5 Myths About Analytics Modeling: Busted
Though most businesses employ some form of data analytics, relatively few professionals have an intimate knowledge of the data collection and analysis process. This isn’t particularly surprising. After all, analytics modeling is a complex subject, and, as such, there are plenty of misconceptions regarding the use of data analysis. Today we’ll explore five of the most frequently disseminated myths regarding analytics. Plus we’ll also explain how analytics modeling relates specifically to the healthcare industry:
All Forms of Data Analysis are Essentially the Same
While, yes, every type of analysis involves collecting and interpreting data, to suggest that all analytics models operate in the same way is a gross oversimplification. Indeed, there are a number of different varieties of data analytics, from descriptive and diagnostic analysis, to predictive models. What’s more, analytics models require constant attention –– since the variables that affect their outcomes are also always in flux. (And that’s especially true in the healthcare field where technologies and industry policies and best practices evolve quickly.)
Data Collection is More Important than Analysis
It’s true that without proper data collection practices, reliable analysis is virtually impossible. However, piles of raw data won’t amount to much in terms of actionable solutions without the application of sound analytic methods. In reality, neither data collection nor analytics is more important than the other; the two function as equal parts of the same concept.
Data Analytics is Only About Money
Can businesses use analytics models to become more cost-effective? Of course. Still, the idea that business intelligence and data analytics are restricted to expense-cutting and profit maximization is a fallacious one. In terms of the healthcare field, data analytics models are used to deliver widespread patient care in a more streamlined and proficient manner. Population health management is crucial for healthcare centers across the country, and it’s just one of the many ways effective analytics models help medical facilities run more efficiently.
Data Analysis isn’t Forward-Thinking
Just because a large part of the analytics process revolves around studying prior data and results, it doesn’t mean it can’t offer meaningful solutions for the present and future of your organization. Professionals who understand the benefits associated with analyzing past performance will, naturally, improve the way they address problems over time.
All Data Management Firms are Created Equal
What’s the difference between one analytics company and another? A good deal, potentially. In terms of price, performance, and service, data management companies run a wide gamut. With that in mind, it’s imperative that your organization partners with a firm that 1) understands your industry and needs and 2) will help you reach your goals in the short and long term. Lastly, remember that low price doesn’t always equate to value. Before you make any business decision of this magnitude, be sure to do your research first!
Data management might not be the first thing on a healthcare professional’s mind, but how your organization takes in and makes use of available data will affect every level of your operation. At Amitech, we understand the unique challenges medical facilities face –– because we’ve partnered with them for years. So contact us here to get started today!