Masaki Oshikawa<\/strong><\/p>\n\n\n\n Executive Officer, Analytics Consulting Unit Head Director Jun Tamura<\/strong><\/p>\n\n\n\n Analytics Consulting Unit Deputy Head Director, Data Scientist Our business falls broadly into two main areas: professional services, in which specialist personnel conduct data analysis, and product services, provided through SaaS products. What Tamura and I work on is support related specifically to analytics consulting within the professional services business that supports clients in their data utilization.<\/p>\n\n\n\n The professional services business covers all data utilization needs \u2014 from data utilization strategy formulation through algorithm development to cultivating data-literate talent. Concretely, this includes marketing analytics consulting \u2014 providing data analysis and consulting in customer relationship management (CRM) and marketing activities \u2014 and support for building the platforms that form the foundation of corporate data utilization.<\/p>\n\n\n\n In the product services business, we provide SaaS products including our own “Rtoaster” to promote data utilization. While new products are emerging in rapid succession with the rise of SaaS companies, there is also considerable feedback today that organizations have “implemented something but can’t make use of it.” What is needed, we believe, is the ability to identify what the optimal solution is for each client and to execute on it. Our data utilization talent with their diverse experience support from the concept stage through to execution, enabling DX that is both immediately effective and realistically achievable.<\/p>\n\n\n\n No. While the roles of consultant, data scientist, and engineer do exist, they are not sharply delineated. The boundary between consulting and data science in particular is blurry, and it is not uncommon for a project to be led by a data scientist in the senior role with a consultant participating as a member, depending on the project’s content.<\/p>\n\n\n\n I believe this is partly related to our organizational scale, but it also reflects a conscious intent: to avoid the downsides of strict division of labor and instead enable each individual to hold broad knowledge and skills and take on diverse roles. It’s not the case that consultants don’t need to do data analysis, or that data scientists don’t need management knowledge \u2014 we place great value on both roles crossing over into each other’s domains.<\/p>\n\n\n\n The Analytics Consulting Unit has approximately 200 members, broken down as roughly 150 data scientists and about 50 consultants. Comparing with when I joined BrainPad seven or eight years ago, the organization has grown by roughly 2.5 times. The consulting team was launched around the time I joined, so it has expanded steadily over the past several years.<\/p>\n\n\n\n It varies considerably depending on the scale of the project, but in the initial stages we often start small \u2014 a manager and one member \u2014 and the team grows as the project expands, sometimes reaching ten or twenty people.<\/p>\n\n\n\n In larger-scale projects, product development often becomes a major theme, and the team composition tends to center on data scientists and engineers. In those cases, consultants may take on a PMO role \u2014 acting as the bridge between clients and technologists, handling not just typical schedule management but also scope changes to algorithms and systems and the associated operational adjustments.<\/p>\n\n\n\n Project duration ranges from two to three months at the short end to two to three years at the long end. A PoC alone can take close to a year, and projects sometimes extend further when those results lead to full-scale system construction and operations support. Projects supporting the launch of a client’s DX promotion organization can also result in long-term partnerships spanning several years.<\/p>\n\n\n\n Many companies have accumulated enormous amounts of data through years of business activity, but are uncertain how to put it to use. While terms like AI adoption and DX have become widespread, the reality is that many companies have not yet mapped out a concrete path for how to combine data and AI or how to advance DX in practical terms.<\/p>\n\n\n\n For clients like these, we ask: “What management challenges are you actually trying to solve?” Data utilization is ultimately just a means to that end \u2014 and without clarity on the management challenge, even having data in hand won’t lead to effective use of it. Even when a project’s initial theme is technical, questions like these can come to the surface, and both data scientists and consultants may raise them.<\/p>\n\n\n\n Yes. When I join a project, I primarily approach it from the perspective of how to connect the management challenges that consultants have clarified with the data the client holds. I then translate that into the concrete specifics of “let’s proceed with data analysis in this way,” and actually execute the analysis. I often take on the role of data scientist through to the point where the findings are connected to final actions.