Why don't business operations change despite repeated DX investments? The root cause lies not in a lack of technical skills, but in "the absence of personnel who can bridge the gap between on-site needs and development" and "the cycle of requirements definition → development → implementation being too slow." By the time the system is designed, developed, tested, and delivered to the field, the situation on-site and the business environment have already changed. This problem of "being unusable by the time it's completed" is repeatedly seen in DX projects in the manufacturing industry.
One type of talent that is attracting attention for its ability to solve this problem is the "FDE (Forward Deployed Engineer)." This article explains the role of FDEs, how they differ from traditional IT personnel, and the benefits of hiring them in manufacturing DX.
What is FDE?
An FDE (Forward Deployed Engineer) is an engineer specializing in quickly solving on-site problems by utilizing the latest AI and data technologies.
For example, in a manufacturing plant, we would interview line operators to design how to use data to reduce quality defects, quickly build a system using the latest AI and data technologies, and take responsibility for its implementation in on-site operations. The biggest difference from traditional engineers is that we don't simply receive requirements and develop, but rather take the shortest route from defining "what should be built" to "making it usable on-site."
In traditional IT projects, strategy planning, requirements definition, and system development were typically handled by separate teams. This division lengthens the cycle and creates gaps between "design and implementation" and "technology and the field." Too much time passes between clarifying on-site issues and delivering a usable system—this is a structural problem that is causing manufacturing DX to stall. FDE acts as a bridge to this gap, functioning as an implementation manager possessing both business understanding and technical expertise.
Definition and Background of FDE
The concept of FDE (Field Development Engineer) spread primarily among Silicon Valley technology companies. This is because AI and data utilization projects require not only technology implementation but also transformation of business processes, making the role of engineers deeply involved in the client company's operations crucial.
Traditionally, engineers working on contract development projects typically handled system construction after requirements definition. In contrast, FDEs are positioned as "implementation-oriented personnel" who are involved from the problem identification and hypothesis testing stages, and drive projects forward in collaboration with clients.
Differences from consultants and system integrators
Consulting firms often focus on supporting the upstream processes, such as formulating DX strategies and developing roadmaps, and do not necessarily become deeply involved in the implementation phase.
While system integrators (SIers) develop systems based on requirements definitions, they rarely go so far as to explore business challenges or design improvement processes.
Unlike these approaches, FDE is characterized by its ability to rapidly cycle from problem definition to implementation and operational improvement while leveraging the latest technologies. It plays a role in connecting DX to actual business transformation by utilizing both technical expertise and a deep understanding of business processes.
Strategic Talent Profiles Revealed from OpenAI and Palantir
The importance of FDE can also be seen in the efforts of AI companies and data companies.
OpenAI has established an FDE (Field Development Engineer) position, where engineers go into the field to directly support companies that want to introduce AI and integrate it into their business processes. The aim is to increase the adoption rate of AI by taking responsibility for implementation tailored to actual business processes, rather than simply providing an API and being done with it. (*1)
Palantir employs a similar model, not only providing a data analysis platform but also having engineers stationed at the customer's site to continuously build and improve data utilization systems. (*2) This "implementation model that involves being on-site" is said to be the reason why both companies have high customer retention rates.
These examples demonstrate that in the age of AI and data utilization, the value of "people who can quickly solve on-site problems using the latest technology" is increasing more than the value of "people who deliver technology."
*1 OpenAI Forward Deployed Engineer "reference
*2 Palantir Forward Deployed Software Engineer "reference
Why does manufacturing DX stop before it reaches the factory floor?
FDE (Field Development Engineer) is a concept that originated in the IT and AI industry, but currently, the manufacturing industry is seeing the greatest demand for its implementation. Many companies possess vast amounts of on-site information, such as equipment data, quality data, and production data, but face challenges such as "data not being utilized" and "systems not taking root in the workplace." This is because the role of FDE perfectly aligns with the challenges faced by the manufacturing industry. So why does manufacturing DX stall before it reaches the factory floor?
