To Prevent Big Data from Becoming a Treasure Left to Rot. What Are the Secrets to Successful DWH (Data Warehouse) Utilization? (Part 1)
In addition to the rapid evolution of technology in recent years, the spread of the novel coronavirus has prompted many companies to abruptly shift their focus toward business digitalization. However, while many companies have recognized this trend and announced initiatives like "promoting DX" and "utilizing big data," many are likely grappling with concerns such as "What exactly should we do?" and "We don't know how to utilize the data."
To gain insights on resolving these challenges, we interviewed Shinichi Yutaka of Dentsu Digital Inc., who provides proposals for solving management issues using big data and consults on AI implementation for various companies. We also discussed DWH (Data Warehouse), a key element in corporate data utilization.
Defining your goal is crucial: What do you want to achieve with the data?
Q. I understand your work primarily involves promoting corporate DX using the latest technologies and consulting on data utilization. What kinds of inquiries do you receive most frequently from clients?
Yuki: The most common request right now is: "We've implemented a system like a DWH, but how should we use the vast amount of data collected there?" The next most frequent is: "Our data is scattered all over the company, and we want to consolidate it into a DWH, so we need help with the implementation."
Q. A DWH is a database that consolidates and stores the massive amounts of data accumulated daily through business operations in a time-series format, correct? So, many companies collect data but aren't fully utilizing it?
Beneficial: Exactly. Many companies implemented DWHs thinking, "If we collect data and it becomes big data, we'll surely learn something." However, many have ended up not knowing what to do with it. Essentially, they didn't fully consider the desired output during the implementation phase.
Q. So, it's crucial to clearly define what data to acquire and how to utilize it right when deciding to implement a DWH, isn't it?
Beneficial: Exactly. So when clients consult us, we first say, "Let's define the goal and then work backwards from there." Then we clarify how much of that goal is currently achievable or unachievable. We start by establishing concrete target metrics and actionable guidelines.
Next, we analyze the client's current situation against our accumulated insights and data. This reveals gaps. Then we proceed through a process of proposing solutions like, "Let's implement this tool" or "Let's collect this data," or suggesting, "We can solve this issue by introducing an existing solution."
Q. Which scenario is more common: introducing something new, or leveraging existing resources?
Beneficial: Initially, leveraging existing assets for improvement is more common. We discuss what can be achieved using current data before tackling immediate challenges. Subsequently, we propose introducing new systems to gather additional actionable data.
We also follow up with users to promote data utilization
Q. What about companies considering DWH implementation? What kinds of inquiries do you typically receive?
Beneficial: We often see cases where companies start considering DWH implementation because their mid-term management plans include goals like "promoting DX" or "leveraging big data." For example, we might get inquiries from someone like the head of a company's digital marketing department saying, "Our mid-term plan has this directive, and executives are pushing us to get started with data utilization. But our internal data is scattered everywhere and not in a usable state right now."
Q. What kind of proposals do you make in such cases?
Beneficial: First, as mentioned earlier, we start by "defining the goal and working backwards." Then, since there are various types of systems for collecting and analyzing data, we propose the best fit for that company. We offer a comprehensive proposal covering everything from system construction to actually connecting the scattered data and consolidating it into one central location.
Q. For example, if introducing a sales support system, the IT department decides on implementation, but the sales department employees will actually use it. In such cases, do you also provide support for the sales department users?
Yuteki: Yes, we often provide support that includes that aspect. If AI is utilized, we clearly demonstrate why the AI is making certain recommendations and the specific probability of sales increase if those recommendations are implemented.
Q. Listening to you, it sounds like your work is closer to business consulting using tools like DWH than just proposing and building systems, right?
Beneficial: Yes. It feels like we're working on projects that stem from data-related aspects and lead to business improvement and profit enhancement for companies.
We don't just say, "Let's implement a DWH." We focus on solving problems.
Q. In terms of industry, which sectors are the most common for consultations?
Yutoku: For me personally, I'm currently handling many projects for pharmaceutical companies. Before that, it was automotive manufacturers, home appliance makers, and so on. That said, I don't think the industries are overly skewed. Also, while inquiries are currently mostly from large corporations, I believe more small and medium-sized enterprises will start adopting these solutions going forward.
Q. I see. So, are big data-related inquiries increasing year by year?
Beneficial: If the first wave involved clients wanting to implement a DWH for their business, the current phase feels like a second wave. We're now seeing more inquiries about how to effectively utilize it, how to enhance its performance, and how to integrate it with marketing systems.
It's like figuring out how to extract data that's sitting dormant like oil, and then how to refine it into gasoline. Wouldn't it be meaningful to tackle that together with the client?
While more companies want to start using data, the key isn't just implementing a system. It's about defining clear goals and planning backwards to achieve them. In the upcoming second part, Mr. Yuteki will share specific client case studies to explore the benefits of DWH-driven data utilization in greater detail.
The information published at this time is as follows.
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Author
Beneficial Shinichi
Dentsu Digital Inc.
After working in M&A due diligence, strategic planning centered on data marketing, business development, and marketing consulting, he assumed his current position. His strength lies in holistically leveraging cutting-edge marketing technologies—including AI (machine learning), MA, CRM, DMP, and BI—to resolve management and business challenges. He also excels at discovering and forming alliances with the latest digital tools globally, and has delivered numerous presentations and authored many articles on digital marketing.
