By Sanna Anjum, Senior Business Intelligence Analyst, CSL
Data analytics dashboards have become increasingly important in organisations; they provide users with an efficient way to monitor and analyse data in real-time, allowing more informed business decisions to be made. Pharma companies generate an extensive amount of data related to drug development, clinical trials, regulatory compliance, medical information and sales and marketing; dashboards allow these companies to efficiently process and analyse these data, uncovering insights and trends which can be used to drive decision-making and improve business outcomes.
However, creating an effective dashboard can be challenging. Let’s take a look at some tips for creating a bespoke dashboard which meets the needs of its users.
Identify User Needs: the first step in creating an effective data analytics dashboard is to identify the needs and goals of its end users; this requires an understanding of the users’ job functions and the different types of data they may require in order to make decisions.
A simple method to identify user needs is conducting user research, such as surveys, or focus groups. This information can help ensure that the dashboard is customised and tailored to meet the specific needs of each user.
Keep Development Simple: the purpose of a data analytics dashboard is to provide users with quick and easy access to relevant information. Therefore, it’s essential to keep the dashboard simple and focused. Avoid cluttering the dashboard with too many metrics or charts, as this can make it overwhelming and difficult to navigate.
To keep the dashboard simple and focused, begin with identifying KPIs which pertain to the users’ needs and end goals. It’s also useful to use data visualisation techniques, such as charts and graphs, to help users understand the data with ease.
Use Real-Time Data: real-time data is an essential part of an effective data analytics dashboard. Real-time data provides users with up-to-date information, enabling them to make more informed business decisions quicker. In addition, real-time data helps users identify trends as they occur, allowing them to respond proactively to changes in the data.
To use real-time data, it’s essential to have a data infrastructure in place which can capture, process, and analyse data quickly; this may require investing in new technologies or software, such as data warehousing or big data analytics, however this investment ultimately enables improved decision-making and better business outcomes.
Test: creating an effective data analytics dashboard is an iterative process; it’s essential to test the dashboard with users in order to identify any issues or areas for improvement. When testing the dashboard, techniques such as usability testing or user acceptance testing often return the best results; these techniques facilitate identifying usability issues, such as confusing navigation or unclear labels. In addition, they can help identify areas for improvement, such as additional KPIs or charts which users would find helpful.
Mistakes to Avoid
On the other hand, it’s essential to avoid certain mistakes which could negatively impact a dashboard’s effectiveness and usefulness. Here are 3 key things to avoid when creating data analytics dashboards:
- Ignoring Data Quality: it’s crucial to ensure that the data used in the dashboard is of high quality; inaccurate or incomplete data can lead to incorrect insights and decisions, therefore it’s important to conduct data quality checks and ensure that the data sources used are reliable and up-to-date.
- Overlooking User Feedback: user feedback is critical to ensuring that the dashboard meets user’s needs and goals. Not incorporating user feedback may result in a dashboard which doesn’t provide the necessary insights and is challenging to use.
- Using Inappropriate Data Visualisation Techniques: using inappropriate data visualisation techniques can also negatively impact the effectiveness of the dashboard. For example, using a pie chart to display large amounts of data can make it difficult to interpret, while a bar chart may be more appropriate. It’s essential to choose appropriate data visualisation techniques which enable users to interpret the data quickly and easily.
Conclusion
To summarise, it’s important for companies to have effective and efficient data analytics dashboards because they allow decision-makers to access relevant information quickly and easily, enabling them to make more informed decisions which improve business outcomes. With the ever-increasing amounts of data generated by businesses, data analytics dashboards provide a way to process and analyse data, uncovering valuable insights that can be used to identify trends, opportunities, and areas for improvement.
Dashboards allow businesses to monitor KPIs in real-time, making it easier to track progress towards goals and adjust strategies as needed. Ultimately, a well-designed dashboard can help organisations make better decisions faster, resulting in improved efficiency, productivity, and profitability.
CSL works with many pharma companies to develop bespoke dashboards; bringing dispersed data together and enabling insights to be shared across businesses. To gain a better understanding of how CSL can help analyse and visualise your data using Power BI and Tableau, take a look at the examples below! In addition, have a read of our case studies to understand dashboard development put into practice.
Power BI
Tableau
