Use case #4: Logistics cost analysis in Tableau

Category: Logistics | Solution: Datama Compare | Type : Ad hoc | Client: Retail | Extension: Tableau

Tags:  #TableauExtension #Stock #Conversion #SupplyChain #Logistics #CostAnalysis

“Datama has been a great tool acquisition that has helped us to deep dive into our analysis in significantly less time than before. Having live insights and commentary about our most impactful variables allows us to provide transparency faster to key decision makers and stakeholders.”

Martin Garza – Supply Chain Analyst – TechStyle


TechStyle is a growing global company that works with an impressive portfolio of prominent and innovative brands. Their continued strategic launching of growing brands has led to a proliferation of both online sales and brick and mortar storefronts. This sustained growth has increased the urgency for clear and efficient business analysis of factors such as cost and performance. Because TechStyle oversees multiple brands, it is essential to have accurate and up-to-date supply chain statistics on the most crucial metrics. Being able to visualize their various costs and how they evolve year over year is crucial to gaining insights for their business. 

TechStyle’s global supply chain and strategy team wanted to see the breakdown of their different costs per unit shipped Year over Year. Their problem was that even if they could calculate whether costs increased or decreased, it was difficult to know what factors, such as origin country, or which brand, was responsible for these changes. These analyses were time consuming, and even with these numbers in hand, it was difficult to visualize this with all of the essential information at a glance.

Eventually, the team found the Datama extension for Tableau, which allowed them to achieve precisely what they were aiming for. This use case will be based on what they were able to achieve in Tableau with DataMa’s waterfall extension (also known as DataMa Compare, for the web version).


Market equation

This particular market equation was interesting, because they wanted to analyze costs, instead of visualizing a standard marketing funnel. For this reason, their market equation differs in multiple ways from the classic market equation. 

Firstly, the end result would be Total Cost per Unit instead of something like Revenue, so all costs were divided by unit. In addition, instead of calculating the product, the costs were summed.

DataMa’s customizable waterfall was ideal for this modified equation (Figure 1).

Figure 1: DataMa’s metrics relations function makes it easy for users to quickly adapt their market equation

TechStyle was able to set up a different cost at each step, divide by the total number of units, set all of the amounts as dollar amounts, and set the total to a sum.


We have created a mock dataset based on TechStyle’s data format, which is available here and visualized in Figure 2.

Figure 2: A sample dataset based on TechStyle’s main metrics and dimensions

On the right-hand side, we have four different costs to track:

1/First Cost

2/Packaging Cost

3/Transport Cost

4/Duty Cost

On the left-hand side, because we want to be able to break down results to see how different dimensions contributed to changes in costs, we include a column for ‘Subsidiary Company‘ (one of multiple TechStyle brands) and a column for ‘Origin Country‘ (of shipping). We also include the total number of units.

Of course, because we want to see the change in costs Year over Year, we include a ‘Year‘ column.


Within the DataMa Tableau extension, the analysis allows us to quantify the change in cost per unit Year over Year. From Figure 3, we can see that the total cost per unit has increased by 11.8% from 2021 to 2022. Within Tableau, the DataMa extension can interact with any filters that are placed on the same dashboard.

Figure 3: The Total Cost per Unit from 2021 to 2021 increased by 11.8%.

Another interesting aspect of TechStyle’s use case is that in this scenario, an increase in cost is seen as a negative outcome. In a standard market funnel, an increase in something like revenue is a positive outcome, so the increases would be shown in green in the waterfall. However, thanks to Datama’s display customization, it is easy to change colors based on what you need to visualize. The colors for increases and decreases were swapped so that an increase in Cost would display as red, indicating a negative outcome at a glance. 

Furthermore, the Datama Tableau extension also allows users to break down changes to identify which factors are driving increases or decreases.

Figure 4 shows a breakdown of ‘First Cost’, showing that even though ‘Company B’, one of the companies in TechStyle’s portfolio, saw some decreases in ‘First Cost’, the increases in cost for the other companies outweighed this decrease. In particular, we can see that the increase in cost is mostly driven by ‘Company A’.

Figure 4: Total Cost per Unit has increased, which can be explained partially by an increase in First Cost of 11.1%

This breakdown can be repeated for each cost, with Datama pinpointing which factors are most interesting and why. Other costs might have mostly been driven by different dimensions, such as ‘Origin Country’


Using the Datama extension, the analytics team at TechStyle was able to create a dynamic waterfall visualization that increased the utility of their Tableau dashboard, providing key stakeholders the essential information they needed, including concise summaries of the key driving factors. Not only does this allow the business to better assess how their costs are evolving, but it also helps them identify key driving factors with no additional analysis, as their data is already automatically connected to Tableau. This integration with Tableau eliminates the need for any additional data engineering, as the data already exists within Tableau, meaning users interacting with the dashboard will have a seamless experience.

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