<\/p>\n\n\n\n Thinking about it that way, once either a data scientist or a consultant reaches a certain seniority level, the boundary between them largely disappears and both end up covering a wide range of responsibilities.<\/p>\n\n\n\n Our approach also involves deciding on priorities to some extent. In an example from a manufacturing client, there was a need to improve productivity by leveraging the vast data accumulated across the factory. The data offered many angles of analysis, but executing each one individually would have required enormous resources. We therefore advanced the project by identifying the challenges to address first, taking into account the balance between impact and feasibility.<\/p>\n\n\n\n A consulting firm may produce a grand strategic proposal that is impressive in its own right, yet when it comes to the concrete execution stage, it is by no means rare for it to be “a cake that was never meant to be eaten.” At our company, we embed ourselves in the client’s actual field, develop deep understanding of both data and operations, and support data utilization that delivers genuine value.<\/p>\n\n\n\n That’s right. I have always had strong intellectual curiosity and wanted to work while learning about society, and had my sights set on consulting from the job-hunting stage.<\/p>\n\n\n\n At Accenture, where I joined as a new graduate, I handled clients primarily in technology-related sectors \u2014 including telecommunications, machinery, and electronics manufacturers \u2014 and was also involved in areas like AI and data analysis. Through that experience, I developed the desire to work with even higher-caliber data analysis professionals, and decided to move to BrainPad.<\/p>\n\n\n\n It was. The company had fewer than 200 employees when I joined, but I had been quite interested in it for some time as one of a small number of companies with particular strength in data analysis. I connected with one of the current directors in an interview, and came away feeling “I can do more interesting work here by putting my expertise to use” \u2014 which is what led me to join.<\/p>\n\n\n\n I joined BrainPad as a new graduate in 2014 and am now in my twelfth year. In graduate school I was in a mathematical statistics research lab, but I decided I wanted to use my data analysis background to do work that contributes to society rather than pursing purely academic research \u2014 which led me to BrainPad. The fact that the profession of “data scientist” was beginning to attract attention right around the time I was job hunting was also a major factor.<\/p>\n\n\n\n Very few. I felt that I was given a reasonable degree of autonomy relatively early on, and was trusted with work of real responsibility. By my second year I felt like something of a veteran, which brought pressure \u2014 but the sense of fulfillment was even greater, and I was able to enjoy my work.<\/p>\n\n\n\n We are aiming to actively open up data utilization domains that we have not yet been able to address. The top priority, we believe, is to expand our data utilization service lineup so that we can respond to every need our clients have.<\/p>\n\n\n\n We are also currently pursuing product development and commercialization drawing on the knowledge we have accumulated. The establishment of a subsidiary recently was part of that effort. In the business development domain as well, people with experience at the intersection of data and business are indispensable \u2014 and I hope we can create new businesses by putting consulting experience to work.<\/p>\n\n\n\n Alongside that, I want to place significant emphasis on growing the headcount as well. BrainPad as a whole currently has approximately 600 employees, with around 200 in the Analytics Consulting Unit \u2014 but when I think about the social impact we could be making, it still feels small. Looking toward a future organization of 1,000 people, we are currently building out the organizational structure and policies.<\/p>\n\n\n\n Since April 2024 I have been in the Deputy Head role, but I want to continue striving not only in my responsibilities as an executive but also as a practitioner who can further strengthen BrainPad’s technical capabilities from the technology side. I want to gradually increase the number of technically challenging projects \u2014 ones where we figure out how to apply the most cutting-edge technologies that are not yet deployed in society, and how to approach challenges that have not previously been solvable.<\/p>\n\n\n\n As the organization expands, I am also sensing the limits of our current structure. I will continue to explore how to grow the organization while preserving the qualities that have defined BrainPad up to now.<\/p>\n\n\n\n What emerged from the conversations with Executive Officer Oshikawa and Mr. Tamura was a firm conviction that this is not merely an analytics company, but an “execution force” that uses data to transform the quality of management decisions. The organizational structure in which consultants and data scientists cross over without fixed boundaries is a natural choice \u2014 one designed to avoid the downsides of strict division of labor and deliver consistent value end to end.<\/p>\n\n\n\n What I want to convey to prospective applicants is the unique environment for developing specialist expertise and business acumen at a high level simultaneously. With the company in an expansion phase targeting an organization of 1,000 people, there are also expanding opportunities to translate personal knowledge into product development and new business creation. For anyone with the aspiration to accelerate the social implementation of data utilization and transform the quality of decision-making in society itself \u2014 this is a place where the highest technical caliber and the deepest passion meet, a true frontier for intellectual curiosity.<\/p>\n\n\n\n ConsulNext Senior Consultant<\/strong> <\/a><\/p>\n\n\n\n
