Three tips for designing a great dashbord

We are experiencing an increasing demand for dashboards. In these uncertain times, I notice among customers that there is a strong need to gain insight into the performance of the supply chain. Companies have more and more data at their disposal and with the right insights from this data, companies can make better decisions. According to BI Survey, this “data-driving culture” is one of the most important Business Intelligence developments of 2024 [1].

Some examples are the Energy dashboard by the European Union [2] or from somewhat longer ago: the coronavirus dashboard of the Dutch government [3]. While tracking completely separate topics, they have a few things in common: they merge data from different sources, they organize and visualize data in a clear and concise manner, and they are used to guide decision-making.

Recently, I got the challenge to create a dashboard for one of our customers to show the performance of their service supply chain. In this blog, I give my three main tips for designing a great dashboard.

1. Define a clear goal

First of all, define a clear goal for your dashboard. At Gordian, we are convinced that customers’ capital goods do not have to experience downtime due to logistical shortcomings. Based on this belief, we help customers to improve their performance. The goal of the customer has an important influence on the design of the dashboard. It determines which topics to focus on. Without a clear goal, it is unclear what information to focus on and what decisions must be taken.

2. Keep it simple

Secondly, apply the “less is more”-principle. Try to display your company goal by means of 3 or 4 Key Performance Indicators (KPI) on one page. A KPI makes the performance of a company measurable and transparent, which is indispensable to achieve your objectives. At Gordian, we mainly look at the relationship between the KPIs logistics delay time, stock value and operational costs to quantify the performance of the service supply chain.

By displaying a limited number of KPIs in one overview, you can focus on the most important indicators to achieve your company goal. In addition, use color coding to show compliance or non-compliance and line charts to plot the development of the KPI over time. By means of colors and graphs you quickly get a general picture of the trend of a KPI.

3. Add indicators to explain bad actors

Thirdly, the dashboard should help you answer the following questions:

  • What is going well?
  • What is not going well?
  • What is the reason why things are not going well?
  • What actions are needed to improve it?

By creating a hierarchical KPI dashboard, bad actors at the highest level can be traced back to the root cause and the responsible process owner. For example, the logistics delay time is influenced by the delivery reliability [4] and lateness [5]. The logistics response time [6] and stock availability [7] are the main drivers of the delivery reliability. By means of cross-sections and drill down-options in the dashboard, you can quickly get an overview of the most important bad actors of a (K)PI.


With a good dashboard you can display the most important data in one overview, enabling you to make fact-based decisions. By applying Deming’s Plan-Do-Check-Act cycle, you are repeatedly making decisions in order to continuously improve your business performance.

Are you still struggling to create great dashboards after this blog, or do you have any awesome dashboard inspiration to share, please contact us!

[1] https://bi-survey.com/top-business-intelligence-trends

[2] Energy Visualisation Portal (europa.eu)

[3] https://coronadashboard.government.nl/

[4] The percentage of requests that were fully delivered on or before the requested delivery date

[5] The average number of days in which the requested delivery date is exceeded. Measured on all late deliveries.

[6] The average number of days between issuing the request and the requested delivery date.

[7] The probability that a request can be fulfilled from stock at any point in time

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