In this podcast, Dr. Beverly Wright, Vice President of Data Science & AI at Wavicle Data Solutions, dives into an enlightening discussion with Huzaifa Syed, Senior Manager of Data Science at The Home Depot, focusing on the topic “Applying AI Technologies for Business Operations.” From enhancing customer experiences to improving return on investment, they reveal how AI, powered by quality data, can transform business results. Tune in to discover the critical role of AI within operations and the vast opportunities it presents.
Speaker details:
Watch the full podcast here or keep scrolling to read a transcript of the discussion between Beverly and Huzaifa:
Beverly: Hello, I’m Dr. Beverly Wright, and welcome to TAG Data Talk. With us today, we have Huzaifa Syed who is Senior Manager of Data Science at The Home Depot. Welcome, Huzaifa.
Huzaifa: Thank you for inviting me. I’m excited to talk to you.
Beverly: We’re talking about applying AI technologies for business operations, which is an enormous topic right now that a lot of people are thinking about. So, before we dig into how to apply AI technology for business operations, tell us, why are you so cool?
Huzaifa: I don’t know if I’m cool, but I like doing data science. I would like to think that I’m cool because of the work that I do. Apart from work, I’m interested in various activities which might make me think I’m cool. I think people will call me boring, to be honest.
Beverly: No, you’re a data scientist. We’re all cool. So, when we talk about applying these AI technologies for business operations, what kind of business operations are we thinking about? Are there certain business operations where we can look at it and go, “Oh, I can definitely use some AI there” and then other types of things that we look at, and we’re like, “No, it’s not going to work right now.”
Huzaifa: Yeah, I think AI technologies or data science can be applied in all business operations. We have definitely reached a level of data collection and data usage in these different fields, and it’s applicable everywhere. However, of course, there are a few areas which can benefit more in the short term or are benefiting more right now compared to others.
But it can be applied everywhere. To list a few, we are seeing how data has really changed the way customers experience shopping, shopping for products, and whatnot. Similarly, marketing is another area where data science or AI has played a big role in shaping how companies are thinking about their marketing strategies. The company I work for, The Home Depot, has data science or AI integrated into almost all its operations.
Beverly: Pretty much everything. Let’s think about a couple of examples. When I go into The Home Depot – I don’t shop in the other place with the L word, I only go to The Home Depot – and I’m looking around, and there’s this little kiosk computer. I walk up to that, and it’s helping me find a two-handle faucet by Moen in this finish, and there’s a camera watching me. Tell me about that. Is that an example of the use of AI? How can that help? As an example.
Huzaifa: Yeah, that can potentially help The Home Depot, or the company, to understand what customers are interested in and can suggest to them what are the next things that they need to buy in order to complete their projects.
Beverly: It’s a game-changer with customer experience.
Huzaifa: 100%. It’s a game-changer. Because a lot of times, in a company like Home Depot, our focus is on helping customers do projects by themselves and create value for their homes. And when they are doing that, a lot of the customers are not educated on how to actually execute a DIY project by themselves.
Beverly: Yes, I am one of them.
Huzaifa: So, Home Depot, and AI, and data science can really help. Home Depot understands, first of all, what customers need help with and then provides suggestions to the customers to get them to complete their projects.
Beverly: Let’s poke at this idea a little bit. Somebody might say, “Yeah, but what about something that’s highly human?” Think about a function, a business operation, that is highly human. And the first one I think of is conducting an interview with a potential candidate. How can AI be used for something like that?
Because we’re saying it can go everywhere. There are very few things, if any, that are not able to be improved in some way by AI. What’s an example you can think of or some commentary around something as personal and human-centered as a job interview?
Huzaifa: That’s a good question. The way I look at it is that when you’re conducting an interview, there are a lot of variables that you’re trying to identify in a candidate. Some of them are very hard facts about the candidate, like how they are good at coding or their functional knowledge about data science and whatnot. But there are other factors that also play a role in an interview; for example, can I work with this person? If I’m comfortable working with this person, if I have a rapport with this person, is this guy going to be a good cultural fit for the team? And those are the things AI might not be able to help us with in the short term. But what can happen is there can be a hybrid type of solution where AI can automate certain tasks of an interview, and then you can have humans fill in the gaps. That can make your interview process shorter. So right now, when you’re interviewing candidates, it takes months for people, and that’s not a good experience for the candidates themselves and for the company. But AI can play a role there and shorten that list.
Beverly: Okay. So, we’re saying most business operations, at some point, can get improved in some way by AI. As a couple of examples, customer experience is an immediate opportunity because it can be a game-changer to see a customer in a very personalized way. And then for other things like interviewing candidates that are fairly highly human, AI can help with certain pieces of it that will help expedite and move it faster, but maybe not do all of it. Is that accurate?
Huzaifa: Yes, 100%. That’s how I look at it. Again, when you think about customer experience, the sky is the limit. To give an example, if I needed to buy shoes, I used to go to a shop and look at different shoes and try those different shoes on. I knew what I wanted in the end, but I was still not sure what shoes would actually fit me and suit me well. Now, I see a future where you’ll have an email dropping by in your inbox which will have the exact shoe you want or will have the selection of three or four shoes that you want. And that is a game-changer because it’s saving so much time. It’s saving a trip to the store as well. So, things like that are going to revolutionize how we as humans interact with products and services as well as companies.
