Using verifiable data to make decisions is a valuable business strategy. Research shows that data-driven decision-making (DDDM) increases performance, output, and productivity. Top-performing organizations use analytics 5 times more than lower performers.
Firms that adopt DDDM have output and productivity that is 5-6% higher than what would be expected given their other investments and information technology usage.
Effective use of data to drive decision-making requires:
1. A culture that supports DDDM, along with a commitment to data transparency
2. Structured and trusted DDDM definitions, activities, and processes to collect, analyze, and interpret internal and external data
You need leadership and a culture that values data (all types of data) and data-driven insights. You need structured, trusted processes and competent staff to:
• Identify pertinent business questions
• Establish common metric definitions
• Collect and organize relevant data
• Analyze data (data analysts/statisticians)
• Draw appropriate conclusions
• Build action plans
If the wrong or bad data are collected or analyzed incorrectly, then leaders will use it to draw incorrect conclusions.
In L&D, there is often the problem that data are collected, but not analyzed. I was on a webinar recently and heard someone say, “We use the Kirkpatrick model and administer surveys but don’t do anything with them. We don’t know what to do with the data.” Right there—the two DDDM requirements are not met and it’s a waste of everyone’s time and resources. Then why are they surveying? Because they think they are “supposed to,” but they don’t know why. That’s an example of an unsupportive DDDM culture and poor activities and processes.
Are you using THE RIGHT data to make THE RIGHT decisions that support THE RIGHT outcomes in THE RIGHT moment? Does your organization meet the two DDDM requirements?