One of the great things about technology is the amount of financial data available in which to make decisions. Too much data can be a problem if you don’t know what to do with it all. And quite frankly, too much of the data available today is useless.
The challenge is not just to store all that information, but to understand the opportunities it offers and effectively analyze it ahead of the competition. The key is processing and interpreting the data and gaining insight from it.
Start by separating your data into two categories; the need to know and the nice to know. The 80/20 rule will no doubt come into play here with the need to know category representing 20 percent of all your data. Your need to know data is the information you need to operate and make decisions on a daily basis. Data like: sales, net profit, gross profit margins, average customer transactions, sales and expenses per square foot, average sales per labor hour, shrink, etc. The nice to know data, is just that, nice to know – meaning, you don’t require it to make daily operating decisions.
Analyzing the Numbers
The movie Moneyball dramatized how the Oakland A’s baseball team could win if they studied and played by the numbers the players produced instead of gut instinct and player reputation. Interpretive expertise is important in order to understand what all the data means, draw conclusions, and make wise decisions based on the analysis. Some of the issues that can be tackled are identifying customer and product trends, identifying your most profitable/least profitable customer segments, most profitable/least profitable products and services, along with your most productive/least productive employees.
Lawyers study individual judges’ decisions to gain insights into strategies to use in their courtrooms. Delta Airlines knows before a plane lands that a passenger’s baggage didn’t make the flight. They then alert the passenger about the bags’ whereabouts and when they will get it before the passengers blood begins to boil as he or she waits next to an empty baggage carousel.
Police departments routinely sift through huge volumes of information to predict and plan for crime trends. They may look, for instance, at weather, traffic patterns, sporting event schedules, holidays, and dates of paydays to pinpoint crime hot spots where targets of opportunity like distracted people flush with cash intersect with would-be bad guys.
The Westin/Starwood hotel chain places their customer data into the hands of their employees servicing customers. Upon check-in, the front desk clerk has the technology to bring up the prompt which allows her to make a personal connection with the guest: “Welcome back Ms. Clark. I see you were here with us last October. Would you like to stay in the same room?”
It’s Not All About Sales
You can use data to glean insight into what makes your top performing employees tick and perform at a high level. Human resource departments can use the data to predict how employees will perform on the job and how to get them more engaged and motivated.
HR managers can study data from past employees, including patterns in their behavior on the job, which will lead to identifying personality attributes that are helpful if people are to perform at the level necessary for the position. It requires managers to think like researchers rather than HR people.
By better understanding your workforce (and potential hires) you can maximize their levels of engagement on the job. Assess employee engagement by surveying employees and studying the data. Engaged employees add (not take away) to the bottom line. Engaged employees develop relationships with customers, which results in increased sales, which drives profitability. Lowe’s home improvement found that the difference between its highest and lowest engaged stores was more than $1 million in sales annually.
For daily tips, insights and inspiration follow me on my Blog at: terrymckenna.typepad.com.