Making Data Simple: Perspectives on data, a view into Japanese business culture and strategies with Keichii Okada

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Making Data Simple: Perspectives on data, a view into Japanese business culture and strategies


Technology trends and growth areas can vary in different parts of the world. In this week's podcast, Keichii Okada, vice president of IBM Tokyo Software & Systems Development Lab, discusses how natural language technology is helping to advance business strategy and healthcare in Japan. He also talks about innovative uses for Watson.


00.30 Connect with Al Martin on Twitter  and LinkedIn.

00.40 Connect with Keiichi Okada on LinkedIn.

01.25 Learn more about IBM Tape drives.

02.00 Learn more about what is next for IBM Augmented Intelligence.

02.00 Learn more about IBM Watson.

02.40 Connect with Madhu Kochar on Twitter and LinkedIn.

04.50 Learn more about Kaizen Management.

12.50 Learn more about IBM Watson Natural Language Understanding.

13.00 Learn more about IBM SQL.

14.25 Learn more about the Edge IoT analytics.

14.50 Learn about IoT at IBM.

16.30 See what JCM is all about here.

16.35 See what Hitachi is all about here.

Ready to dig deeper? Check out our previous podcast episodes of Making Data Simple.


Al Martin:                  Hi, you found your way to the Making Data Simple Podcast. I am Al Martin, your host. I am the VP of analytics development and client support at IBM. 

With me today, as my guest is Keichii Okada. He is the VP of Tokyo Software and Development Lab. He is halfway around the world, so we’re going to see if this works out here. So, Okada-san as I refer to him, welcome. How are you? 

Keiichi Okada:          Thank you, Al, for introducing me. I am Okada and I am leading the Tokyo Software and System Development Lab. We have about 700 working and developing software and hardware projects I think.  

Al Martin:                  Fantastic. I thought we would take some time today and chat about Japan, analytics, technology, big data and simply go wherever the discussion takes us. Does that sound cool? 

Keiichi Okada:          Yeah, that sounds cool.

Al Martin:                  So Okada-san, let me start here. Can you tell us a bit about yourself? 

Keiichi Okada:          I have been working on tape storage for many many years, and I am one of the founders and we are still doing business with the drive, so that is my long term background on products.  

Al Martin:                  That is your claim to fame, huh? Very good. So what are you up to now? I know you are responsible for the Tokyo Software and System Development Lab but can you talk to the audience about what that entails? 

Keiichi Okada:          It was very exciting to have this opportunity. It was about three years ago. I used to run the hardware lab in Japan, but now my responsibilities have been expanded to the software area where you can find AI, and also Watson IoT and also Watson Health.                                    

                                    Those are really the focus areas in my lab and many people are working on those cognitive areas which is very exciting in these days.  

Al Martin:                  Great. Do you have any more about what you’re doing right now, you have analytics or services? What are all the different services that make up your responsibilities?  

Keiichi Okada:          Yeah, I have a lot of responsibilities in my own station and a lot of esteem for analytics, which is the biggest part of my lab services. Almost half of my revenue is coming form the analytics services. This is the biggest part of the business.  

                                    In terms of development, my team has the full responsibility of delivering the Watson product under Madhu Kouchar, I think.

Al Martin:                  As I jump in here, first of all let me say happy new year. We have not talked since the new year. I was in Japan prior to the holidays of 2017. I guess you could say I was Making Data Simple for Japan and you guys treated me very very well.                                    

                                    At the time I was meeting with you, we brought up the need to preform a podcast. So this is me really coming back but unfortunately while I was there, there were way too many obligations and we could not have gotten it done. I come back to the States and we are doing this halfway around the world using technology. What I thought we would do is we would have a quick podcast today and I ask you a few questions about technology like I said and we will see where it goes.  

                                    Can you talk a little but about Japan business culture? 

Keiichi Okada:          Yeah, I think many of the Japanese clients including the big enterprise clients and also midsize companies have a lot of focus on the quality, of course, right? They have a very high expectation on a product quality and that is why I think this is kind of a difficult situation. Some problems happened.  

I was called by a customer and we got together and did the analysis in depth. This means that the customer always requires the root cause of analysis within a written document. Most importantly, they are really focused on the preventative action. Just fixing a problem is not enough there. They always think that that that kind of thing will never happen again, therefore that means some preventative action has to be put in place. 

Al Martin:                  So overall, how do you see the Japanese business environment? How does it compare? So, obviously you have lived in the US. How can you compare and contrast the difference between you know, the business practices in Japan versus the business practices in, for example, the US? 

Keiichi Okada:          I think they are very conservative. That means that if we change something, then some trouble may happen. That is why many of the Japanese clients, especially the system owners, keep the system unchanged. They are very conservative in upgrading the software or even the hardware. Therefore, if trouble doesn’t happen, we want to keep the system at the same level.

Al Martin:                  You know, one thing I studied when I was in college was the concept of Kaizen Management. For those listening, that just boils down to continuous improvement. One thing I wanted to ask you, I noticed that many Japanese companies remain giving the over release of products.                                   

