The more the data, the better will be the analysis leading to effective problem-solving skills resulting in the smooth running of the veterinary markets.
FREMONT, CA: Data analytics involves the techniques and processes of collecting, cleaning, transforming, scrutinizing, and modeling descriptive (qualitative) and mathematical (quantitative) data to understand a problem and its existence. By doing so, the process lends itself to evidence-based problem-solving. Data analytics is the foundation for efficiently reaching goals and objectives, and it can do the same for veterinary medicine.
The veterinary profession defaults to a problem-solving method involving trial-and-error. Due to this, many of the problems are unresolved as new issues take hold. Also, it takes a longer time for trial-and-error practice to yield solutions as it exceeds the longevity of each critical problem, where evidence-based solutions are never identified or implemented. Although many professional associations and private organizations have collected and analyzed data intermittently to find solutions for problems, none has continuously and consistently gathered the comprehensive set of data required to enable the ongoing analysis of the veterinary markets.
A large volume of collected data is from surveys and not from actual transactions or measurements of other actions. Both types of data collected over time can indicate how an event is changing. However, they do not necessarily give equally essential data about the occurrence of something. Responses to surveys are subjective that the respondents are apt to provide answers that are inexact or that they perceive the surveyor expects to hear through a phenomenon known as social bias.
There are sectors of veterinary medicine that do share data for analysis. The U.S-accredited colleges of veterinary medicine share information with the Association of American Veterinary Medical Colleges. Members of both groups collect and share practice information within themselves. Manufacturers and distributors enlist a single entity to pile up sales data while large practice chains aggregate their hospitals' data to derive health-care and economic insights, most of which they keep private. On the other hand, independent practice owners and other owners of practice groups likewise could pool their data. It could be anonymized for privacy and handled by an umbrella group that serves all contributors and participants equally.
Disparate entities invested in the veterinary profession must learn to collaborate to provide the comprehensive and consistent information needed to explain the existence of problems. Only through cooperation and instituting sound data analytic processes, knowledge to manage and minimize persistent problems can be acquired.