Uncovering a New Equation for Enhancing Corporate Value
Fujitsu’s Financial and Non-Financial Analysis Project, made up of a cross-organizational team of personnel, is taking on the challenge of clarifying the connections between financial and non-financial indicators. We take a broad view of initiatives related to non-financial indicators, such as those that help foster our organizational culture and demonstrate the fulfillment of our social responsibilities, as measures for advancing our strategy. The project’s aim is to clarify which of these initiatives effect changes in intermediate factors and thereby contribute to financial performance and the sustained enhancement of corporate value. We spoke with members of the Financial and Non-Financial Analysis Project, who lead hypothesis building, data collection, and causal analysis, about the aims of the project and their expectations for the analysis. (This cross-talk discussion was held in July 2026.)
Mariko Yamada
Head of Sustainability Division
CEO Office
Yoshio Masuda
Head of Corporate Finance Unit
Kana Tajima
Head of CRO Office
Seiichi Nakamura
Head of Business Strategy Design
Enterprise Strategy Promotion Unit
Susumu Amano
Head of Employee Success Unit
Masayuki Wada
Head of Corporate Digital Unit
Please tell us more about the purpose of the Financial and Non-Financial Analysis Project, who its members are, and what expectations you bring to the project.
Yamada
The purpose of the Financial and Non-Financial Analysis Project is to clarify how human resource measures encourage changes in the mindset and behavior of employees as well as how we can leverage Fujitsu’s proprietary digital technologies to change the way employees engage with customers. Working from the hypothesis that intermediate factors exist upstream of financial results, we are seeking to clarify how those factors connect to financial performance. A distinguishing feature of this project is that we conduct analysis that can be applied to frontline activities rather than ending with an academic analysis.
Another major feature of this project is that various business divisions with differing backgrounds and missions collaborate across the organization, with CSSO Takashi Yamanishi orchestrating such collaboration. I participate as the overall coordinator from the Sustainability Division of the CEO Office.
Masuda
From a financial perspective, a question we frequently receive from investors these days is, “When and in what form will the effects of a given measure lead to improvements in your financial performance?” The use of AI is a prime example, but it is by no means the only one.
Fujitsu constantly invests in people, including raising employee compensation levels, expanding opportunities for reskilling, and creating an environment in which employees can work autonomously. What investors really want to know is how these initiatives translate into future growth and higher profitability, rather than being only a record of activities.
For example, even if non-financial indicators, such as employee engagement and diversity leadership, improve and progress according to plan, do they in turn create new value and spur innovation in ways that lead to greater customer value and growth in earnings? We are being called upon to prove such causal relationships clearly exist.
The purpose of disclosing non-financial information is not simply to report indicators of progress. I believe that what truly matters in doing so is explaining how investment in human capital and AI helps realize enhanced corporate value and sustained growth. We intend to clarify the connections between changes in non-financial indicators and business results more than ever before and to use the understanding of said connections as a basis for engaging in constructive dialogue with investors.
Tajima
I am here representing the unit that promotes NPS®,*1 one of the non-financial indicators. Relationships with customers are a strength of Fujitsu and a major pillar of business. How do these relationships impact earnings? Starting with this question, what should we strengthen in order to achieve more ambitious targets, and how can employees engage with customers and find building relationships rewarding in their work? We want to find answers to these questions using our own technology.
Nakamura
The Enterprise Business focuses on the manufacturing and distribution sectors and is essentially a market-facing organization, which places us in proximity to earnings and financial results. While we are expected to deliver high growth in orders and revenue, we see the challenge as being whether we can sustain that growth simply by managing the outcome of sales activities. Don’t we need a deeper understanding of how the pipeline is formed and how it leads to orders? To that end, we have come to believe that we cannot achieve sustainable growth unless we look closely at the quantity and quality of a series of actions and even at the skills that underpin them. Our expectation is to bring to light how these non-financial elements connect with financial results, using data and causal analysis rather than relying on conventional experience and intuition, and to obtain clues that lead to behavioral change.