                                    So my question would be, that seems like the antithesis or the opposite of Kaizen management and I know Japan innovates a ton, and I want to talk a little about that because it seems kind of contradictory in terms of some of the experiences that when I am in there in Japan. I see some of the older versions and their reluctance to upgrade, yet I also see the push towards greater innovation. Where does that balance reside?

Keiichi Okada:          That is a really good question, and we talked about this when you were here. Why am I seeing that conservativeness and yet a high expectation of quality? Like a cognitive area. We are very proactively and aggressively developed in application and the fact is that for example like Watson, I have been involved in a project with Watson for several years now and Japan is one of the biggest markets in Watson.  

Almost all big enterprise customers are showing us interest. We have a good conversation and a good deployment of the Watson solution for Japanese companies. In that area, I think they are very innovative. For example, we have a company here, like a Japanese version of Amazon, and they are very very proactively adopting the Watson cognitive type of technology and they created a COC.They are actually extending the solution around this AI and Watson all over the company. Different type of business area, but they apply Watson in many kinds of business areas.  

Al Martin:                  So what you are saying and that is very interesting to me is the fact that there is a lot of innovation but one of the innovations that is leading the way is Watson in cognitive technologies. Do you have any examples, case or proof points of how they are using the product? I am curious exactly how they are using Watson. 

Keiichi Okada:          I would say probably the most interesting application is matching. Matching can be used for many applications. One example is temporary staff, those with temporary staffing needs to do some kind of interviewing right with many clients. First, the interview happens with the company that really wants to hire that staff. Also, temporary staffing companies itself needs to do some interview and then we can have some matching. Manpower can be employed by some company, right?  

                                    That process is a very complicated process where they need to do multiple types and multiple numbers of interviewing of staff, but Watson helps. How their job matching is done is through cognitive technologies so their hit ratio or the job matching became easy with Watson technologies.  

Al Martin:                  If I look at Japan, taking a look at it at a micro level, where is the growth happening. What type of new technologies are clients talking about? What is catching all the excitement? I think GDP is about flat right now but what are you guys still the third largest economy in the world still? Where is all the enthusiasm in technologies.  

Keiichi Okada:          Again, the AI area is obviously the growth area in all of the Japanese marke,t not just IBM but all of Japan. There is a huge opportunity with this AI area. That is why I think IBM Japan puts a lot of focus on the AI area. As I said, we have a lot of use cases through these Amazon types of companies and insurance companies. Of course there are other big companies, every industry for the engineering analysis. Actually all the AI and cloud are a really strong area for the Japan market.  

Al Martin:                  So it seems like in Japan right now, if there is an application or configuration that is working they like to set that in so it doesn’t move but in some of the newer technologies and applications like AI, Watson and analytics, some of the new applications they are throwing out they are pushing, what we call pushing the envelope. This is that they are aggressively pushing new ideas to the market. Would that be accurate? 

Keiichi  Okada:          Yes I think that is a very accurate statement.  

Al Martin:                 We have a thing we are talking about right now in IBM Analytics where you really can’t have artificial or augmented intelligence without machine learning and you can’t have machine learning without analytics and you can’t analytics without information architecture. Are all four of those areas hot items in japan today? 

Keiichi Okada:          Yeah, I agree with that statement that is true. And for analytics from that point of view, like I said, Watson Explorer is fully developed by the team here in Japan and we are putting machine learning feature in Watson Explorer product and I keep hearing a lot interest from the clients. 

                                    We have a download and go version for the community already on the internet and there is a lot and a lot of interest in using that right machine learning feature in just Watson Explorer.  

Al Martin:                  You know, I think there are a lot of examples of augmented intelligence. You know, Japan was the inventor of Pepper the Robot. I think there was Softbank that did that. There are a lot of innovations through history whether it’s the bullet train or the Walkman or whatever, what other innovations do you see coming out of Japan in the next couple of years? 

Keiichi Okada:          Yeah, I think the one innovation that might happen in Japan is around the health care area because you know Japan is an aging country. Probably more than the United States or other European countries. It is already happening and that is why I said there is a huge opportunity for IBM to step in.  

                                    I think that together with IBM and Japan, we will encounter a lot of opportunity to create innovation and product.  

Al Martin:                  Yeah, you know, I think that is one area where the US and Japan have a lot in common because I see a lot of my time in health care and insurance. You know, preventing churn on the insurance side and machine learning technologies within health care to help create to preventative measures across whatever disease or other thing we are talking about.  

Keiichi Okada:          And also natural language processing is a key component of technology because we have a lot of documents written by doctors, right?  

Al Martin:                  So talk to me a little about that. That is very interesting to me. Within our database this year, we will be implementing natural language processing rather than using SQL. You can simply talk to the database, ask for the data back, and there you go. It essentially takes the place of SQL, and your case, this is very interesting because you are speaking a different language.  

                                    You have a lot of clients in Japan that specifically prefer, even if they can speak English, to speak Japanese and if they do so, how does natural language technology play out there? 

Keiichi Okada:          Yeah, one example is the insurance companies using the natural language processing very often. They are using this process in their key areas including machine learning. This is an example. This is probably life insurance, you know the doctor writes the clinical record and sometimes they write by handwriting. Now that hand writing needs to be digitized and after they have digitized the doctors handwriting with the record. After that, the insurance companies can determine how much money needs to be paid to the patient also. Depending on the name of the disease and the type of surgery.  