Beverly: Some people even say it could get to the mind-reading level, not just sentiment but actual mind-reading. And not just give you an email with the shoes, but they’re actually at your front door. The possibilities are far-reaching, but it’s not that far away. It seems like a lot of this is already starting to happen.
But if you think about the purpose, why would we want to leverage more AI to improve business operations? In what ways are we improving? If I’m hearing you right, it sounds like this is reducing expenses, becoming more efficient, and serving customers better. Is there a component of improving revenue?
Huzaifa: Yes, there are definitely those business KPIs as well, which can help you grow your business more. There are customer experiences and ease of operations, all of those things. But then there are also those hard facts of the financial numbers that can also be helped improve with AI.
For example, let’s say your company has 10 million customers. And you’re emailing those 10 million customers every week or every day about what products they want. Each of those emails will cost you some type of expenditure. But if you use data science or AI, you might not have to talk to all those 10 million people. Maybe the customers don’t have that need for your products at this point of time. So, you can talk to only a certain number of customers. If you do that, you’re reducing the cost of operations, and then you’re also improving the customer experience because your email is not being considered spam. And that’s another problem.
Beverly: Right. If you over-message, then they start moving you into different folders.
Huzaifa: Exactly. That’s something happening. HubSpot did this survey, and it’s available online. They found that the reason why people unsubscribe from certain emails is because more than 50% have said that they received too many emails. So that’s a problem. That’s one example where it’s improving customer experiences as well as the bottom line of the company.
Beverly: Yeah, that makes sense. Somebody listening right now might say, “Well, my company’s not doing any of that.” Why not? Why are more companies not doing this? The Home Depot is doing some really cool stuff. Most of the people I know at The Home Depot talk about how cool you all are. But there are plenty of companies out there that are just trying to figure out where their data is, and to get it clean, organized, and centralized. They’re not really leveraging it in another way like this and certainly not using AI on it. So, why are more companies not leveraging AI to improve their business operations? What’s the barrier?
Huzaifa: That’s another good question. And I think about that a lot: why this might be happening. Let’s say I’m running a camera company. My goal is to sell as many cameras as possible and to make better cameras. The leadership of the company is very focused on those two goals. And they might not be paying attention to the way they are doing data collection, data curation, data governance, and all these things. So, it might be a secondary priority for the company’s leadership, and again, that might be because their goals are different.
If the leadership starts paying attention to collecting the data, curating the data, governing the data, and making sure that their customers are comfortable with how they’re using the data, then those are the companies I see that are going to make a dent in the future.
Beverly: So that’s the key. If you have good data, those are going to be the companies that succeed. It’s not about anything else; you’re saying that if they have great data, they have more opportunities for leveraging AI. Isn’t it funny that we’re having this conversation in 2024, and we’re still talking about data?
Huzaifa: That’s really the key. If you really want to apply data, then you need to have good-quality data. Without you paying attention to the data, you’re not going to get the results. So, a lot of companies might say, “Oh, there’s a big buzz coming around, so let’s try and apply this technology.” But then it does not produce the same results to them.
The reason why it’s not producing the same results is because they have not really paid attention to this behind-the-scenes process of data collection. And then it doesn’t yield well, these AI projects fail, and it’s blamed on the AI. So, you have to think about the long term. And I think CEOs need to think about data curation a lot more than they do right now.
Beverly: But if you keep digging back upstream and find the root of the issue, a lot of times, it’s data. If you keep digging and go back upstream, if you’re looking for success, often, it’s the data. That’s very interesting.
So, to finish us off, if people are listening, thinking “Gosh, I just want to do something with AI to improve business operations.” What final piece of advice would you give to somebody who’s trying to leverage AI for business operations?
Huzaifa: So, the first mistake I see companies doing is that they see a fancy new technology come up, and they want to directly apply that to solve something. But that’s not the right way to go about it, in my opinion. The right way to think about these technologies is to first look at your business operations, where they are, what they are getting out of it, and how they can take that from point A to point B. Then, decide what technologies can get them to point B. So, you need to start by thinking about the business. Again, I can talk about so many examples where you can use the current technologies that are available to take your operations to the next level. You just have to decide. But decide based on which will give you the easiest return on investment to get you started on the journey.
Beverly: I love it; very good advice. Thank you again to Huzaifa Syed from The Home Depot for talking to us about applying AI technologies for business operations.
Huzaifa: Thank you so much for inviting me, Beverly. It was a pleasure.
Beverly and Huzaifa’s engaging discussion sheds light on AI’s transformative role in business operations. Their insights underscore the importance of leveraging high-quality data to drive innovation, streamline operations, and enrich customer interactions in the digital era, spotlighting the boundless opportunities that AI introduces. Explore the full catalog of TAG Data Talk conversations here: TAG Data Talk with Dr. Beverly Wright – TAG Online