Tajima
We can picture the connections in our minds like a logic tree. These behavioral patterns are desirable in order to achieve financial targets, and this kind of learning is necessary for realizing those behavioral patterns. Using our technology, we aim to bring to light elements that have not yet come to the surface: the relationships among the various internal initiatives and measures as well as the impact those initiatives and measures have on each employee’s behavioral patterns and mindset.
Amano
The human resources unit places importance on people changing their behavior, which in turn changes the organization, changes the business, and changes the value we deliver to customers. As a management foundation for this, we believe we should build a mechanism that connects financial and non-financial elements, and we hope this project will go so far as to clarify the entire chain of connections from employee behavior to the value we deliver to customers.
For Fujitsu to grow sustainably, we must enhance the value of our human capital, the results of which will permeate our business and lead to the sustainable growth of the Group. To make that happen, we want to see in high resolution where we stand today and where the essence of the challenge lies.
Wada
I currently serve as a leader in the Corporate Digital Unit, which spearheads our internal digital and AI transformation efforts. In the context of AI adoption, many companies aim to reduce costs with AI. We too attach great importance to cost reduction through greater efficiency, but we believe that is not the only objective. Rather, the question is how to enhance the value of people and empower them through the adoption of AI. We want to focus our efforts on how to raise corporate value in this way. It is, admittedly, a difficult challenge. A major theme for us is to firmly grasp and visualize what factors intervene between the adoption of digital technology and the empowerment of people and behavioral change, and between behavioral change and top-line expansion and improvement in corporate value.
Yamada
To enhance the value of our people, the foremost example of intangible capital, Fujitsu has long worked to create an environment in which employees can work innovatively and with a sense of belonging, including through measures such as education and workstyle reform. We look end to end at how this undertaking translates to corporate value. It is highly encouraging that so many people are genuinely committed to this project.
Wada
At present, we are meticulously introducing AI internally while also advancing operations by applying AI to every business process. However, the adoption of AI and its effects and outcomes do not connect in a straightforward manner. A certain distance separates the adoption of digital technology from financial management indicators. We also aim to visualize what intermediate factors lie between the two and how they exert an impact, while clarifying how the adoption of AI realizes improvements in corporate value.
Masuda
Fujitsu has set financial targets that are extremely high even within the industry, and we continue to take on the challenge of achieving them. People generally discuss this from the perspective that initiatives on the non-financial side, such as human capital and organizational culture, lead to improved performance, but I believe the reverse perspective is also important.
For example, in the process of setting lofty targets and striving to achieve them, employees grow and the organization’s sense of unity strengthens, which can in turn foster engagement and a culture of taking on challenges. In addition, the experience of success that comes from generating results heightens employees’ confidence and sense of fulfillment in their work while also serving as a driving force for further growth.
In other words, I believe there may be a two-way relationship in which non-financial indicators not only generate financial results, but financial results themselves bring a virtuous cycle to the organization and its people, leading to improvement in non-financial indicators.
Going forward, we intend to shed more light not only on the impact that human capital and organizational culture have on earnings but also on how taking on lofty targets and achieving results affect engagement, innovation, and the enhancement of organizational capabilities. Rather than viewing financial and non-financial elements separately, I believe it is important to demonstrate how the two interact with each other to create corporate value.
Please tell us what you learned from the initiatives that preceded this project and, more specifically, what the Financial and Non-Financial Analysis Project is currently seeking to accomplish.
Yamada
From this project’s analysis of the relationship between financial and non-financial elements, we did observe to some extent that placing emphasis on human resource measures, including employee training, changed behavior and also changed the way we approach customers. However, what the data revealed remained within the range of our expectations, and we did not reach the point of determining that “this measure holds the key” or “this initiative does not lead to results.”
Wada
Speaking on the topic of data, our earlier approach started from the data we already had and began with the assumption that, by visualizing the relationships among that data, a reasonably strong causal link—a single storyline—would emerge.
