Maritime & Mercantile Sees Increased Accuracy and Responsiveness

Evan Powell, CIO
Maritime & Mercantile

Maritime & Mercantile (MMI), headquartered in Dubai, UAE, imports, distributes and resells alcoholic beverages worldwide.

The kind of analysis that we do in Tableau currently, we were not able to do before – mainly because it took a lot of effort and the data became outdated before we actually got to use it.

For almost a century, Maritime & Mercantile has imported, distributed, and resold alcoholic beverages worldwide. In this video, Chief Information Officer Evan Powell explained how using Tableau for every aspect of the business has significantly improved the Dubai-based company’s accuracy and responsiveness. “We started with 5 users, and the demand was simply overwhelming. I never expected it to extend as fast as it did and get as big as it did.”

Tableau: How do you use Tableau at Maritime & Mercantile?
Evan: We use it for all our notices, reporting, decision-making, management support, and business intelligence. We look at every aspect of the business: sales, marketing, logistics, and financial.
Tableau: Where does your data live?
Evan: Mainly in a data warehouse, although we use Tableau extracts and other sources for the non-ERP data.
Tableau: So you’re connecting live to a data warehouse sometimes and using a data engine at other times?
Evan: Yes, and blending them.
Tableau: Tell me a bit more about how that works.
Evan: One example is in the retail environment, in our retail channel, blending sales by the hour. The ERP system doesn’t know how many people come into the outlet, but you want to relate sales to how many people actually come in. So you blend the two.
Tableau: So how did you do that before Tableau?
Evan: We didn’t. Or, we put it together in an Excel spreadsheet, which is very manually intensive. You can’t make decisions quickly. The data’s changing every day, every hour, and by the time you put the spreadsheet together the data has changed considerably. So, you’ve got to have time with your data, and it’s got to be done with less manual intervention.
Tableau: How has your process changed now that you have Tableau?
Evan: The analysis is less manually intensive and more accurate. Spreadsheets by their nature are not accurate. Those are the major things that have changed. The kind of analysis that we do in Tableau currently, we were not able to do before – mainly because it took a lot of effort and the data became outdated before we actually got to use it.

For example, we’re doing blends where we’re doing budgeting outside of the system. We look at what happened last year, we look at forecasting, and we look at what we’re budgeting in order to validate how we’re forecasting. These come from completely different data sources. We put them all together, and we’re able to make very quick and sensible decisions.

The other analysis that we do with varying data is that we relate sales to inventory to procurement, in order to look at, for example, potential out-of-stocks. We are able to look ahead by analyzing where we are now and react before we have a problem.

Tableau: How big is the data you’re working with?
Evan: It’s not necessarily huge, but it’s very complex. We’re looking at millions and maybe 10 million rows of data, but we’re viewing that data from very different views. The supplier views the data one way. Our internal sales team views the data in a completely different way. Our customers view the data in a completely different way. So our complexity is not in the volume of the data; it’s in how we view it.
Tableau: How many people do you have using Tableau?
Evan: We have roughly 100 users, of which half are using Tableau Desktop. So we have quite a large section actively creating analysis, as opposed to consuming it. It’s 50/50.
Tableau: How did you grow to have so many users?
Evan: Our users reacted very well to self-service. We started with 5 users, and the demand was simply overwhelming. I never expected it to extend as fast as it did and get as big as it did. I never thought we’d have 50 active people analyzing data.
Tableau: And who are the consumers?
Evan: It covers a wide spectrum. We have management. We have our customers, who are hotels and restaurants. Our analysis is very important to them. We also have principals we have to present to. We have contracts that are interested in performance vs. contract.
Tableau: How has Tableau changed the way you communicate with these various audiences?
Evan: We are able to publish data without people having access to the tool. So, for example, all our management reports contain visualizations and all our reports to our principles contain visualizations, which we could not do before.

Also, when we do presentations in our offices – which we do a lot of – we use interactive data. When we communicate with principals, for example, this is significant because it focuses them on the raw materials. They also have fewer questions, which is always a good thing.

Tableau: So your consumers have responded well to Tableau?
Evan: Exceptionally well, which poses quite a challenge. They are demanding more and more information from us. And we have the challenge of being able to publish that to external people behind our firewall.

Of course, this kind of analysis does strengthen us quite significantly in that we present a very professional and well-organized image to our customers, as well as to our suppliers. It gives us the opportunity to use another tool to convince them to become bigger customers, or in our contract negotiation with suppliers. It strengthens all the areas.

Tableau: How would you summarize the benefits Tableau has delivered for Maritime & Mercantile?
Evan: Quicker decision-making. More relevant and accurate information. And a changing culture. For example, instead of thinking in rows and columns of numbers, we think in terms of relations and proportions.
Tableau: If you were talking to another company, what best practices would you recommend for rolling out Tableau?
Evan: The first thing is to get your data right. Not all your data, but the data you want to analyze first. There’s nothing worse than sitting in a management meeting and your financial manager saying, “That graphic image is incorrect.” You’re going to kill your Tableau implementation completely.

The second thing is that Tableau is very approachable and it’s very quick to do visualizations, but training is critical. To have at least one Tableau expert trained and certified is a very valuable tool. You’re able to mentor and influence people far more quickly.

The third thing I would say is that if you’re an IT professional, like I am, you’re going to need to think completely differently. Instead of thinking platforms and standards and security, you have to think conversation, data, and communication. Tableau is not just a business intelligence tool. It’s a lot more. As an IT professional, you’ve got to change how you see things.

When I say you have to think differently, you have to think from a user’s perspective first. In other words, don’t think data volumes, performance, standards, security, and all the usual stuff that an IT person thinks of – think of the actual decision that the person is trying to make.

What is it that is important to the user? If their role is to influence customers, how are they doing that? And then find a way to actually achieve it. Meaning if your data warehouse is not performing, you have to find a way to get there. Don’t start from the performance of the data warehouse; start from the end result and then find a way to meet it.

Tableau: You mentioned security. Are you managing security at the data level?
Evan: Yes, we tend to secure access at the data level. The Tableau security is more a mechanism to control who can see what, because if everyone can see everything, it’s very confusing. So you only want people to see what they’re consuming. So we use the Tableau security more in that way, and we secure access at the data level. So if they were not permitted to see it, they would not see the results anyway.
Tableau: That’s great. Any final thoughts?
Evan: You can’t predict up front. We had a certain view of what we were going to analyze, but you cannot predict the path that follows. Where people go with analysis is very interesting. Each person has their own view of what they’re trying to analyze. All you can do is go with it and encourage it. It’s a fascinating journey once you start because it’s not within your control.

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