Sales analytics: Identify decisions then acquire data
A. Analytics can be a powerful tool in the DME space when leveraged properly, but the key to making implementation most effective is a complete understanding of analytics’ capabilities and best practices.
A common misconception is that analytics is simply software, leading to data being loaded into a system, but not properly utilized. It is important to recognize that analytics is actually the systematic use of data and varied business assumptions, developed through the application of analytical disciplines and associated models to drive fact-based decision-making.
Once there is a complete comprehension of the definition of analytics, there are a few simple best practices that DME companies need to consider while beginning to implement an analytics program.
First, identify the decisions you want to make before thinking about acquiring data. Data is often a very expensive proposition, so questions need to be clearly outlined to understand what information will be required before embarking on the acquisition process. These questions will influence what data is necessary.
Simple questions require very few data elements, while complex questions—such as those regarding access and reimbursement, primary and secondary procedures, diagnosis, or polypharmaceutical patterns—often require sizeable amounts of data.
This large quantity of data can incorporate ZTT (sales and marketing zip code hierarchy assignment) files, reimbursement files and claims detail files from payers and PBMs, combined into one master file with multiple joins and indexes.
After deciding what information you require, data should be laid out by element and then run against numerous models.
The more thorough the model, the more accurate algorithms become, leading to the most effective results.
Zachary Madrigal is vice president of business development, HME Healthcare, for Genpact USA. He can be reached at 203.512.3501 or email@example.com.