Leading the way in innovation for over 55 years, we build greater futures for businesses across multiple industries and 55 countries.
Our expert, committed team put our shared beliefs into action – every day. Together, we combine innovation and collective knowledge to create the extraordinary.
We share news, insights, analysis and research – tailored to your unique interests – to help you deepen your knowledge and impact.
At TCS, we believe exceptional work begins with hiring, celebrating and nurturing the best people — from all walks of life.
Get access to a catalog of the latest news stories from across TCS. Discover our press releases, reports, and company announcements.
With an ever-growing abundance of data in today’s ecosystem, there is a significant role played by data analytics in enhancing day-to-day tasks of an individual or a business. Data dashboards provide centralized access to information in visual or structured formats. These dashboards comprise a collection of visual reports that display key performance indicators (KPI), important metrics, and key data points—usually in real-time—to monitor the health of a business. In the clinical trial process, as well, analytics play a vital role in risk-based monitoring.
The role of KPIs
In the pharmaceutical industry, KPIs and key risk indicators (KRI) are critical where subject-safety, data quality, and early risk assessments play a crucial role. To digitize the process of clinical trials without compromising important quality checks, the industry needs a solution that is powered by KPIs and KRIs, and follows a proactive approach to quickly identify issues and accelerate the process. Risk-based monitoring targets and maps resources around risks related to subjects and efficacy. Monitoring critical processes and data through efficient visualization tools, such as charts, bar graphs, etc., offers quality insights and improves productivity in pharma research. Visualization in clinical trials should be designed such that it quickly and precisely identifies the outlines and issues alerts to end users in real time.
Effective analytical interfaces
Knowing how to structure the data is the first step in developing a robust analytics interface that can help in making smarter decisions. Selecting the right kind of data visualization from a list is the next and most important step, since it enhances usability of the dashboard. Listed below are a few aspects that should be considered while developing a data-intensive analytics application.
Unified, user-first approaches
The information provided by data dashboards should be concise, crisp, and in real time. From an end-user perspective, all data visualizations on a screen should form a unified view. The main question that should be asked throughout the dashboard design process is whether the intended user interface is seamless and effortless for users to learn and work on. Pilot studies and focus group discussions demonstrating existing knowledge and prior success prove extremely valuable here.
Relevant data dashboard screens
Dashboards should allow users to have a seamless experience. The information furnished by dashboards should be precise, with a provision to have optimal visuals for each KPI. Visual tools such as graphs and charts present data in an easily understandable format. Understanding the purpose of each chart or graph helps users choose the most appropriate tool for requirements.
For example, bar charts and column charts are primarily used to summarize data in categories or provide value-based metrics, whereas line graphs display continuous data over time. Pie charts display related category breakdowns, and a gauge chart measures KPIs against set targets. The most appropriate chart for a dashboard’s end objectives should be chosen carefully. From a visual standpoint, RAG (red, amber, green) thresholds are critical to the presentation of KRIs.
The role of user research in the development process
The process of developing dashboards is centered on users and begins with creating user personas, collecting information about user roles, and mapping out user stories. User research plays a pivotal role during all stages of development and involves creating wireframes, testing, and validation. This can be used as a guide for developers through wireframes that contain action-oriented information to understand functional needs and eliminate gaps during development.
User experience (UX)
Users will judge any application on its ease of navigation and ability to reduce effort. Here are a few important aspects of any dashboard screen:
Structure: The page should be structured in a way that draws attention to significant data points and follows UX standards.
Colors: The use of monochromatic colors on a dashboard helps to provide a clean appearance.
Contrast: Contrast, when used sparingly, can help communicate a point or quickly distinguish outliers.
Repetition and consistency: Repetition and consistency across the board can make a design intuitive and engaging for the user.
Responsiveness: A device-agnostic design format will add more value to the application.
Conclusion
Analytics play a vital role in the digitization process of clinical trials, especially with the plethora of data around us. Thus, it is imperative that dashboards are created with user personas and experiences in mind. A sound knowledge of visualization and UX principles will help develop and architect applications that add value to the pharmaceutical industry.
Harnessing Generative AI in Procurement for Enhanced Efficiency
Enhancing Dealer Network Management with Master Data Management
Overcoming Barriers to Gen AI Adoption
The Role of AI in HRMS Industry