Data-Driven Decision Making: Technologies and Implementation

Data Collection Methods

Many different technologies can be implemented and applied to data-driven decision making. Decision makers will need to determine what is best for their specific needs. The first step is to identify what type of data you need to collect. For example, you may want to understand the shopping habits of consumers in a particular area. To gather this information, you might implement a questionnaire or survey.

Several distribution methods are available. You may create a survey using Microsoft Word, have a company like Xerox make several thousand copies, and use a mass mailing system to send them to residents. To encourage participation, you can offer incentives such as coupons or a monetary reward for completing and returning the survey. Alternatively, you can post the survey on an online survey platform where residents can respond directly.

Data Storage and Management

Once you have collected the information, you need a way to enter it into a large database or data warehouse system. If surveys are filled out online, you can collect the information as comma-separated fields and import it directly into the database. For paper surveys, you will need a system that can scan the documents, read and interpret the content, and automatically extract and import the information into the database.

Data Analysis and Reporting

After all information is entered, you need to view and understand it without manually reviewing each entry. For this purpose, you will need a program that can query information from the database and present it in a report that provides the answers necessary to make informed decisions for your company.

Critical Considerations in Data-Driven Decision Making

Several important factors should be considered before implementing data-driven decision making. First, understand that this is not an inexpensive solution. The process of collecting, storing, analyzing, and implementing data can be very costly. Be certain about what data you need to collect, ensure you are not misinterpreting the data, and verify that no biases exist when entering the collected information. Any mistakes made during the data collection phase can be costly and may not be discovered until too late.

Second, recognize that data-driven decisions are not made quickly. It takes considerable time to collect and analyze data properly. Take the time to ensure you collect sufficient data to make a proper decision. Many advertisements claim that "two out of three people" or "nine out of ten dentists" prefer a product, but this information was not achieved by surveying only three people or ten dentists. Rather, it came from surveying tens of thousands of people or fifty thousand dentists across the country or even worldwide. Collecting enough data from the appropriate areas, or if the information is general, from a wide enough geographic area to eliminate local fads while including broader patterns, is necessary to retrieve unbiased information.

Third, proper analysis of the information can be a lengthy process. To ensure no information is overlooked and that the correct information is being examined requires time and redundancy. The data should be analyzed by several different people, and each analyst should repeat the process multiple times and compare results to ensure they all reach the same conclusions. Analyzing data only once leaves results vulnerable to speculation and errors that could lead to incorrect conclusions being mistaken for correct ones.