The development cycle is too long, making it impossible to keep up with on-the-ground issues.
In DX projects, it's not uncommon for the entire process, from identifying issues and defining requirements to system development, testing, and implementation, to take several months to over a year. Especially in the manufacturing industry, changes in production line configurations, revisions to product lineups, and shifts in the market environment continue unabated during this time.
As a result, situations repeatedly arise where "the problems have changed by the time the system is completed" or "it's not what the field needed." Furthermore, systems begin to become obsolete the moment they are implemented. As the market and the field are constantly changing, engineers who can continuously update the system while staying close to the field are essential, rather than just building it once and being done with it. FDE solves both the slowness of this cycle and the obsolescence by rapidly iterating through hypothesis testing and implementation while utilizing the latest technologies.
The disconnect between practical work and data science
When implementing AI, a gap in understanding can sometimes arise between data scientists and those on the manufacturing floor.
If the results of data analysis do not align with the decision-making criteria used on the ground, the system may fall out of use in actual operations. This kind of language gap is one of the major factors hindering the successful adoption of digital transformation (DX).
Dependence on external vendors and the barrier to in-house development
When DX projects are outsourced to external vendors, the know-how may not remain within the company after the project is completed. As a result, an increasing number of companies are moving to "promote in-house development" by hiring and training engineers. However, engineers who possess technical skills but do not understand the actual work on the ground often do not mesh well with the workforce, and in many cases the project ends up failing.
As a result, continuous improvement and the creation of new themes become difficult, and DX initiatives often end up being intermittent.
Lack of personnel responsible for implementation and uncertainty regarding return on investment.
In DX projects, it can sometimes be unclear who is ultimately responsible for the outcome.
"We're investing in DX, so why aren't our operations changing?"—this is a question many executives grapple with. While multiple stakeholders, including consultants, system integrators, and internal IT departments, are involved, the lack of an implementation manager who understands both the business and the technology creates a structure where no one can take responsibility for the final outcome. This is also the root cause of the difficulty in seeing the return on investment. By appointing a Field Development Engineer (FDE) who is responsible for everything from defining on-site problems to implementation and stabilization, it becomes clear for the first time "how much was invested in what and what results were achieved."
Benefits of adopting FDE in manufacturing
FDEs (Field Development Engineers) are expected to play a crucial role in resolving these challenges by leveraging the latest technologies to quickly solve on-site problems. Here, we introduce the main benefits of employing FDEs in the manufacturing industry.
The speed of transitioning from proof of concept (PoC) to production deployment will increase.
FDE is involved from the design stage of the Proof of Concept (PoC), designing a structure that takes into account integration with existing systems and business processes.
In the manufacturing industry, designing systems with practical implementation in mind is essential, including methods for acquiring equipment data and coordinating with on-site operations.
By having FDE lead the project, we can expect to accelerate the transition from PoC to production deployment.
AI utilization will become more readily adopted in on-site operations.
A common reason why AI and data analysis initiatives fail is that their suitability for on-site operations is not adequately considered.
For example, even if an analytical model is highly accurate, it won't be used in actual operations unless it's incorporated into on-site decision-making processes and workflows.
Because FDE designs systems in close collaboration with on-site personnel, it can integrate AI and data utilization into business processes.
As a result, data analysis is more likely to be used on a daily basis in field operations such as quality control, equipment maintenance, and demand forecasting, rather than being limited to the efforts of a few specialized departments.
This will enable the promotion of cross-departmental data utilization.
In the manufacturing industry, data is often scattered across multiple departments such as factories, quality control, procurement, and logistics, which can limit DX initiatives to individual departments.
FDE's key feature is its ability to design systems while understanding the entire business, enabling the creation of mechanisms that facilitate cross-departmental data utilization.
For example, it is believed that this will enable initiatives that enhance decision-making across the entire organization, such as quality forecasting by linking production data and quality data, and supply chain optimization by linking demand forecasting and production planning.
