2 posts tagged

BI

Tableau Dashboard Overview

Estimated read time – 7 min

In the previous article, we focused on the problem statement, designed a layout, shared our goal to build a Tableau Dashboard for Superstore dataset. The dashboard should provide insights on most profitable regions, products, customer segments and estimate key performance indicators (KPIs) over the past time.

The data in SuperStore Sales reflect sales and profit of the retail chain in Canada. It includes information about customer orders, refunds, sales and geodata. But we’re mostly interested in sales data, as our main goal is to create an executive dashboard to understand company’s operating margin, find most and least lucrative product categories, and customer segments.

So here’s how the dashboard looks like:

All dashboard elements are placed into containers, we can easily resize or change their hierarchy, this enables to optimize the dashboard and make it more mobile/tablet friendly. We can also filter the data by time periods and choose a specific month and year in the top right corner, and all the charts will be redrawn automatically.

The next field shows key factoids on the company performance: profit, sales, orders count, average discount, customers and sales per customer. Each of the indicators displays YOY, a statistical measure to evaluate a company’s financial progress over time. If the indicator shows positive change, a green arrow will be added, if negative – red.

Below are two core charts, displaying regions (colored based on profit) and profit dynamics. We can click on a specific one to view its stats in-depth.

The green dot on the right chart represents data for a selected month this year, while the blue dot displays the same month last year. When hovering these points you can see a trend line, that facilitates assessing how the company’s doing today.

Let’s move to the second part, here we placed company’s products and customers onto 3 charts. The first one, starting from the left, called bar in bar chart, where you can easily explore product efficiency. For instance, Tables is one of the most inefficient categories, with Breford CR4500 that resulted in significant losses.

Bar in bar chart implementation

Then goes the chart with company’s customers, by default they are sorted in descending order by profitability. The chart is linked with Top Performing Provinces, so if we want to discover best or worst customers for the selected province, the data will be redrawn automatically.

Dashboard Evaluation

We evaluated this dashboard according to the criteria below. On a scale of 1 – 10, 10 being the highest, it gets the following scores from our team :

  1. Meets the tasks – 10,0

  2. Learning curve  – 5,5

  3. Tool functionality – 9,0

  4. Ease of use – 8,5

  5. Compliance of the result – 10,0

  6. Visual evaluation – 9,7

This Tableau Dashboard scored 8.8 out of 10 from the team! In our perspective, the dashboard fully meets the requirements and facilitates understanding of business performance over a reporting period. We can assess profit dynamics in general or for the selected region, and effectively leverage products and customers data in measuring monetary results. The final version is available through this link.

Please let us know your thoughts in the comments down below, how would you rate this dashboard?

 No comments    168   5 mon   BI   BI-tools   guide   tableau

Defining a problem statement for Analytical Dashboard

Estimated read time – 4 min

In our previous post, we announced the beginning of a new series about modern Business intelligence (BI) tools. As the adage goes, “problem first, solution second” – today we’ll start by defining our problem. Let’s consider a fairly common scenario for a large company, one that almost every company, where I happened to work encountered with. Suppose that a top management team holds monthly meetings to review the results of the past month. Their key goal is to maximize the company’s dividends and profits.
Hence the team needs a tool that would display the historical profit trend with some other key indicators for the reporting period. The tool is needed to understand where and how profit is formed, and what are the main drivers for profit growth. We suggest using an analytical dashboard as such a tool.

Problem Statement

Our goal is to design and create a Dashboard using the Superstore Sales data (which is really close to reality) to provide answers to the following questions:

  1. What are the performance indicators values for the past month? It’s necessary for stocktaking and comparing it against the same period last year.
  2. What key factors do affect profit growth?
  3. What categories, subcategories, products and clients generate more profits, and what ones that bring losses?

Reviewing Data

The data contains information about customer purchases (Orders list) and returns (Returns list). The purchasing data includes all available information on orders: record ids, order dates, order-processing priority, number of items, sales and profit margins, discounts, shipping options and prices, customer data, and other useful information. But are only interested in the Orders list.

Snippet of the Orders list

Designing a Layout

We’ll position the header with a brief description on top of the page. Then, goes the time-based filter on par with the header. And the subheading “KPI” on the next line.

First of all, we want to generalize key changes according to the factoids:

  • Profit and YoY growth
  • Sales and YoY growth
  • Orders count and YoY growth
  • Avg Discount and YoY growth
  • Number of customers and YoY growth
  • Sales per Customer and YoY growth

Below will be a graph presented as a tree-like map (or equivalent) with top regions by sales count. It will be comprised of different rectangles, the size will correspond to sales volume while the color to profits made. This brings more clarity and helps understand which regions are most effective. It would be great if the reviewed BI tool would provide expanded information upon clicking on a region so that we could see the difference between regions.

More to the right will be a graph with a historical profit trend, displaying how profits change over time. We will try to dot the reviewed month and the same month last year to trace a trend.

Next is products and customer segments. The horizontal bar chart on the left side will be displayed sales volume and profits arranged by categories and subcategories. And try adding a filter for top product names by profit if the BI tool functionality allows so.

Learn more about how to build an interactive waterfall chart

On the right is a horizontal bar chart with top products sorted by profit
volume.

On the bottom of the page, there will be a horizontal bar chart displaying most lucrative clients. It’s very similar to the previous one, but instead of product names will be shown names of customers grouped by their segment and amount of generated profits.

To sum it up, our dashboard layout will look something like this:

Dashboard draft layout
 No comments    36   6 mon   BI   BI-tools   dashboard