

Customer Success, quoting, reporting, spec sheet updates, marketing, and engineering. These are core operations for every lighting manufacturer, and they all rely on the same context: your products.

Without a digital twin of your products feeding live product data to each of these operations:

• Your quotes team misconfigures, misprices, or mis-crosses, takes longer to respond, makes mistakes, and loses the job
• Your reporting can’t drill down to the products each customer favors, and you miss key trends, and product opportunities
• Your spec sheets and documentation become outdated, leading to frustrating back and forth with specifiers, reps, and your engineers
• Your engineering team has to spend more time communicating product changes to marketing than spend time on product engineering

A digital twin ensures each function can work and trust the product data because it’s no longer scattered across documents, or silo’d in different departments.

3 - Agentic AI needs a Harness to execute work

An AI agent is an AI that can escape its chatbox and actually execute work on your behalf. But to do so, it needs a harness.

An agentic harness is the complete software infrastructure, execution layer, and control system around the AI. A good harness can both reduce the tokens per task, and increase the quality of the output. (A token is the unit of compute an AI consumes when prompted)

The harness provides a set of tools the AI can use to execute tasks and deliver a deterministic result.

Without a harness, an AI can only produce a statistical artifact of what it predicts as the next token. It relies on the tools from its harness when you need a precise, deterministic result.

A digital twin acts as the agentic harness for your business and unshackles your superintelligent AI from its chatbox.

If you believe in ASI by 2027-2028, you’ll want to empower this 200 IQ AI to do their best work with a digital twin harness.

How to build your own digital twin

This varies depending on business complexity.

For a lighting manufacturer, a digital twin is very hard to build. We would know because we’ve spent the last 8 years on this problem. (6 of which was spent on the frontlines of lighting manufacturer operations.)

It’s not as simple as uploading your spec sheets into chatGPT, or vibe coding an app with spec sheets as context. That’s akin to a knowledge base, and it’s not going to get you good results because the approach itself is generic. (among other reasons like context limitations, context rot, and memory)

Extraordinary results come from the extraordinary effort required to create a digital twin. It’s in modelling the finer grain details of your products, configurator, accessories, specs, prices, costs, and importantly, how they relate to each other.

It’s in breaking down a process into its essential elements, building it back up from first principles, then doing the same with every operational process in your business then connecting the dots to put it all together.

If you’re not willing, or lack the bandwidth/expertise, to put in the extraordinary effort in building a digital twin yourself, I recommend looking for a digital transformation partner who has already done the hard work.

For a firm who has already figured this out, with real case studies and measurable success. Check out www.electrifyconnect.com