Reach Goals and Increase Profits With Data-Driven Decision Making

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Nupura KolwalkarBy Nupura Kolwalkar, Chief Product Officer, Brightree

What if I told you that you were making decisions the wrong way? Or, that you were leaving money on the table.

You aren’t the only ones. In today’s business environment, gut instinct is not enough to remain competitive. Enter data-driven decision making (DDDM). Simply put, it’s “the process of using data to inform your decision-making process and validate a course of action before committing to it.” Providers that implement DDDM move from analyzing why an outcome occurred to predicting its occurrence and, instead, intentionally moving toward a desired result.

Providers that implement DDDM move from analyzing an occurrance to predicting it

Invalidating the Rearview Mirror Approach

Throughout the DME sphere, organizations are looking retroactively at their business results and wondering why something happened the way it did. But today’s business environment requires a sharp pivot from this rear-view approach. Decision-making shouldn’t be about when, but how.

Let’s take an example. If a goal is never set, DMEs may wonder why their teams only conducted outreach to half of their patients. But with a data-driven goal, providers can take a proactive instead of reactive approach. This is what a data-driven goal sounds like:

My DME can drive $5 million in additional revenue while keeping patients adherent on their therapy. For that to happen, we must reach out to at least 80% of our patient population on a monthly basis to ensure they use their products, order on time, and continue to stay on therapy.

In this scenario, providers identify an objective and a strategy that is proven to achieve it, based on data from their own past, as well as from outside of their organization and in other industries. Bearing this in mind, those providers know how to meet their revenue goal and can focus their most important resources where they will have the biggest impact, thereby maximizing profits with limited resources. By actively analyzing and implementing data, the rearview mirror approach is invalidated.

Breaking Down DDDM

Breaking Down Data-Driven Decision Making

Data-driven decision-making is a five-step process—strategy, identification of key areas, data targeting, collection and analysis, and finally, action items. Let’s take a closer look and understand how DDDM can work in DME from start to finish.

  1. Strategy
  2. Identification of Key Areas
  3. Data Targeting
  4. Collection and Analysis
  5. Action Items

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VGM Playbook Growing Your Business With Data and TechnologyThis article was originally featured in the VGM Playbook: Growing Your Business With Data and Technology. To read the full article and more like this, download your copy of the playbook today

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