The Track Most Manufacturers Overlook
When companies review Korea's Smart Manufacturing Innovation programs, most focus on production equipment and MES deployment. What often goes unnoticed is that the same program framework includes a separate track: SME Smart Service Support.
While the smart factory track targets equipment and processes inside the plant, the smart service track funds ICT and AI solutions for non-manufacturing work that happens outside the factory floor — sales, logistics, after-sales service, and customer management. Manufacturers are fully eligible. The assumption that "we run a factory, so only the smart factory track applies to us" costs companies real opportunities every year.
Funding Scale and Eligibility
The decisive review criterion is whether the project makes substantive use of advanced ICT such as big data and AI. Website redesigns or straightforward ERP replacements are at high risk of being ruled ineligible. The project should be designed not as a system swap, but as a change in how decisions get made, grounded in data.
What Kinds of Projects Get Selected
The application areas manufacturers most often pursue include:
Service businesses — wholesale and retail, distribution, logistics, healthcare services — can take the same approach. In every case, however, the deciding factor is whether usable data already exists. Roughly one to two years of organized transaction or service history is what makes a project credible as feasible.
If you are applying under the advancement category, you must state improvement metrics relative to your existing system. The rule is to express it numerically — not "we will add features," but "we will raise forecast accuracy from 72% to 85%."
Running Two Tracks in Parallel
It is entirely possible to split your application: the smart factory track for what happens inside the plant (equipment, processes), and the smart service track for what happens outside it (orders, inventory, customers). Before proceeding, confirm three things:
Most importantly, the two programs compound only when you design them around data integration. Forecast accuracy improves when production results generated by MES meet order and shipment data on the service side. Defining those connecting data fields at the application stage also makes post-completion performance reporting far easier.
Where Applications Win or Lose Points
What Determines the First Six Months After Go-Live
The most common failure is straightforward: the system is built, and then no one enters the data. Without a designated owner and an input routine embedded in daily workflow, even a well-built forecasting model sits unused within months.
The second is establishing a baseline. If you do not record your pre-deployment numbers, you have no way to demonstrate improvement in performance reporting. Measure and document current cycle times and error rates before the project begins.
How KITIM Can Help
KITIM supports companies at every stage — assessing which track fits your business, designing the project, preparing the business plan, matching you with solution providers, and managing post-deployment performance. If you are unsure which track works better for your company, we invite you to request a consultation.