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  • Post published:20/05/2021
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BI Dashboards: A Definition With Detailed Examples

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Modern business practices generate more information from more segments of the business than ever before. Ranging from sales and inventory to internal processes and projects to social media and website interactions, the information forms a key part of organizational strategy.

With such a bounty available, the most successful businesses are the ones that best utilize their information. Those that do are able to time their moves, such as software development projects, for more efficient sales and accessing larger markets. This is because business information tells these businesses where their customers are, what they’re interested in, and when they’re likely to buy. The information can also educate you about internal processes and pipelines. Is there anything slowing you down? Is there a chance of streamlining and automating? Do you have security issues that need to be patched? Are developers happy or burnt out? Are features being released or left behind? Even whether you’re creating your business information using the right data or not.

But with so much information available, how do you make sense of the mess?

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This is where we fall back on the old phrase that a picture is worth a thousand words. That might be an exaggeration. But there’s no denying the power of a well-designed graph. And that’s what business intelligence (BI) dashboards are all about. They use visualizations to tell the story of your business information on a single page. They give you a snapshot showing the good, the bad, and the ugly—unlocking the potential of business information. In this post, you’ll find two detailed examples demonstrating two uses of BI dashboards for unlocking business information. Before diving into that though, let’s start from the bottom and build a definition of what BI dashboards are and what they can do.

Definition

There are two ways to go about this. I could simply define what a BI dashboard is in a sentence or two and then present some examples, hoping you’d understand. Or I could build up the principles and then move on to the examples, with the foundations in place. The second way might take a bit longer, but it’s true to the Plutora values. In this section, I’ll first introduce what business intelligence is, before introducing dashboards and finally bringing it all together into BI dashboards.

Business Intelligence

Business intelligence is all about gaining and using insight from organizational data to inform company strategy. Specifically, BI is the set of information that describes the historical, current, and predictive future states of an organization. In practical terms, it’s heavily intertwined with technology and the process of transforming raw organizational data into actionable business information (i.e., intelligence). Common BI functions include reporting, data analytics, business analytics, process optimization, performance management, and predictive analytics. To keep up with these functions, BI technologies are designed to rapidly handle large volumes of mostly structured data. Some inputs, however, may include unstructured data.

The goal of BI, therefore, is to identify, describe, develop, and progress strategic business opportunities. This allows organizations to flourish with strong competitive advantages and stability.

Dashboards

When most of us hear the term dashboard, we immediately think about cars. And why wouldn’t we? In that neat display, we can see a snapshot of everything we need to know about driving (beyond paying attention to the road, of course). If we think of the car as an organization and the dashboard as a set of related graphs, we can see why the term is used. It’s a neat analogy to dashboards in our context, which can be defined as a single page of time-dependent visualizations.

It’s a short definition. But one that packs a large punch. So let’s break it down a bit. There are three distinct components in this definition: visualizations, a single page, and time dependency.

  1. Visualizations take us back to the introduction. I used the old phrase about a picture being worth a thousand words. Much like a speedometer, visualizations in a dashboard tell you what you need to know about your data in as little space as possible, with visual elements scaled and highlighted by importance.
  2. In a good dashboard all the visualizations are contained on a single page. Users are therefore able to grasp the whole picture, and not a subset that they need to navigate. It’s not only an increase in usability, it’s an increase in understandability, and, therefore, decision-making.
  3. Finally, dashboards are time dependent. In my opinion, this is the biggest aspect. By introducing time, dashboards separate themselves from ad hoc reports and free themselves from the shackles of manual updates. It means that the data being presented is never out of date.

With that in mind, the goal of dashboards is to increase data access for at-a-glance understanding, which leads to better decision-making.

BI Dashboards

The problem with BI as introduced above is that it’s discrete and often a single-use process. Someone in an organization performs some data analytics and builds a report, which the company acts upon. This involves a lot of time-consuming, manual work that needs to be adjusted and repeated each time a decision is required or whenever the data changes. In the modern, data-dense, fast-paced business world, that’s not feasible. This is where the marriage with dashboards comes into its own. If you remember, one of the keys of dashboards is the time dependence of the visualizations.

Therefore, a BI dashboard can be defined as a single page of time-dependent visualizations that describe the historical, current, and predictive states of an organization. They highlight important organizational data, such as KPIs, business analytics results, and process metrics. BI dashboards allow you to adjust business strategy at any time, without the need to run a specific report or piece of analysis. In fact, BI dashboards commonly contain a summary of multiple dynamic reports. This allows users to get an overview of everything they need at a glance and then drill down into the details as required.

Examples

The best way to understand BI dashboards is to see how they’re used in practice. With so many moving pieces, requests, and constant changes, one of the business sectors that can benefit most from dashboards is software development. So, without further ado, let’s jump into some examples using Plutora.

Value Streams

The first BI dashboard example I’m going to explore is visualizing metrics related to your software value stream (if you need a refresher on value streams, click here). In short, the value stream is a description of the software development process from the moment of idea creation right through to when the software product is in use by the customer. As you can imagine with something so all-encompassing, there’s a lot of business data. And not static business data. Ever-changing business data.

That makes it a perfect candidate for a BI dashboard. Not only is the data always evolving, but a near-infinite number of small and large decisions need to be made based on the data. Moreover, the decisions must be made while the process is underway. You can’t pause development to run a few reports and check everything’s on track.

Have a look at the screenshot below.

This is an example from the Plutora Value Stream Management platform. Per the screenshot, you can see how efficiently your software delivery factory is running in one glance. 

This screenshot shows an organization’s level of automation, with test automation percentages for each value stream. It gives a quick snapshot of the number of tests running, whether they can be automated, and how much has actually been automated.   

Total Cost of Application Ownership

Alongside value streams, BI dashboards are great at combining business information from different sources across an organization, such as financial and software. This example demonstrates that utility in Plutora via the total cost of application ownership.

The total cost of application ownership is the sum of all direct and indirect costs incurred by that software and is a critical part of the ROI calculation.

In this example, we see the strength of BI dashboards in presenting to different stakeholders. Having a dynamic, time-variable display that combines a variety of business information allows you to explore and explain the benefits of an application. Below is an example of total cost of application ownership for environments: 

The screenshot shows cost by day and also for the selected duration by Environments and by Projects (which is the shared cost when an environment is used by multiple bookings/projects) .

Okay, So What Next?

As with most things that are visual, it’s great to hear about it and see some examples, but the real power comes in using it. If you want to see how a BI dashboard can work for your organization, request a demo with Plutora.

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