Informed decisions can work out well for organizations, if the iconic baseball movie Moneyball is any indication. In the movie, Brad Pitt starred as coach Billy Beane. Coach Beane used certain performance metrics to predict success for the Oakland A’s baseball team, as well as, minimize his costs for hiring players. Long story short, it worked.
It was about fifty years ago that former NFL quarterback Virgil Carter started working with big data by attempting to quantify the number of net points a team could anticipate, based on their position on the field, down, and distance remaining for a first down. Carter is credited with going beyond the traditional box score by instituting analytics for better decisions.
From a business perspective, you need to formulate an approach for problem solving. The needs of each and every business are going to be different. The approach they take is going to be different. Irrespective of whether business markets are becoming more complex or businesses themselves are becoming more analytical, better decision making is becoming more important for the average company.
For example, Quest Diagnostics is a formidable provider of clinical lab tests. But they also tout their company as having ‘the world’s largest database of clinical lab results.’ Several years ago, Quest made the decision to move into data analytics.
In effect, they had a tremendous amount of data at their fingertips and they wanted to use it to their competitive advantage. That is exactly what they did and now they consider themselves a clinical lab but also, by using big data, ‘an insights company’.
According to the Oxford Language Dictionary, big data is using extremely large data sets that may be analyzed computationally to reveal patterns, trends, and associations, especially relating to human behavior and interactions.
Louise Lee, of The Wall Street Journal, did a significant amount of research to determine the best ways for small and medium size companies to utilize analytics. Maybe even more importantly, for companies who do not have an entire department or division devoted to analytics, it is of paramount importance to avoid the paralysis of analysis. In other words, be selective in how you begin and expand your journey into the arena of big data.
Several experts agree, you should begin accumulating information that is more historical than your recent quarter. Actually, you should begin your journey by looking at several quarters. Further, establish a specific frequency when you review the information you have obtained. Whether it is weekly, bi-weekly, or even monthly, strive to conduct the review process on a regular basis.
Probably, the most significant decision you will be making is to determine what information you will be using and how you will use it. It is also important that you do not get too bogged down in industry data. While general trends and directions can be helpful, most of the time, they are not realistic for a specific business. There are too many variables influencing your business that may not be impacting the industry at all. A familiar term in business is the initialism KPI (Key Performance Indicator). Take some time to think about what KPIs you would like to develop and once you develop them, how you will use them in your business decision making process.
From a website viewpoint, Google Analytics can provide you with information and KPIs like how many visits there were on your website and when they visited. That example could allow you to analyze traffic to your site based on the timing of a ‘sale’ you conducted. Your business should also determine how people learned about you; via social media, advertising (radio, television, paper, billboard, etc.), or search engines.
Lee goes on to suggest that customer data is very important. She suggests, from a retail perspective, that you develop the means to “solicit all kinds of information about individual customers, including age, gender, and family size. You can learn customers’ geographic locations and purchasing histories, too, from your ordering and fulfillment systems. Then put all of that information into a database program so you can slice and dice it by various criteria. If your data shows a big chunk of customers have large families or live in the suburbs, you can target your promotions and marketing accordingly.”
Be sure to take these examples into consideration, as you think about ways to grow your business using big data. Each piece of information could end up being a big help.