Designers are getting increasingly busy, but why is the time they actually spend on design becoming less and less?

In the R&D departments of manufacturing enterprises, complaints like this are often heard: "There are too many projects and not enough staff, designers are working overtime every day." Especially in the context of ever-increasing product categories, frequent changes in customer demands, and continuously shortened development cycles, the design department always seems to be in a state of insufficient resources.

Faced with this situation, the most immediate response of enterprise management is often to add R&D personnel, adjust project plans, or introduce new design software and AI tools. However, our practice of R&D management consulting finds that the busyness of the design department is not entirely due to the excessive workload, but may also be that a large amount of time is consumed by low-value repetitive work.

A question worth pondering for managers is: designers work ten hours a day, how much time do they actually spend on thinking about product design, solving technical problems and optimizing design solutions?

What exactly are designers busy with in a day?

Let's observe a typical working day of a mechanical design engineer in a manufacturing enterprise.

Arriving at the company in the morning, he first deals with the drawing problems fed back by the production department. Then the procurement department inquires whether a certain part can be replaced, because the original supplier cannot deliver the goods on time. Just as he is about to continue the design of yesterday, the project manager notifies him that the customer has modified the technical requirements, and the 3D model and BOM need to be adjusted.

In the afternoon, he attends the project progress meeting, and prepares the design review materials after the meeting. During this period, he also needs to look for the drawings of similar products in the past, hoping to learn from the original design scheme. However, since the historical documents are scattered in different project folders, it takes a long time to find the relevant materials, and there is only the final design result on the drawings, without explaining why such a structure was adopted at that time.

When he can finally concentrate on the new product design in the evening, another project has an on-site assembly problem that requires urgent support.

This engineer is very busy all day, and he has indeed dealt with a lot of work. But careful analysis will find that the time actually spent on new product design, technological innovation and scheme optimization may only account for a very small part.

This is exactly the problem that many R&D departments tend to ignore: we usually count how many working hours designers have invested, but rarely analyze how much design value these working hours have created.

Excessive design changes are eroding R&D resources

In the product development process, design changes are inevitable. Changes in customer demands, technological progress, and regulatory adjustments may all require re-adjustment of the design scheme. But not all design changes are of the same nature.

Some changes are reasonable demand changes, while others are caused by inadequate preliminary work. For example, after the design is completed, it is found that the understanding of customer requirements is wrong; when entering the trial production stage, it is found that the product structure is not conducive to manufacturing and assembly; when procuring, it is found that the selected parts are difficult to obtain; after the product has quality problems, it is found that the same failure has occurred in other previous projects.

These problems often mean that designers need to modify the models, drawings and BOM again, recalculate, re-review, and even reorganize the tests. One design change may also cause a chain adjustment of other parts and systems.

On the surface, the designers have completed a lot of work, but a considerable part of it is only to correct the problems that were not identified or solved in the early stage.

For example, a certain R&D project invested 300 hours, of which 200 hours were used for normal design and development, and the other 100 hours were used for design rework. If the enterprise only sees that the project has invested 300 hours, it is easy to draw the conclusion that "R&D resources are insufficient".

However, if the rework time can be reduced by half by improving demand review, design review, manufacturability analysis and historical problem prevention, the enterprise will release 50 hours of R&D resources equivalently.

Therefore, to evaluate R&D efficiency, we should not only look at how many hours designers work, but also pay attention to how much time is spent on repetitive design that could have been avoided.

For R&D managers, in addition to project progress and design working hours, they should also analyze the causes of design changes, the stages where they occur, the cost of rework, and how many of these problems could have been detected in the early stage of design.

Enterprises have a large number of design materials, but have not formed real design knowledge

Another easily overlooked problem is that designers spend a lot of time looking for information.

In many enterprises, the R&D department has accumulated drawings, 3D models, technical specifications, design review records, test reports and quality problem reports for many years. But when designers need to refer to historical projects, they often do not know where the materials are, or who to turn to.

What is more noteworthy is that even if the historical drawings are found, it may not be possible to truly understand the design decisions at that time.

Why choose this material? Why adopt such a tolerance? Why is the structure designed like this? Have other solutions been considered? Is this dimension related to the quality problems that occurred in the past?

If the enterprise only saves the final drawings but does not retain the basis for key design decisions, then these materials can only be reused repeatedly, but it is difficult to form design knowledge that can be continuously inherited.

Young engineers may need to re-analyze problems that senior engineers have already solved, while experienced engineers have to repeatedly explain the same design logic.

This is also the reason why some manufacturing enterprises have complete R&D databases, but their design efficiency has not improved significantly.

In recent years, more and more enterprises have begun to try to use AI for design material retrieval, similar product recommendation, standard query and historical problem analysis. This undoubtedly provides new possibilities.

But whether AI can really play a role depends to a large extent on whether the enterprise has established a clear and reliable design knowledge system. If the historical materials only have design results but no design basis; only problem records but no cause analysis and experience feedback, then AI can help enterprises find files faster, but may not be able to help engineers make better design decisions.

Therefore, R&D digitalization cannot be simply understood as centrally storing drawings and documents. More importantly, it is necessary to establish the correlation between design standards, design basis, historical failures and technical solutions, so that past experience can truly serve future product development.

The busier you are, the less time you have for improvement, and the R&D department is prone to fall into a vicious circle

In the process of R&D consulting, we often find a phenomenon: the busier the R&D department is, the harder it is to spare time for design standardization, technical training and experience summary.

For example, a young designer has doubts about the technical scheme when designing a certain structure. But senior designers are busy with other projects and have no time to discuss. The young designer has to continue to complete the design according to his own understanding, until the design review, he finds that there are obvious problems in the whole structural scheme.

