How would you define analytics and why is it important?
Analytics is a big word that gets thrown around a lot. But what does it mean for businesses? In this episode of Qcast, we’ll discuss what analytics is and its importance in business.
Sahil Brij Malhotra: Hi, I’m Sahil Brij Malhotra, director of business development at Qualetics Data Machines. Welcome to Qcast! Where we bring in our leaders, experts, and guests to talk about AI challenges and opportunities. Today we are going to interact with Mike Fowler, chief commercial officer at Qualetics. We’re going to talk to him about Analytics and its importance.
Welcome, Mike. So Mike, how would you define analytics and why is it so important?
Mike Fowler: Good question, I think it’s probably helpful to just realize that the practice of analytics is something that good managers have been doing in business for years. Good managers have always looked at the processes and practices they’ve done, studied the outcomes, and then tried to understand how they could change their processes and practices to improve those outcomes.
We define that with the word analytics and when we break down analytics it tends to break down into different forms. I’ll start with descriptive analytics. So descriptive analytics is how we measure what has occurred. So if I use a grocery retail example here, if in my grocery store I want to see how my milk products are going, I can look at descriptive analytics and see that my milk sales have been relatively flat, so then we might take the next step of diagnostic analytics.
Diagnostic analytics looks at the past to understand what variables to find the why that occurred, so descriptive is telling us what has occurred. If I were to do some diagnostic analytics of my past milk sales might see that the whole milk products have been selling less and the low-fat milk products have been selling more, offsetting the reduced whole milk sales. Okay so that gives me a little insight as to what has been happening in the past, now if we then go to the next step which is predictive analytics, this helps define if this path that we’ve been on continues what does the future look like, what can I expect from future outcomes. And if I were to look at my predictive analytics it might tell me that what has been flat, maybe may continue to be flat and may even decline.
So then you take the next step which would be prescriptive analytics and in prescriptive analytics, it analyzes more of the why in diagnostic analytics to analyze that if we can look at those variables and make some changes, how can we improve the trajectory I’m on. So if our prescriptive analytics studied our past milk sales it might see those whole milk products are on a trend to decline in sales low-fat milk products may also just stay flat or even decline, but we may have this oat milk product that in the last year or two has really been increasing in sales so our prescriptive analytics may cause us to look to non-dairy milk products as our growth opportunity in our milk sales business. So that’s the range of analytics and how it can be applied.
Because without analytics really you’re exposing your business to risk you’re sort of operating with accepting a little bit of what fate may have to offer for you versus with analytics it’s all about going beyond guesswork and using facts and data to inform your decision making.
Sahil Brij Malhotra:
Thank you, Mike, for providing such a real-world framework for analytics; descriptive analytics, diagnostic analytics, predictive analytics, and prescriptive analytics.
Thank you Mike for your insightful thoughts on the impact of AI on business growth. We just heard from Mike Fowler, chief commercial officer at Qualetics Data Machines and we will be back with more thoughts from Mike and our other team members soon.