Organizations are more likely to accumulate implementation capabilities.
When relying on external vendors to advance DX (Digital Transformation), a challenge arises: the know-how gained is not retained within the company once the project is completed.
By incorporating FDE into your organization, you can accumulate knowledge about system design and data utilization within the company, making it easier to build a system that can continuously promote DX.
Furthermore, having personnel with implementation experience makes it possible to make realistic technology choices and project designs when planning new DX themes.
We can create DX themes starting from the field.
FDE understands on-site operations, identifies challenges, and designs solutions using data utilization and AI technology. Therefore, it acts as a deterrent against the "top-down approach" that is common in many companies.
For example, promoting DX starting with themes directly related to on-site challenges, such as predictive maintenance using equipment data or anomaly detection using quality data, makes it easier to achieve actual business improvements.
Types and characteristics of FDE adoption
There are several ways to integrate FDE into an organization.
It is important to select the optimal method according to the company's DX maturity level and organizational structure.
1. In-house development of FDE (Fuel Deposition Engine)
First, there's the option of hiring and training FDE (Functional Development Engineer) personnel in-house. Having individuals with a deep understanding of the company culture and business processes can drive DX (Digital Transformation), potentially leading to the greatest competitive advantage in the long term.
Furthermore, the accumulation of implementation capabilities within the company leads to the creation of new DX themes and continuous improvement.
On the other hand, individuals possessing both a strong business understanding and advanced technical skills are rare in the market, making recruitment and training challenging.
2. Hired through dispatch from external partners.
Next is the method of utilizing FDE (Field Development Engineer) personnel from external companies on a project-by-project basis. This allows you to secure highly skilled personnel in a short period of time, thus accelerating the launch of DX projects.
Another advantage is the ability to utilize engineers with specialized knowledge in specific areas such as AI and data utilization.
However, relying too heavily on external personnel can make it difficult for know-how to remain within the company, so it is important to design projects with knowledge transfer and in-house development in mind.
3. Companion-type support (hybrid model)
This model involves external FDEs and internal personnel jointly driving the project. In the initial stages of the project, the external personnel take the lead in implementation, gradually transferring their knowledge to the internal members.
This method is well-suited to the organizational structure of Japanese companies and is characterized by its ease of achieving both the launch of DX and in-house development.
To ensure success, it is crucial for management to clearly define the ultimate goal of in-house production and simultaneously advance a plan for developing internal talent.
What Macnica considers FDE-type support to be
At Macnica, we support manufacturing DX with an approach similar to FDE's philosophy. Macnica engineers go into the customer's site, work together to organize business requirements, and proceed with system implementation. We don't just make recommendations like consultants, nor do we develop according to specifications like system integrators; our ultimate goal is to "make it usable in the field."
What we place particular emphasis on is designing a system where knowledge remains within the company after the project is completed. While external engineers lead the implementation, we work alongside internal members to help them understand "why it's built that way"—a support model that incorporates on-the-job training (OJT) type knowledge transfer. This allows a single initiative to lead to the creation of a system that can independently handle the next DX theme.
The concept of FDE itself is still relatively new, and examples of its application in the manufacturing industry are still being accumulated across the sector. Macnica also sees this approach as a promising way to promote DX, and is working on it through both on-site implementation and in-house development support.
FDE: An option with the potential to advance manufacturing DX
The root cause of the stagnation in manufacturing DX is not a lack of technology, but rather the fact that "development cycles cannot keep up with the speed at which on-site challenges change," "there is no one to bridge the gap between on-site needs and development," and "there is no one responsible for implementation who can guarantee a return on investment." FDE has the potential to simultaneously resolve these issues by utilizing the latest technologies and connect DX to actual business transformation.
If you are facing challenges such as "We want to implement AI in the workplace," "Development takes too long and DX is not progressing," or "The effects of DX investment are not easily visible," then it is worth considering using FDE.
Please feel free to contact us for details on Macnica 's FDE-type support services, case studies, and more.