Companies that make data-driven decisions tend to be 6% more profitable than their competitors. With quintillions of bytes of new data being created every day, data-driven decision-making (DDDM) empowers businesses to act on insights that can lead to greater profitability.

However, relying entirely on data is a questionable approach for a business leader. On the contrary, it is better to find a balance between gut instinct and DDDM, thus avoiding costly missteps.

What is DDDM?

It involves using big data to make informed choices, i.e. using various metrics to achieve business goals. DDDM plays a vital role in many business-related activities, such as surveys to determine the types of goods and services that customers might want. Companies also use DDDM when studying changing demographics to consider new business opportunities.

DDDM is making its presence felt in healthcare, as noted by Joel VanEaton, vice president of compliance and regulatory affairs at Broad River Rehab, a skilled nursing facility in Arden, NC Van Eaton, writing for McKnight’s Long-Term Care News, put this way:

“When looked at strategically, data has a voice, it comes to life, it can actually tell you a lot. are used deliberately by the Centers for Medicare & Medicaid Services to compare communities to others in their locality and across the country.”

Benefits of DDDM

Adopting DDDM can eliminate some errors and false assumptions, although many companies rely more on intuition to make consequential decisions. While it can reveal what numbers cannot, there are many advantages to using DDDM:

• Increased confidence: Collecting and analyzing data can provide certainty when making certain decisions. Even when DDDM doesn’t yield an optimal result, prioritizing data over instinct ensures you’ve acted on the best information available.

• Proactive decision making: Executing a decision after analyzing the data is usually a reactionary course of action. However, data can also help you be more proactive. DDDM can help you see trends before the competition or detect threats before they become overwhelming.

• Faster decision making: Deliberation can be effective in ensuring the best course of action. However, when decisions are urgent, having objective data to support your action proposal can reduce the time needed for debate. In a competitive market, making quick decisions can give you an edge.

VanEaton offered as an example the Research Data Assistance Center, a database that provides actionable information for skilled nursing (SNF) facilities. He specifically mentioned data reflecting the fact that patients readmitted to hospitals from SNF are more likely to have sepsis than to have the condition during their initial stay, and concluded that such information would enable SNF to formulate plans to curb the trend.

Problems with DDDM

DDDM is not a panacea, and it can even be detrimental if done incorrectly. Here are some caveats:

• Use of unreliable data: Available data is not always accurate and companies that base their decisions on this information can lose credibility with their customers and stakeholders. Additionally, unreliable or incorrect data can lead managers back to intuition when faced with critical choices.

• Inability to draw appropriate conclusions: Another potential problem is the inability to understand what information the data may reveal. Part of the battle is to understand the source of this data and what it represents. Also, a conclusion may be premature if you have not gathered enough information.

• Paralysis of analysis: While it may seem ideal to collect as much data as possible, sometimes large amounts of data are overwhelming, making it difficult to move around.

Keys to effective DDDM

Most successful CEOs admit that effective decision-making involves a balance between data and instinct. While it’s okay to listen to your instincts sometimes, it’s best to verify and quantify these feelings with objective information. Here are ways to optimize DDDM:

• Determine your business objectives: Determine the most important challenges facing your business, then ask the questions the data can help you answer. Otherwise, you may find yourself chasing after your tail.

• Understand different types of data: Not all data is in quantitative or numerical form. Some are qualitative, focusing on observation rather than measurement. This data (from interviews, focus groups, etc.) can help you understand the reasons for trends and changes that quantitative data might reveal.

• Know your data sources: Knowing the origin of your data can help you determine its accuracy, credibility and usefulness. Whether you draw from an internal or external source, this is an essential step.

• Keep your data clean: Always “clean” your raw data before doing any type of analysis. This means removing incomplete or incorrect numbers, or classifying and defining variables so you know what their measurements mean in the overall analysis.

• Use the appropriate analysis: Good data analysis depends on knowing the conclusions you want to draw. For example, there is a difference between using information descriptively (e.g., frequency counts) and using inferential statistics to show that a group’s average numbers are significantly higher than those of another. Other findings may require predictive insights, which uses data to recommend a course of action based on past events.

• Minimize unconscious bias: We all tend to have biased judgment. The key is to be aware and prevent bias from clouding the way we interpret data. A team of people skilled with DDDM can bring multiple perspectives to the table and cover everyone’s blind spots.

• Revisit and reassess: No analysis or conclusion is ever definitive. Be sure to bring in an objective colleague to verify your results. Walk away from your research and rethink your proposed decision before recommending or acting on it. Ask yourself what you can change or improve.

In short, a flood of data is now available to actors in the health sector and beyond. Carefully and comprehensively analyzed, it can be of great value, informing decisions and the very direction of a business like an SNF.