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12 John Ang on Digital Transformation with Companies

· AI,podcast


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Podcast with John Ang Part 1


Speaker: John Ang, Andrew Liew


John Ang shared his backstory of how he got into AISG. He shared with the audience to see the challenges of digital transformation as opportunities to free up time on mundane repetitive tasks. He shared a story in which a company was able to achieve 12 to 13 times more productivity and free up so much time using digital transformation on a human resource management system.

[00:00:00] Andrew Liew: Hi, everyone. Welcome to the AI of mankind show where I share anything interesting about mankind. I'm your host for this season. My name is Andrew Liew. I work across four Continents and 12 international cities. Also, I work in tech startups across a range of roles from selling products, making customers happy, figuring out fundraising, making finance tick, building teams, and developing sticky products. Apart from building startups. I've also worked in fortune 500 companies as a chief data scientist or technologist and people leader. You can call me Jack of all trades or master of learning. I hope to make this podcast show a great learning experience for us In each season, there is a series of interesting things where I invite guests to share their views about their life and interests. Now let the show begin.

[00:01:26] Andrew Liew: Hi, everyone. Welcome to the show. My name is Andrew. I'm your host for today. My guest John Ang is the product manager at AISG. which stands for artificial intelligence, Singapore, where he works on various products. One of the products that he worked on is TagUI.In addition to his work on TagUI, he's the face of AI, Singapore for everyone's program, and is one of the main architects for the AI for the industry program. John has also instructed for the data and analytics program at the NUS business school and the NUS school of continuing and lifelong education, scale.

[00:02:06] Andrew Liew: John has a background in finance as well as in the startup industry. Over his professional career, John has planned and executed multiple data-driven projects across finance. Healthcare and education prior to his row as a product manager, John was an AI engineer and principal consultant in AI, Singapore, where he worked across industry verticals to scope AI projects for the 100 experiment program. Before joining AI, Singapore, he was also responsible for leading and setting up the business development team, and the analytics team at a biotech startup. And before that, he worked in the merger and acquisition and leverage finance team at Barclays Capital on New York wall street. He has a bachelor of science degree in finance from the New York university stern school of business. So everybody let's welcome. John

[00:03:06] Andrew Liew: thank you, John, for coming to this show.

[00:03:12] Andrew Liew: So as we mentioned, the audience wants to hear about anything to do with artificial intelligence, digital transformation, and you yourself. So why don't we start with the first question? Tell me more about how you get from your bachelor days to where you are.

[00:03:28] John Ang: Hi Andrew thank you for hosting me for this show. My experience has been pretty diverse.

[00:03:34] John Ang: I've gone from being in finance to doing a biotech startup, and now I'm doing high technology with AI. So then we just connect the dots for you. So my background in what I studied in school was finance. And I joined a large investment bank after I graduated doing well in mergers and acquisitions.

[00:03:52] John Ang: What I realized after doing it for some time was that. I wasn't just interested in the [00:04:00] finance side of things. I was also very interested in the operational aspects of a company basically what they were doing on a day-to-day basis, and how their operations were run. Real impacts they were having in the market.

[00:04:12] John Ang: So that was something that I was very interested in. And when an opportunity came up to go back to Singapore and join your friend to launch a biotech startup that was looking to convert food waste in Singapore into high-quality, high-tech organic fertilizers for sale to farms in Southeast Asia.

[00:04:33] John Ang: I jumped at the chance and over two years, I grew the company from just being in Singapore to Indonesia, Malaysia. and Taiwan. Most of the countries in Southeast Asia. And what was really interesting was that after being on the farms, working with farmers for some time, I realized that they were collecting data, that they were not using.

[00:04:55] John Ang: And I became interested because that then big data and [00:05:00] AI were coming up as buzzwords. I became interested in figuring out, could I use this data to predict ahead of time. They're going to be problems if a farmer's crop and if there are going to be problems. How should we deploy our products and our fertilizers to reduce the impact of those problems?

[00:05:18] John Ang: And to my surprise, the data analytics actually work. And I wanted to integrate this high-tech piece into the product suite that we had. I'll start off by my co-founders were not so tech savvy as myself. They just wanted to sell the physical product. But I couldn't get the idea out of my head.

[00:05:38] John Ang: It was really eyeopening over whenever I say the data could be a review so much in terms of insights. So I kept a look out for opportunities to continue implementing AI and using data. And eventually, I found this organization, AI, Singapore, they had been tasked by the Singapore government to roll out AI to the entire Singapore economy, whether it's [00:06:00] organizations or whether it's individuals.

[00:06:02] John Ang: And it was a hard decision because the startup was doing quite well. But eventually, I started to leave and joined this particular team and I've been with this team and I sing a ball for the last two to three years. We have done multiple initiatives and frameworks to help, not just the startup go to the medium and large enterprises in Singapore, learn and adopt various AI algorithms, in their products as well.

