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Analytics as a Mindset – An Interview with AAARL CEO Eric Huang 

Eric Huang, CEO AAARL

Eric Huang, the founder of Advanced Analytics and Research Lab, AAARL, a Toronto area data analytics services, solutions, and education company, doesn’t think of data analytics primarily as a technology. He believes it’s a mindset that everyone can benefit from, especially small and medium businesses. 

In part II of our interview, the AAARL’s CEO shares his thoughts on why data analytics accessibility is essential and what SMEs should consider when embarking on analytics. 

Q: You’ve made a career out of ensuring data analytics is affordable and accessible to nonprofits and SMEs. But what does making data analytics accessible to everyone mean to you, and why is it important?

Eric Huang: I don’t think of data analytics primarily as technology innovation, but more of a mindset. How do we get to the truth? How do we make decisions with the best data available? I believe if everyone can be more informed about whatever it is–whether it’s social issues when they vote or even managing their personal life– having a decision-making framework and better data is a good thing.

Probably my favourite book on statistics is called How to Lie With Statistics. It was written in the 50s, and some of the wording is old school. Each chapter talks about a simple way people can lie with statistics. And it’s true! The simplest definition in statistics is an average, but there are actually 10-20 different ways of calculating an average. So even with the most basic statistic, someone can very easily lie or tell the story with any stat they want. And people will believe the story once they see the statistic. And there are always statistics being thrown around. So, I encourage people to be skeptical and ask why certain numbers are used and what is the source for those statistics.

But there is an easy way around it. I believe we can improve things with a bit of education on statistics, analytics, and technology. We used to do workshops, and people could learn the basics in a few hours. Having that foundation changes the way people think and work.

At AAARL, we wrote this article where we talked about analytics and life. For example, we talked about wearing fitness trackers—having that health data available can help you even subconsciously improve your numbers. You want to hit your 10,000 steps, right? So you do things to achieve that. In my life, I take it a little further. I calculate how I eat or spend time during my day. The joke around AAARL in 2021 was I calculated that I only spent 7% of the time with my family and decided it was a little low, so I bumped it up. 

Q: Part of the way you educate people on data analytics is through outreach. You will participate at the CanadianSME Small Business Expo, June 29-30, 2022, to discuss how SMEs can more quickly adapt to the changing social and economic ecosystem today and in the future. What are the key challenges businesses have faced since the pandemic or in the new normal that analytics can address?

Eric Huang: First, the pandemic was hard, especially for small and medium enterprises. Businesses’ priority was ensuring they survived, which is about resilience and hard work. Analytics can assist businesses. But if the business is not there, it will not help. 

Through the pandemic, we’ve done a lot of analytics work with our clients, including helping them understand trajectory by looking at their data so they could make better decisions by saying, “Hey, our sales have gone down three months in a row. What do we need to do to make that change?” 

And going beyond this, the algorithms we had in place for clients before the pandemic could project out and alert them to the fact that things were going to be bad. This way, our clients could, for example, adjust marketing spending and pricing so they didn’t have inventory on the shelf. When we were coming out of the pandemic, and things looked positive, our clients could see this and ask questions such as, “How do we adjust pricing so that we actually have inventory on our shelves?” 

We have an inventory optimization system that uses historical optimization to predict things such as the number of units sold on a particular SKU and what amount of on-hand safety stock will be required on hand during this period. Much of this work is not rocket science, but it brings our clients improvement and sophistication with analytics.

Everyone knows you need products on hand, but rather than waiting until the end of the month and walking around and noting what products are low. We help clients to have a system in place that can tell them how much they have right now, next week, a month from now, and whether they need to order it in advance to meet their usual demands.

Q: Are there any common misconceptions about data analytics that SMEs might have you believe are essential to address?

Eric Huang: I think the biggest one is understanding what analytics is and isn’t. Analytics is a mindset. Everybody uses analytics because it’s basic problem-solving with data. People do that every day. A psychologist will say people make about 100 decisions from the moment they wake up to the moment they go to bed, and if you include the subconscious decision, that number is more like 400,000 or 500,000 because people wake up and think things like, “Do I eat breakfast?” Is that a conscious choice, or is that a subconscious choice? You make that choice based on the information you have. Are you hungry? So, analytics is simply problem-solving.

Everybody can benefit from data analytics, but it’s not a thing you buy or a person you hire. It’s a mindset and a culture. 

A business will say it wants an analytic strategy, but what does that mean? There is a spectrum of analytics. Everybody starts with no data, collects some data, and reports on it. Then, they automate the reporting, so they don’t have to spend all their time doing it. Then they venture into analytics, which is descriptive, predictive, optimization, and machine learning and AI. So there’s a whole spectrum of things you could do. 

Then there are verticals, various technologies, and dimensions. There are marketing analytics, finance analytics, and HR analytics. Every industry has different problems that they deal with. It can be complicated for the average person trying to get into data analytics to understand what it is.

This is a fundamental problem we have in the market. We have traditional industries that mostly know they need analytics but don’t know how to get into it. On the other hand, we have big tech companies with all the data centres, hiring all the smart people. And the joke is all the smartest people in the world are just trying to get you to click on an ad because all the tech companies paid for those people. And then, there’s a big gap in the middle, which is what AAARL is trying to fill. We are trying to bring analytics, skill sets, and knowledge to the traditional industries, nonprofits, and SMEs in an affordable way.

Q: What advice would you give a business that wants to be more data-driven but doesn’t know where to begin?

Eric Huang: You start by looking top-down at what are your big problems. Can you solve them with analytics, or is it other things? And a lot of times, analytics will solve the problems. Then you look bottom-up at all the data you have and figure out where the gaps are. What data do you need to get? 

You should have a high-level overview of your industry, where you want to go, your innovation objectives, and your growth objectives. Then, try to align that understanding with your analytics.

Ultimately, it is being more intelligent and more sophisticated about your data. Knowing versus not knowing makes a huge difference. 

Beyond that, I think you need to understand what the options are right? How do you obtain analytics? You can buy a system, hire your own team, or hire an outside person.

And I would say most traditional organizations have a customer relationship management (CRM) or point of sale (POS) system. They’re doing some reporting on those systems. I think about half the organizations today are going into automation, business intelligence, and reporting. The next step, I think, would be descriptive analytics. So actually being more sophisticated and understanding your own data. What’s been going on in the past month? What’s been going on the past year? How can we dig deeper to find out where we can improve and dive deeper into the data. Which customers are buying the most? Which customers buy the least? Which one was the most profitable?

I think many leaders know this is what they must do but don’t have time to do it. So how do you create the resources and automation so that the information is brought to the surface and you can see problems that cause diagnostics right away? 

Q: So a business doesn’t have to be a Fortune 100 company to do analytics, but how do you get that message across to an SME when analytics may be way down on the list of priorities? 

Eric Huang: First, I think they have to have the desire. If the owner doesn’t have the desire to innovate or continuously improve, then it would be hard to convince them of analytics because the mindset is not there. In some sense, analytics brings a new mindset, innovation, and new technology. The technology is only 25% of analytics, and the rest is having the mindset, culture, and process in place. 

Thank you to AAARL CEO Eric Huang for sharing his thoughts on data analytics and what SMEs should consider when embarking on analytics for their businesses. If you are looking to start your own analyitcs journey you can visit the AAARL website and book a consultation. 

Eric will participate in a panel discussion with small and medium-sized enterprises during the CanadianSME Small Business Expo 2022 in association with Caary Capital on Wednesday, June 29th, at 3:00 pm. For more information about the free event, visit the event website

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