If a ten-minute technical discussion is carried out in the conceptual design stage, the problem may be solved easily. But after the design of the model, drawings and related parts are all completed, making modifications may take hours or even days.

As a result, the department falls into a cycle:

The project is too busy to have time for preliminary technical discussions; insufficient preliminary discussions lead to an increase in later design problems; the increase in design problems further takes up the time of engineers.

The same logic also applies to R&D standardization and talent training. Due to the tight project schedule, the department has no time to sort out the standard part library, summarize design experience, improve technical specifications, and no time to train young engineers. As a result, the next project still relies on a small number of senior designers to solve problems, and R&D resources continue to be tight.

This shows that the improvement of R&D efficiency cannot only rely on individual work efficiency, but also requires management to consciously invest resources to reduce repetitive work in the future.

For example, establishing a design knowledge base, improving the product platform and standard part system, carrying out review of historical failure cases, and organizing cross-professional technical discussions in the early stage of design. These activities may not directly increase project output in the short term, but they can significantly reduce the development cost of future projects.

Truly effective R&D management not only ensures that the current project is completed on time, but also makes the next project easier to complete than the previous one.

Over-reliance on senior designers: is it a capability advantage or an organizational risk?

Many manufacturing enterprises have several very excellent senior designers. They are familiar with product structures, manufacturing processes and historical problems, can quickly judge technical risks, and can always find solutions when encountering complex problems.

They are often the busiest people in the R&D department and the most relied on by the enterprise.

But from the perspective of organizational management, this phenomenon is worthy of vigilance.

If only one person in the enterprise truly understands a certain product, if key design decisions must be made by a certain senior engineer, and if young designers cannot complete conventional designs independently, then the enterprise actually concentrates a large amount of R&D capabilities on a small number of individuals.

Once these personnel leave, retire, or take on too many projects at the same time, the R&D system may be significantly impacted.

More importantly, when senior designers are engaged in fire-fighting tasks for a long time, they also lose the time to carry out technical research, guide young engineers and establish design standards.

Therefore, managers should not only care about how to make these excellent engineers take on more projects, but also think about how to transform their experience into organizational capabilities.

For example, transform mature design schemes into reusable product platforms, transform common technical judgments into design criteria, transform historical failures into design inspection requirements, and transform personal experience into technical knowledge that young engineers can learn and apply.

A mature R&D organization does not always rely on the best engineers to solve problems, but can enable more and more engineers to no longer encounter the same problems repeatedly.

AI can improve design efficiency, but cannot replace the R&D management system

With the development of generative AI, intelligent CAD and design automation tools, enterprises are gaining more opportunities to improve R&D efficiency.

AI can help engineers find technical materials, generate documents, assist in analyzing design schemes, and even automatically identify some design errors. These applications can reduce a large number of transactional work.

But one problem cannot be ignored: If the original R&D process of the enterprise has defects, AI may only make the inefficient work executed faster.

For example, if the requirement definition is unclear, AI cannot automatically ensure that the design input is correct; if there is no effective mechanism for design review, automatically generating more review materials may not reduce design risks; if historical quality problems do not form effective design prevention requirements, AI may not know what to focus on avoiding in the next design.

Therefore, before promoting the application of AI in R&D, enterprises first need to understand which activities in R&D work really create value, which are necessary management activities, and which are wastes that should be eliminated.

From the perspective of R&D management, at least three aspects need to be focused on.

First, reduce unnecessary design rework. By improving demand management, design review, DFMEA, manufacturability review and verification mechanism at the development stage, solve problems as much as possible in the early stage of development.

Second, improve the reuse ability of design knowledge. Through product platformization, modularization, standardization and design knowledge management, reduce repeated development and the dependence on the experience of individual personnel.

Third, make the R&D process match the digital tools. On the basis of clear business processes, clear division of responsibilities and effective technical standards, use AI and digital systems to reduce the time for information retrieval, repeated entry, document preparation and cross-departmental communication.

In this way, AI can truly help designers devote more energy to technical judgment, risk prediction and product innovation, instead of simply speeding up the original work rhythm.

What managers really should focus on is not how busy the designers are

For the R&D department, being busy does not mean low efficiency. After all, the development of complex products itself requires a lot of engineering investment. But if designers are busy with modifying drawings, repeatedly looking for materials, explaining the same problems, handling production abnormalities and conducting design reviews repeatedly for a long time, then managers need to re-examine the organization mode of R&D work.

Instead of just asking "Do we have enough designers?", it is better to answer several questions first:

1. Among the working hours of designers, how much time is actually used for new product design and technical problem solving?

2. Among the design changes, how much is rework that can be prevented in the early stage?

3. Can the design experience and quality problems in the enterprise's historical projects be effectively utilized in the next development?

4. Is the time of senior designers used for key technical decision-making and talent training, or for constantly dealing with recurring problems?

5. Do the existing R&D processes and digital tools reduce the workload or increase new management burdens?

These questions are more helpful to judge the real level of the enterprise's R&D efficiency than simply counting the number of R&D personnel, the number of projects and overtime hours.

Give designers' time back to real design work

The competition of manufacturing enterprises in the future is not only the competition of product performance and R&D speed, but also the competition of R&D resource utilization efficiency.

When products are getting more and more complex, technology is updated faster and faster, and talent costs are constantly rising, enterprises cannot rely on adding engineers infinitely to solve the problem of R&D efficiency.

What R&D management really needs to change is to release engineers from repetitive transactional work, and let them devote more time to demand understanding, technical research, scheme optimization and risk prevention.

The ultimate goal of R&D efficiency improvement is not to let designers complete more work, but to let them have more time to complete truly valuable designs.

This article is from the WeChat official account "TPP Management Consulting", the author: TPP Management Consulting, authorized to release by 36Kr.