                                    So I think that process is a little complex, and if it's done by humans they would needs hundreds of people to do that kind of identification. I think in that kind of natural processing it is of course unstructured data the text analytics is really a great tool to identify the disease and to identify the surgery type and then finally they can determine the amount of the money to be paid to the patient.  

Al Martin:                  In my discussions with many of the clients when I was there, when we talked about data science there was a ton of interest, but it felt like it was very early on in the adoption of data science. In fact, a lot of the executives that I met with were interested in bringing on a data scientist, but they were very hard to find in this given time.  

Keiichi Okada:          Perhaps I will say that the number of the data scientists or the ratio of the data scientist is less than the other countries like the United States, so I think fewer people, but I think that also the demand is now going up. 

Al Martin:                  So note to self, if you are a data scientist now is the time to go to Japan and make a lot of money. 

Keiichi Okada:          Yeah, I think so, even in Japan we don’t have a lot of data scientists, so they are truly fully booked. 

Al Martin:                  Here is a quick question that I wanted to run by you. What are the one two or three things businesses must get right to succeed in Japan?                                   

                                    In the US, it is all about client experience. I think we are seeing an experience revolution right now kind of like a revolution. This is my theory that is going on right now. If it is not reliable, simple, consumable, then you are not going to be successful in the market or you are not going to be successful very long.  

                                    I think that is key and I think that is where the businesses are going and I think that is where you see the transition to cloud. That is where you are going to see transition to the edge, to IoT. In that regard, heck, if I look at my phone and something does not come back to me in a few seconds or not I am ready to throw it away. I am guilty as anyone these days in wanting instantaneous satisfaction. It all ties into that client experience. That is what I would say in the US and I think it is actually going worldwide, but I want to hear in terms of Japan to see if that is consistent. 

Keiichi Okada:          Yeah I think so, we talked about quality and I think quality is the one important thing for (unintelligible), right? To have, you know last year the systems business in Japan grew double digits if that mainframe or whatever. That is because of our quality.

                                    Quality is really the key to success in Japan.  

Al Martin:                  The order of things for me, and I don’t know if this applies to other countries, but it always starts with people, then it goes to the product and then clients. In other words, you have to have great people that produce great products that bring great clients and then there’s like an ecosystem that develops there after that.  

                                    You see it the same way or is Japan different in that perspective? 

Keiichi Okada:          No, I think this is exactly the same way here. I think the interaction with clients is really key for our success in Japan.  

Al Martin:                  Who are the big players in Japan right now? It is certainly IBM, and we will continue to be a major player, but who are the other major players that you want to run across when it comes to data, analytics, ML, AI? 

Keiichi  Okada:          JCM, Japan Computer Manufacturer…Hitachi..(Unintelligible) those companies are really domestic companies that really put focus on AI and IoT and cloud. They are clearly the competitors, but in addition to those domestic competitors, we have a battle with Microsoft in US that is also the same in Japan.  

Al Martin:                  Let me ask the question a little but differently. If you were to start up your own company in Japan, what do you think the best opportunities are if you were to say I am going to start up a company, where are the opportunities?  

Keiichi Okada:          Ah. That is a good question but if I have a good idea I would probably quit IBM and start up.  

Al Martin:                  Fair enough. 

Keiichi Okada:          I think, in general, the AI area is very popular and so many start ups I am seeing, and I don’t remember the names of the companies specifically, but every day I think newspapers are talking about AI and IoT.

Al Martin:                  Let’s finish up with Okada-san here a little to get to know you a little bit.  

                                    So in Japan what do you do for fun? You go golfing, you eat sushi. What else do you do for fun? 

Keiichi Okada:          I have been a badminton player for many years since I was in high school. I am still doing it once a week so that is exercise.

Al Martin:                  I also wanted to ask you, great leaders often have habits that make them successful. You are a vice president and that does not happen accidentally. Do you have any advice for listeners of how to drive success in everyday roles? Any cadence that you drive to help promote your achievements? 

Keiichi Okada:          Perhaps, empowering and delegation. That they are, that the people have ownership. Let them own their products and their subjects. If anything, bad happens then you can step in, but other than that, I like to empower and delegate the responsibilities to many leaders in my organization and that is how I work every day. If anything happens, then I step in and solve the problem together, and even as a team we solve the problem together.  

Al Martin:                  Yeah, that sounds consistent across cultures that autonomy mastery purpose. So, essentially, empowerment expertise and purpose seem to be consistent between our different cultures here.

Keiichi Okada:          Yes, that is consistent.  

Al Martin:                  Very good. Well, I appreciate you joining us today giving us your input and insight from Japan. It is not often that you get to listen to somebody halfway around the world and get that insight, so thank you for joining us. Unless you have something to say that you want to sign off with, I just want to say thanks again! 

Keiichi Okada:          Thank you for inviting me to this very interesting type of podcast. 

Al Martin:                  Thank you and Okada-san. I know I will talk to you next time and we will be solving business problems soon.