[00:06:26] John Ang: their processes. And they'll come up with various initiatives on how we are able to actually make the process of adopting AI smoother, easier, and cheaper as you go along. So that's been the I've been doing for the past couple of years and we have actually had some. Very interesting successes and also insights.

[00:06:47] John Ang: And we have after having done it for this amount of time.

[00:06:50] Andrew Liew: Cool. you mentioned you were doing a finance degree working on wall street, and then eventually stumbled yourself to that biotech startup. There are some [00:07:00] data that can be mining could actually help farmers.

[00:07:03] Andrew Liew: And then your passion actually left you to figure out where to pick up the skills to basically get started in using AI. And so the interesting question that I wanted to ask you in the course of your role and AISG, as you work along with companies, big or small what are the challenges that all these companies face when they do digital transformation?

[00:07:31] John Ang: I think that one of the biggest opportunities, actually, when you look at challenges, I look at it as opportunities are actually in the automation of administrative tasks that a lot of the companies have. Many functions, videos talk about finance, accounting, sales, and marketing, even HR. Alot of these functions have a built-in amount of administrative work.

[00:07:57] John Ang: And if you can free your staff up [00:08:00] from having to do these repetitive job tasks, your staff is actually able to shift that focus and do a much higher value work and increase their productivity. Let me give you an example. One of the SMEs that we were working with had bought an HR management system, because one of the functions for calculating over time, the way that they were doing it on the ground was not supported by this HR management system.

[00:08:28] John Ang: What actually happened was that they had to get one HR headcount to dedicate two entire weeks, each month to process the overtime claims of the staff that they had. They had about 4 to 500 stuff.

[00:08:41] Andrew Liew: Wow! I'm just curious, like what, why do they need to put two headcounts to compute these seemingly simple tasks, which is computing overtime pay, and if they don't do it well, what happened to them?

[00:08:54] John Ang: It's not the computation of overtime pay that was the problem. The problem [00:09:00] was that once that overtime pay was computed, it had to be uploaded manually into the HR management system on an employee-by-employee basis. So you can imagine you have to go into the system, open the employee's account, navigate to their overtime section and fill in that data manually of 500 employees and each one of those employee workflow nukes will take something between 10 to 15 minutes. That was a huge time suck because in order to interact with the HR management system, they had to do this manually, and that was suck up a lot of time.

[00:09:37] Andrew Liew: Wow. So like you mentioned if 10 minutes and you have about 500 staff and looking at 5,000 minutes that's if you divide by 60 that's about 10-20 hours they could have spread it over 2 weeks. So is it because every time they receive this overtime computation, it was a time crunch? They need to finish up the computation or the loading and loading within a quick, short span of time to submit CPF or this payment thing.

[00:10:02] John Ang: They have to pay themselves every one month. In fact, right now they were trying to consider how they were able to be more competitive in, how they are going to pay their staff once every two weeks, but functions such as this, there was bottleneck by the manual process make them unable to do

[00:10:18] Andrew Liew: wow. So before that, how much time they actually went to. After with your help and your team to automate the stuff, what was the effect like?

[00:10:26] John Ang: So the whole process spread out, would take about 2 men made weeks across one month. So they will probably do it for three, four hours every single day, dedicating one HR staff entire daily output to just this task. And after we came in managed to completely automate the process. So as the HR person had to do was to press the start button and everything else would be taken care of by a computer. She would go on to do other work on her own computer and the entire process of, getting that data from the raw Excel sheets into the HR management system was reduced to 1 day.

[00:11:07] Andrew Liew: Wow. So are talking about two men weeks, about three hours a day to one man day. It's almost like 12 to 13 times of productivity. And that frees up a lot of time, and this is done over month on month. So imagine those cumulative months, when you guys went back to them, what was their response like? What did they do with those time?

[00:11:31] John Ang: They had so many things that they were not able to do because they had to work on this low-level admin work. So other things that they were able to do was to move over to that two-week payment cycle and also roll out a lot of other process improvements that they were not able able to make space . So it was very interesting actually freeing up this bottleneck that allowed them to optimize the rest of their workflows in an even better manner.

[00:11:57] Andrew Liew: Hi everyone, thanks for tuning into this episode. We have come to the end of part 1 with John. In the next episode, we will continue with John on part 2 which he shared with us a use case on how to start the process of digitally transforming the Human Resource division of a company. John will also share tips on how to overcome resistance for digital transformation. Lastly, John shared about the response he would have taken for a successful implementation of a specific phase of digital transformation.

[00:12:23] Andrew Liew: If this is the first time you are tuning in. Remember to subscribe to this show. If you have subscribed to this show and love this. episode Please share it with your friends, family, and acquaintances. See you later and see you soon.