The approach we are now taking anew begins by drawing up several hypothetical scenarios along the lines of “there may be a relationship of this kind,” and then assembling the data necessary to verify those scenarios. While filling in the missing data, we analyze and verify whether the scenarios are correct. I feel that this approach is extremely important.
Amano
Holding a certain hypothesis of our own and envisioning scenarios such as “the problem may lie here” or “we want to dig deeper in this area” are, from the perspective of the division of roles with AI as well, surely important tasks that humans should undertake. As we look deeply into whether that hypothesis truly holds while verifying it with data, new discoveries also emerge, such as finding that the essential problem actually lays elsewhere.
Yamada
Based on that approach, Mr. Masuda and Ms. Tajima conducted interviews with high performers in order to formulate hypotheses.
Tajima
We are building hypotheses while interviewing sales personnel known as high performers who deliver outstanding results.
As every company, competitors as well as Fujitsu, makes use of AI, the key to differentiation ultimately comes down to how we communicate with customers and build relationships with them, as well as to how we can support their decision-making. One insight from the interviews is that one of the strengths of sales personnel lies in their ability to get close to customers and build good relationships. When we interview the heads of sales divisions, who are the very embodiment of high performers, they say that building relationships alongside strong proposals, as two parallel axes, is extremely important. We have a strong interest in what behaviors are involved in connecting such relationships to deal outcomes and financial impact.
We have not yet reached the point of unraveling the secrets behind the master craftsmanship that we want to see. The next step is to raise the accuracy of the data while placing as little burden as possible on frontline personnel. These behaviors and the customer business context data obtained through them should be precisely what leads to value creation by Fujitsu in the AI era and to differentiation from other companies.
Wada
For example, we are building a mechanism whereby, when someone records on a smartphone by voice that “I visited so-and-so and had a conversation about such-and-such,” the system converts that voice data into structured data and automatically compiles it into a database.
Nakamura
We have high expectations for this mechanism. Sales behavior has traditionally been difficult to visualize in some respects, but taking this project as an opportunity, we are developing a mechanism to visualize behavior together with Mr. Wada’s team. If we are able to collect behavioral data while reducing the input burden on sales personnel as much as possible, that in itself will be one achievement of this project.
Masuda
We have discovered that when we conduct interviews with high performers together with Ms. Tajima, dig into successful cases, and extract the key intermediate factors, we can then deploy those findings to other divisions as well. To that end, we are currently organizing the successful cases that warrant in-depth analysis. In parallel with data collection, we analyze our hypotheses and the collected data using Fujitsu Causal AI,*2 a proprietary technology developed by Fujitsu Research.
This proprietary causal analysis technology is shedding light on a wide range of insights. In recent years, we have strengthened our approach to decision-makers in business operations and to customers’ management teams. As part of this, we are increasing the occasions on which Mr. Wada and I visit customers, and on which our President, Takahito Tokita, and our CFO, Takeshi Isobe, call on them directly. As a result, we are seeing that the rate of winning deals does indeed rise dramatically. Moreover, we are even coming to see at which stage and at what timing a visit leads to winning a deal. Furthermore, insights such as the fact that employees who actively participate in training have a very high win rate on deals, and which types of training are effective, are gradually becoming clear.
Amano
When people see their own data visualized, their commitment to change grows. They do not act because top management or a division head tells them to, nor because human resources tell them to. A momentum emerges in which the organization changes autonomously, driven by a desire to make their own organization better.
In addition, once the data shows that certain actions work, the ROI*3 of human resource measures also rises. Human resource measures truly span a wide range, so implementing them comprehensively simply drives up costs. This analysis is important precisely so that we can act with a clear sense of purpose and consider which approach among the many measures delivers the highest ROI.
Nakamura
In the market division as well, we are indeed translating the results of analysis by Fujitsu Causal AI into actions. We have come to understand that strengthening points of contact with customer executives leads almost directly to orders. Based on these success factors, we have begun initiatives to formalize this knowledge into a mechanism called the executive sponsor system, having experts such as Mr. Masuda meet with customer executives at the appropriate timing and connecting this to stronger relationships and the creation of deal opportunities.
