PODCAST | How to maximize your ROI with your Data Analytics?

We have seen a lot of evolution in analytics these past years using new modern technologies & solutions but also by collecting more and more data, but what about the methodology following this? What companies should do to bring value from their data? Bahram Assadollahzadeh, Data Management expert, is sharing key golden rules in our Business & Decision expert Podcast.

Why do analytics not always deliver qualitative benefits for companies? That’s a question we often hear from businesses as it is getting difficult to quantify analytics and do better with them.

How do you gain value with your Data Analytics?

Our Business & Decision Expert Podcast strives to answer business questions in the domain of Data & Digital for your company’s digital transformation. For this episode, our experts will highlight the main reasons why companies fail with their analytics.
What we will discuss in this podcast episode:

• Why do businesses struggle to get a return on investment from their analytics?
• How to get aligned between your business strategy & your data?
• How to get the data you need in the right and good format?
• What a business should consider for a successful analytics initiative to gain results?

Gerrit Denayer, Business & Decision Marketing Director, received around our table Bahram Assadollahzadeh, Business Analytics & Corporate Performance Management to answer those questions.

Listen to the full podcast:

Gerrit: Today how, in your view, has analytics changed over the different years? From my experience, you know, we were talking reporting on green screens right was CIC, S and RPG and S400,well, we were happy to get data out of some old database systems, whether or not relational systems. So we were far from the big data structures we are today. It was all on even hierarchical databases and network databases, you know, all these fun things index sequential databases was different. So now, on the analytical part, how did it evolve in your eyes over the years?

Bahram: I think in the last 25 years, it’s interesting to see, there has been a lot of evolution in analytics. We touched on the technological or tool side of the things that still a lot is done with Excel. But obviously, on the platform side to side, a lot has developed. I mean, there’s so many applications now, with which you can do analytics. And the technology behind it has also evolved very much. I mean, a lot of massive data can be, can be crunched and analyzed, with a lot of the applications that exist. And over the years, especially in the last 10 years, it has moved very much from a technological domain where only experts can do analytics, to a world where even business people without IT skills can do actually a lot of things. So it has became much more user friendly, much more business friendly. But that’s all on the application side. What I think hasn’t changed very much in the last 25 years, is more on the methodological side, that a lot of businesses, even if they implement analytics with more modern tools or even the most modern platforms, almost all of them struggle to generate return on investment on analytics.

Obviously, having analytics is better than not having that, but we ask businesses : “okay, now you’ve invested this much, what is the real outcome?” Oftentimes, you don’t get an answer at all. Or sometimes it’s just fuzzy answers that are qualitative. So I would say most businesses really struggle to create a tangible return on investment on the analytics that they do.

Gerrit: So yeah, I think the ROI part is something that challenge and that many companies are facing when they are talking about how do you calculate the ROI of an analytics project. Because typically, when you do an ROI calculation of any type of digital project, it’s typically very easy. It’s relatively easily you know, you have manual labor today that’s happening, you make an automated process you save on labor, so you can very easily calculate what the return is going to be. Certainly the direct return, as the indirect return is always harder. But on analytics, you typically talk on indirect returns, it’s very hard to know how do you measure how do you quantify or qualify, having not not having a report or having it later or having it in a different visual? You know, it’s very hard to see that. So why do you think that that in general, the business has struggled to do that return? And because there is a lot of, I think, a lot of examples already where the ROI is calculated afterwards, where you see the difference, the change before and after that. But before starting a project, it’s a lot of second guessing estimations, assumptions, which is very hard to quantify, to make them concrete before you start a project to see what the ROI is going to be.

Bahram: Yes that’s absolutely true. I think there are two sides to determine when you’re talking about return on investment, ROI, obviously, I mean, it would be very interesting to be able to show it quantitatively. But since a lot of businesses also struggle, just from a qualitative point of view, to say :”Okay, this is what the analytics initiatives and investments brought.” We looked back and looked at so many projects that we have done, the ones that were maybe more successful, the ones that were maybe more challenging for my return on investment perspective and try to find common reasons why ROI after the project wasn’t there, and common within within those projects over all these years.

We have identified seven reasons that were the most common? Why did they change? And I would say the first reason why we see is that there’s a lack of alignment between the strategy a business wants to wants to drive and the analytics that they do. And there are two or three components that why this alignment is, for example, missing. One is, what we observe a lot of times is that management, top management or the leadership of the company, isn’t really involved in analytics. Analytics is very often delegated down to the to the finance roles, for example, to the CFO, and is therefore in there, it’s delegated further down the hierarchy. So it’s automatically pitfall there, were alignment between really the business strategy, “what is going to make you successful over the years”, is not really mapped to what you do on the analytics. So there’s missing link to start with.(…)

Business & Decision Expert is a podcast where we talk about Data, AI & Digital topics. ​We receive every month Data & Digital experts to discuss how Data is revolutionizing our daily lives and we strive to answer business question related to digital transformation.​ We aim to gather a community of Data passionate people around our podcast where everyone can learn something in a relaxed and fun way.
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