Home Our Insights Insights Elevating Animal Health Data Analytics: Unleashing the Potential through Effective Report Design

Elevating Animal Health Data Analytics: Unleashing the Potential through Effective Report Design

Maciej Kłodaś Head of UX
5 min read
25.08.2023

In the animal health industry, well-crafted reports in data analytics play a pivotal role in accelerating analyses, expediting data inferences, reducing cognitive load, and minimizing errors. Equipping staff with data literacy and confidence is of paramount importance. Effective report design can lead to analyses being conducted 2x-3x faster and data inferences up to 6x faster, thereby unlocking the potential for success through data utilization.

Introduction

In the current stage of the animal health data analytics evolution, the process of gathering data, ensuring its quality, processing it, and then leaving the rest to the analysts has become a standard practice, much like vehicles being equipped with essential features such as air conditioning. However, there is one aspect that often goes unnoticed, and addressing this element can substantially enhance the analytics process. This enhancement can translate to achievements like tripling current analysis speeds or achieving data inference speeds up to six times faster. What is this crucial element?

In the past, securing a competitive edge in the animal health industry revolved around obtaining access to data and leveraging it to make superior decisions compared to competitors. Subsequently, data began to be collected in diverse formats (ranging from spreadsheets to text files and printed reports). Those with more proficient analysts had an advantage in accessing and dissecting this data.

The era of dashboards then arrived, introducing data visualization, automation, big data, and the democratization of reporting. Presently, as most companies in the animal health sector rely on data for informed decisions, the focus has shifted towards sophisticated analytics involving natural language processing (NLP), natural language generation (NLG), machine learning (ML) algorithms, and automation. This transition underscores the importance of empowering non-experts with analytical capabilities.

Unfolding Chapter

Animal health data analytics has progressed significantly from the time when individuals with specific analytical skills managed data while business personnel were merely recipients of analysis outcomes. The landscape has transformed. Business individuals now actively engage with reports, regardless of their varied analytical skills. This accentuates the significance of well-designed reports as they enable individuals without deep data analysis expertise to effectively grasp insights and discoveries from these reports.

Nevertheless, the growing democratization of data analysis and the increasing technological support do not mark the end of the journey. A further step is required to gain a competitive advantage through data: enhancing the analytics experience.

This can be accomplished by developing reports that are easily comprehensible, thereby being truly enlightening and empowering. The foremost goal is to reduce the analytical entry barrier and elevate the overall data literacy within the organization. As evidence of this approach, our team has produced the C&F Insights publication.

Today and Beyond

Empowering animal health industry employees to drive data-informed decisions hinges on fostering the confidence and capability to make independent choices. However, this requires employees to comprehend data—an essential precondition. Recent research conducted at C&F Insights using eye-tracking technology investigates how the design of an analytical report influences its recipients and the quality of their data-related tasks. The findings highlight that well-designed reports lead to analyses being conducted 2x-3x faster, enabling users to promptly identify relevant insights within the report. Moreover, these reports facilitate data inference speeds that are 5x-6x faster while maintaining high confidence levels in delivering accurate answers and identifying precise data points. Furthermore, well-designed reports result in cognitive load reduction by 2x-3x, making them more accessible for information extraction. This equates to a potential 3x reduction in error risk compared to poorly designed reports. You can access the full report from our research.

Final Stages

An analytical report in the animal health sector serves as a document presenting data and its analysis on specific topics or issues, aiming to guide decision-making. These documents vary in complexity and length based on subject matter and user needs. They cover various subjects, including market research, financial analysis, performance evaluations, and more.

Imagine an organization in the animal health industry with its IT systems, trained experts, data sets, and substantial investments in data management and quality control, akin to a production line. This production line generates analytical reports as its final output. But can this final output fall short of expectations, even with a well-functioning production line? In the context of analytical reports, this is an all-too-common scenario.

Costs of Insufficiency

Reviewing data on dashboards and reports should ultimately provide individuals with enough information to carry out their daily tasks. However, this doesn’t always happen, and the repercussions of these inadequacies can include time wastage, frustration, reduced productivity, a burdensome analytical load, missed opportunities, uncertainty, and the stress of decision-making with limited insights. This can potentially lead to misguided decisions, loss of confidence, lack of initiative, decreased team loyalty, and diminished sense of value.

These costs stem from how dashboards or reports are constructed, designed, and tailored to a specific audience’s objectives, context of data utilization, and behaviors. Elements such as colors, title sizes, descriptions, nomenclature, data hierarchy, visualizations, and layout each contribute, with certain elements exerting more influence. Overlooking these factors significantly heightens the risk of crafting a less effective report that’s harder to analyze, entails higher analytical costs, and yields lower-quality insights and decisions.

Even if an animal health organization employs advanced technical data solutions, what truly matters is the report and how end-users interpret and employ the data. Crafting an exceptional data analysis experience eradicates uncertainty and fosters confidence in decision-making, leading to enhanced business outcomes. Consequently, investing in user experience (UX) design within analytics can be the key to triumph in the contemporary data-driven landscape.

The Essence of Quality Insights

While data itself is invaluable, the generation of high-quality insights drives actions founded on data analysis. By prioritizing effective data design, animal health organizations can unlock the latent potential within their data, enabling employees to make well-informed decisions. This results in elevated job satisfaction, increased engagement levels, and a fortified competitive advantage within the data-driven animal health domain.

The journey of animal health data analytics transcends data collection and processing. It encompasses the art of shaping meaningful reports, fostering favorable analytical experiences, and enabling employees to harness the potency of data. Embracing these principles empowers animal health organizations to convert their data into a strategic asset, steering triumph in today’s era driven by data.