While the push to “advance DX” is gaining momentum, its interpretation varies significantly depending on one’s position. Frontline staff often envision it as “introducing new systems or tools,” while management sees it as “transforming the very nature of the business by leveraging AI and data.” This discrepancy frequently leads to misaligned discussions, where tool implementation proceeds ahead of strategy, often failing to deliver the expected results.
This article clarifies what DX fundamentally is, explains its distinction from IT modernization (which is often confused with it), and provides a straightforward guide on where to actually start.
What is DX?
While the push to “advance DX” is gaining momentum, its interpretation varies significantly depending on one’s position. Frontline staff often envision it as “introducing new systems or tools,” while management sees it as “transforming the very nature of the business by leveraging AI and data.” This discrepancy frequently leads to misaligned discussions, where tool implementation proceeds ahead of strategy, often failing to deliver the expected results.
This article clarifies what DX fundamentally is, explains its distinction from IT modernization (which is often confused with it), and provides a straightforward guide on where to actually start.
DX stands for “Digital Transformation.” While the term itself may sound complex, the concept is quite simple.
DX refers to leveraging digital capabilities to rethink how a company creates value and conducts its work, transforming these processes into better forms.
The key point here is that DX is not about implementing systems as an end goal. Its essence lies in using digital technology as a catalyst to rethink previously accepted workflows and decision-making processes, ultimately driving tangible results.
For example, digitizing paper application forms makes work more convenient, but that alone doesn’t constitute DX. The next step is to ask, “Why is this application necessary?” or “Could we reduce the procedures altogether?” and redesign the entire workflow. Only when such changes emerge beyond mere convenience can we say we are approaching DX.
Digital adoption facilitates smoother work handoffs, ensures decisions aren’t dependent on specific individuals by making them reproducible, and improves customer experiences. The key indicator of true DX is whether these changes enhance the company’s strengths and drive tangible results.
The Difference Between IT Implementation and DX
A term often confused with DX is “IT implementation (digitalization).” Clarifying the difference between the two helps align internal understanding.
IT implementation involves replacing existing business processes with digital equivalents. Typical examples include switching paper documents to web-based applications, moving Excel management to the cloud, and processing attendance and accounting through systems. IT transformation holds significant value in making tasks easier, reducing errors, and improving operational efficiency.
DX, however, goes beyond this. It involves a mindset that delves into how to leverage the results of implementing tools, transforming workflows, decision-making criteria, and the value delivered. The difference between IT transformation and DX becomes clearer when applied to actual business operations.
Specific Example: “Customer Inquiry Handling”
For instance, in handling customer inquiries, IT solutions primarily involve setting up inquiry forms or introducing chat tools. This reduces the effort required for phone support and makes it easier to manage response statuses.
In contrast, DX involves analyzing collected inquiry data to visualize common concerns and stumbling blocks. By incorporating these insights into proactive guidance and user flows, the volume of inquiries themselves can be reduced. This ultimately leads to shorter response times and improved customer satisfaction.
Specific Example: “Field Handover”
The difference is also clear in field handover. IT implementation achieves some benefits by digitizing paper manuals and storing them in shared folders. However, DX goes beyond mere procedure manuals to organize decision-making criteria, such as “Why make this judgment?” and “How to approach exceptions when they occur.”
By creating a system that ensures consistent quality regardless of who is assigned, it prevents reliance on specific individuals. This stabilizes operations on-site even when personnel change.
Specific Example: “Sales and Customer Acquisition”
The same applies to sales and customer acquisition. Implementing a reservation system or increasing social media posts are IT initiatives. With DX, we leverage the data gained from these efforts to analyze “what types of customers are most satisfied” and “which offers are most frequently chosen.” Based on these insights, we optimize plan content and communication methods, leading to improved satisfaction, word-of-mouth referrals, and repeat business.
Thus, even when using the same digital tools, the key difference with DX is that it doesn’t stop at mere convenience—it designs systems that drive tangible results.
Why DX is Trending Now
The reason DX is receiving so much attention isn’t just a passing trend or something limited to a few advanced companies. The underlying factor is that the changes in the society and business environment surrounding us are accelerating at an unprecedented pace. Simply continuing with traditional methods increasingly risks putting businesses at a disadvantage without them even realizing it.
For example, the following changes can be cited:
- Customer behavior has shifted to being “internet-centric” (searches, reviews, reservations, etc.)
- Labor shortages have increased the burden on frontline staff
- External factors like rising prices and logistics changes have made cost management more difficult
- Competitors have leveraged digital tools to improve speed and quality
In this environment, relying solely on traditional methods or human effort is showing its limitations. What is now required is a mindset that rethinks operations and systems themselves using digital power, transforming them into stable, low-burden models. DX is being prioritized as the means to realize this approach.
