Even though using data analytics has not traditionally been a part of hospital and health system CEOs' job descriptions, in the era of Big Data, understanding analytics has become a competitive necessity for healthcare leaders. However, this is intimidating for some leaders without finance and data analytics training.
"A lot of people want to hide because they weren't particularly quantitative in school or school was a long time ago, but given the number of executives that want to use data-driven insights to propel their decision-making, you can only hide for so long," Thomas H. Davenport, PhD, a professor at Babson College and the author of Big Data at Work, told the Harvard Business Review.
But hiding is bad for your organization, and will only perpetuate your lack of understanding on the topic. It is important for leaders to learn to interpret results and use data analytics to make better decisions and increase efficiency.
Here are six strategies for leaders who seek to improve their understanding of data analytics and their skills working with the quant team.
1. Make the effort to learn. While those who remember what they learned in their college statistics courses or business schools might be in good shape, those who don't, or are a little bit more numerically challenged may require a refresher. HBR suggests enrolling in an executive education class, reading books and articles on data analytics or taking an online course. The ultimate goal is to become data literate.
"It's not hard to get the fundamentals down," Joe Knight, a partner and consultant at the Business Literacy Institute and co-author of Financial Intelligence, told HBR. "You need to have a sound baseline understanding of business analysis — including the four families of financial ratios and tools for calculating return on investment." Mr. Knight also suggests gaining a solid understanding on the basics of regression analysis — what it means and how it is performed.
2. Build relationships with the "numbers people." In some organizations, the business executives and quant team often find themselves butting heads. Managers may feel, "'Those numbers guys are always ruining our projects.' While the analysts think, 'Those business people don't understand the analysis.' It's counterproductive," Mr. Knight told HBR.
It is important not to simply write off the quants as number crunchers. You will see much better results if the "business people" and "numbers guys" develop strong relationships and mutual trust, according to Dr. Davenport. The best way to build these bridges could be for business leaders to make it clear they value the analysts' skills and want to learn from them. Saying, "I have a lot to learn from you," can be a meaningful first step.
3. Include quants in the decision-making process. "Make the quant a full-fledged member of your team," Dr. Davenport told HBR. "Expose them to the business problems, so they can see them with their own eyes." To prepare them for success, set up frequent meetings and project-reporting sessions so they have a comprehensive understanding of the business side.
However, analysts should not just be brought in to observe. Rather, they should be included in the decision-making process, especially when it involves the data they've delivered. Ask for their opinions, as they will likely have different insight than the rest of your team.
4. Encourage open communication. You need to have open and honest communication to form valuable relationships with the quant team. It is also important for business leaders to ask lots of questions, such as "What are the assumptions you're using in this model?" "Under what conditions might those assumptions become invalid?" And, "How well do the sample data represent the population?" according to Dr. Davenport.
"Don't be afraid to admit what you don't know," Dr. Davenport said, adding it is important to always ask for clarification if you're confused.
5. Don't let the volume of data overwhelm you. The sheer volume of data available can be intimidating. However, business leaders don't necessarily have to pay attention to all of it.
"All businesses run on a few key metrics," said Mr. Knight. "You don't need to be looking at 10 to 20. That's too many. You need to understand the two or three that drive your organization's profitability and cash flow."
According to Mr. Knight, when looking at data, business leaders can weed out the metrics that don't have a big impact, and instead zero in on those that do.
6. Respect the data. Data should drive decision-making in business, not instincts or opinions. Although "a good operations executive might have an intuitive feel for what could work in the business," the leader should never pressure an analyst to seek out data to support his or her opinion, according to Mr. Knight. Doing so would defeat the purpose of rigorous analysis and create an environment where the data team feels its sole purpose is to please the leader.
It is important for leaders to be willing to conduct experiments and trial runs to test out their ideas and gut feelings. While there may be instances where you want to overrule that data, ignoring what the numbers convey can be detrimental to the organization.