Tajima
As came up in the discussion just now, the range of people who collaborate in our approach to customers extends beyond the market division. If analysis makes clear that such collaboration ultimately leads to greater business performance and financial results, I believe it will also boost the motivation of employees in other divisions who cooperate with the market division.
Please describe the aim of future initiatives.
Nakamura
We have already begun applying Fujitsu Causal AI in ways such as holding workshops with customer executives, and it has been very highly regarded. Until now, projects such as RPA*4 have in some cases achieved no more than partial optimization of operations, but causal analysis cannot deliver sufficient effect unless we take a bird’s-eye view of the operations and data of the entire organization. I believe that is also why it is CxOs who take an interest in Fujitsu Causal AI. We want to master causal AI ourselves and connect it to proposals for optimizing our customers’ entire data architecture and overall operations.
Wada
For our non-financial analysis, nothing has been completed at this point. Rather, we see it as a process for analyzing cross-sections of the various transformations Fujitsu itself is undertaking. It is important that we continue to transform ourselves as well while clarifying the mechanisms by which non-financial factors lead to financial value, because what we see now is not the goal.
We constantly put the latest technology into practice internally, combining it with our own IP*5 and creating best practices through trial and error. That is what we call Customer Zero, in other words, putting an idea into practice internally. Rather than stopping at simply having introduced digital technology or AI, we visualize the value of the impact this generates. We place importance on moving these two initiatives forward together and delivering the results to our customers as our value proposition.
Amano
At present, we are still working within the framework of financial and non-financial factors to clarify which non-financial indicators, once achieved, lead to financial results, but there should be further scope beyond that. I believe the ultimate goal is to have all of this connected and visualized, showing whether we are truly solving the issues of our customers and society.
Masuda
My own purpose can be summed up as achieving “a better society for the next generation.” Through this causal analysis, I aim to strengthen the ability of Japanese companies to manage their businesses and, as a result, enhance the competitiveness and corporate value of Japanese industry as a whole. However, this is unlikely to succeed if Fujitsu works on it alone. That is why we are now holding frequent discussions with a wide range of companies. When I explain initiatives of this kind, many people tell us they very much want to work on them together with us. Many companies want to know, through causal analysis, which initiatives they should focus on and what holds the key to enhancing corporate value.
Even looking at prior research, causal analysis of financial and non-financial factors has not yet been fully completed, and studies remain at the level of correlation analysis. For this reason, I see the non-financial field as currently running up against a wall. If we can break through this wall with causal analysis, we should be able to start a movement where companies disclose non-financial data voluntarily in order to demonstrate the logic of value enhancement, rather than simply because it has been mandated, which in Japan is scheduled for 2027 under the SSBJ standard.*6 I hope Fujitsu will lead this movement and change the world.
Note
- *1 Net Promoter®, NPS®, NPS Prism®, Net Promoter System®, and the NPS-related emoticons are registered trademarks of Bain & Company, Inc., NICE Systems, Inc., and Fred Reichheld. Net Promoter Score℠ is a service mark of Bain & Company, Inc., NICE Systems, Inc., and Fred Reichheld.
- *2 A core technology developed by Fujitsu’s research laboratories and provided via Fujitsu Kozuchi, an AI platform. Fujitsu’s proprietary algorithms deliver a dramatic advance in the accuracy of causal analysis and a substantial increase in speed, enabling the analysis of large-scale data that was difficult with conventional causal analysis methods.
- *3 Return on investment: An indicator showing how much profit has been generated relative to the invested costs
- *4 Robotic Process Automation: Technologies and tools that use software to automate routine administrative work
- *5 Intellectual Property: Here, the term refers broadly to not only intellectual property that has been secured as rights, such as patents, but also to proprietary technologies and services.
- *6 A domestic standard established by the Sustainability Standards Board of Japan (SSBJ) to enable companies to disclose sustainability-related information in a consistent manner