DX does not equal AI implementation. Common pitfalls
One reason DX becomes difficult is an approach that prioritizes means over ends—like “just implement AI” or “just move to the cloud.” Of course, both AI and the cloud are useful tools that can become powerful assets when used effectively. However, if the purpose for implementation and the desired changes remain vague, the resulting systems often fail to fit the actual workplace. This leads to the situation where “it was implemented but isn’t being used.”
A common stumbling block follows this pattern:
1. Implementing tools just because they’re trendy
2. The field doesn’t know how to use them, leading to increased workload
3. The tools don’t take root, and everyone reverts to old ways
4. “DX just isn’t feasible for us”
The scary part of this cycle is that even though the failure stems not from DX itself but from the “wrong order of implementation,” the only lasting impression is a reluctance toward DX. Tools don’t deliver results the moment they’re introduced. If you don’t review everything—including on-site workflows, role assignments, and data handling—it can actually increase the burden. That’s precisely why the order matters to avoid this pitfall.
First, define “who” you want to benefit and “what positive changes” you aim to achieve. For example: “Reduce customer inquiries and speed up responses,” or “Accelerate quote creation to avoid losing sales opportunities.” Make the desired changes concrete. Only then should you select tools as necessary means. In essence, DX isn’t about implementing AI or cloud systems as an end goal—it’s fundamentally about rebuilding systems to drive tangible results.
Three Key Decisions Management Must Make to Advance DX
DX cannot be driven solely by frontline efforts. In fact, leaving it entirely to the frontlines often leads to tool implementation becoming an end in itself, or departments proceeding independently, resulting in fragmented progress that fails to achieve overall optimization. Consequently, expected outcomes become difficult to achieve.
The first essential step is for management to establish the foundation for progress. Ambiguity here halts decision-making midway, leaving frontline staff wondering, “What exactly do you want us to do?”
Management must decide on three major points:
① Articulate the “Why”
- What kind of company do we want to be chosen by customers in 5-10 years?
- What additional value will we deliver to customers to achieve this?
DX is a means; the goal is “maximizing the value provided to customers.” For example, reasons for being chosen vary by company—it could be “prompt responses,” “reassuring explanations,” “intuitive navigation,” or “accurate delivery times.” Without this defined, decisions on whether to prioritize efficiency or service quality improvement, or how far to extend investments, will constantly waver. Conversely, if the value definition is articulated, field improvement proposals can be evaluated by “Does this contribute to that value?” reducing unnecessary investments and aimless deliberations.
② Decide “Who Decides What and How” First
Merely issuing a directive to “advance DX” won’t sustain frontline momentum. Since DX involves multiple departments like sales, administration, operations, and accounting, decentralized decision-making leads to inconsistent priorities and stalls.
What’s needed are rules defining “which issues to tackle first,” “who makes final decisions,” and “investment limits.” By pre-establishing decision-making forums, responsible parties, and evaluation criteria, improvement proposals align on a common axis, preventing interdepartmental confusion and rework. To sustain DX, establishing a “decision-making framework” takes precedence over technology.
③ People and Culture
Data utilization and improvement methods aren’t fixed. Without a culture of testing small changes, learning, and iterating, implemented tools become underutilized.
DX doesn’t come with a predefined set of correct steps; it involves trial and error to find the approach that fits your company. Without a culture that ensures time for learning, allows questions when things are unclear, and avoids blaming failures, the front lines will become paralyzed. If the environment fosters the mindset that “it’s your fault if you can’t use it,” no one will touch the tools, and they’ll just sit idle. Conversely, if there’s a culture that encourages sharing reasons for setbacks and making improvements, operations will gradually stabilize, and results will accumulate.
What management must provide is an attitude that values taking risks and an environment that enables continuous learning. The success of DX hinges less on the tools themselves and more on whether an organization can be built that will keep using them.
Where to start? Your “First Steps” Checklist
When it comes to DX, it’s easy to feel overwhelmed, wondering where to begin. But you don’t need to start with major overhauls or expensive systems. The key is to identify small pain points within your current operations and streamline them with better processes.
That’s why we’ve prepared this checklist of actionable steps to kickstart your DX journey, arranged in order of ease. By working through them sequentially, the “must-do” tasks will naturally become clear.
DX is a concept for “strengthening companies through digital means.”
DX isn’t merely about introducing IT tools or AI. It’s about using digital technology as a catalyst to rethink how work is done and how decisions are made, creating systems that reduce the burden on the front lines while driving results.
If IT implementation is about “making tasks easier,” then DX is about “strengthening the very approach to creating value.”
The key is not to aim for major reforms from the start. Identify one problem at the front lines, test a small solution, verify its effectiveness, and build upon that improvement incrementally. This accumulation ultimately strengthens the entire organization.
An example of DX in healthcare is “DIP Ceph,” an AI cephalometric analysis support system for orthodontics. DIP Ceph streamlines analysis tasks, helping create an environment where doctors can focus on core activities like diagnosis and patient explanation.
Such specialized initiatives can serve as useful reference points when considering DX. For detailed features and usage scenarios, please check the official introduction page.
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