Completed a master’s degree in Engineering at the University of Tokyo Graduate School. Joined a major foreign consulting firm and worked on a variety of data utilization projects both in Japan and internationally. Joined BrainPad in 2017. Has a broad track record in DX support leveraging analytics technology across diverse industries and domains \u2014 including supply chain transformation using data such as order optimization with machine learning and logistics efficiency through mathematical optimization, advancement of sales activities, concept formulation support for launching medical data services, and support for building AI solution development structures. Has been in current role since July 2023.<\/p>\n\n\n\n
Joined BrainPad as a new graduate in 2014. In the web and entertainment industries, has provided support centered on digital marketing \u2014 including improvement of advertising products and analysis for marketing strategy planning. Also handles challenge resolution support in the areas of general trading companies and supply chain management (delivery optimization and order operations support based on demand forecasting). Has been in current role since April 2024.<\/p>\n<\/div><\/div>\n\n\n\nProviding Upstream, High-Expertise Support for Data Utilization<\/h2>\n\n\n\n
![\"\"](\"https:\/\/mirai-works.co.jp\/consulnext\/wp-content\/uploads\/2025\/06\/brainpad_ph01.jpg\")
<\/figure>\n\n\n\n\u2014 Mr. Oshikawa, could you tell us about BrainPad’s business?<\/h3>\n\n\n\n
\u2014 Your company invests heavily in data analysis. When providing support, are roles clearly divided into consulting teams, data science teams, and so on?<\/h3>\n\n\n\n
\u2014 Could you tell us about the current headcount in the professional services business?<\/h3>\n\n\n\n
\u2014 Could you tell us about project structure and duration?<\/h3>\n\n\n\n
Linking Management Challenges Deeply to Data Utilization \u2014 Providing Precise Support While Setting Priorities<\/h2>\n\n\n\n
![\"\"](\"https:\/\/mirai-works.co.jp\/consulnext\/wp-content\/uploads\/2025\/06\/brainpad_ph02.jpg\")
<\/figure>\n\n\n\n\u2014 I’d like to ask about the details of your projects. What kinds of challenges typically serve as the starting point?<\/h3>\n\n\n\n
\u2014 Mr. Tamura, you often step into projects as the leader of the technical team. Do you take a similar approach?<\/h3>\n\n\n\n
\u2014 Taking on company challenge resolution from the upstream seems like it would require substantial resources and time.<\/h3>\n\n\n\n
An Environment Where Professionals with Diverse Backgrounds Come Together<\/h2>\n\n\n\n
![\"\"](\"https:\/\/mirai-works.co.jp\/consulnext\/wp-content\/uploads\/2025\/06\/brainpad_ph03.jpg\")
<\/figure>\n\n\n\n\u2014 Next, I’d like to ask about your backgrounds. Mr. Oshikawa, I understand you joined Accenture as a new graduate?<\/h3>\n\n\n\n
\u2014 Moving from a large organization to BrainPad must have been a significant decision.<\/h3>\n\n\n\n
\u2014 Mr. Tamura, could you tell us about your background?<\/h3>\n\n\n\n
\u2014 Were there any surprises after joining?<\/h3>\n\n\n\n
Broadening the Scope of Data Utilization Support and Accelerating Social Implementation<\/h2>\n\n\n\n
![\"\"](\"https:\/\/mirai-works.co.jp\/consulnext\/wp-content\/uploads\/2025\/06\/brainpad_ph04.jpg\")
<\/figure>\n\n\n\n\u2014 Mr. Oshikawa, what is the vision for the consulting services division going forward?<\/h3>\n\n\n\n
\u2014 You are aiming to expand the scale of the business, then.<\/h3>\n\n\n\n
\u2014 Finally, Mr. Tamura, you have continued at BrainPad since joining as a new graduate. What is your personal vision for the future?<\/h3>\n\n\n\n
\n\n\n\n\u3010Post-Interview Note\u3011<\/h3>\n\n\n\n
![\"\"](\"https:\/\/mirai-works.co.jp\/consulnext\/wp-content\/uploads\/2025\/11\/img-tsukada.jpg\")
<\/figure>\n<\/div>\n\n\n\n
Masahito Tsukada<\/strong><\/p>\n<\/div>\n<\/div>\n\n\n\nBrainPad Inc. \u2014 Company Information<\/h2>\n\n\n\n
Tokyo Stock Exchange<\/strong><\/td> Prime Market (Securities Code: 3655)<\/td><\/tr> Representative Director & President CEO<\/strong><\/td> Tomohiro Sekiguchi<\/td><\/tr> Founded<\/strong><\/td> March 18, 2004<\/td><\/tr> Employees<\/strong><\/td> 545 (consolidated, as of June 30, 2024)<\/td><\/tr> Business Activities<\/strong><\/td> \u30fbBig data utilization services supporting corporate management improvement
\u30fbDigital marketing services<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\nBrainPad Inc. \u2014 Job Listings<\/h2>\n\n\n\n