The cost of collecting and storing data is plummeting. Large scale data storage technology has fallen nearly 28 percent annually since 2002, according to the Federal Reserve.
Large businesses have responded by collecting mind-boggling amounts of data about their customers and operations. This data—if used properly—may provide valuable insights to increasing sales and running operations more efficiently. Small businesses might start doing the same. Capturing and analyzing data about your business may be one of the most important decisions you can make to compete and succeed.
Before talking about how to analyze your business, let’s agree on the definitions to use. These are popular definitions of key terms, but keep in mind that different companies and experts may define them somewhat differently.
Big Data. Big data refers to the massive amounts of information that businesses generate. Industry analyst Doug Laney characterizes it as the “Volume, Velocity and Variety” of data available.
Business Intelligence. Business intelligence refers to the tools and techniques available to analyze big data and convert it into meaningful and useful information. Many times, BI refers to historical information that is processed to identify lessons that can be applied toward the future.
Analytics. Analytics refers to tools, processes and methods to identify important patterns in data. Sometimes this is used interchangeably with business intelligence. Other times it refers specifically to the analysis of current and active data as opposed to historical data.
Key Performance Indicators. Key performance indicators (KPIs) are specific metrics or ratios calculated from big data that provide insight into a specific component of your business. They are the end result of using big data, business intelligence and analytics. KPIs can be broken down into customer-centric and operations-centric.
Customer-centric KPIs usually involve transactions with data captured by point of sale systems and traffic counting systems. Operations-centric KPIs usually deal with elements of your business that don't directly touch the customer, like inventory management.
Before you start working with KPIs, consider these suggestions:
Take a focused approach. Analysis paralysis can be a common problem for first time users of big data. There's so much information, which can lead to hundreds or even thousands of opportunities to improve your business, that some may get stuck not knowing where to start. That’s why it may be best to take a focused approach. Select one specific KPI to improve. An example might be conversion rate during weekends. Focus on ways to convert more browsers into buyers for Saturday and Sunday. By making it specific, you can measure results clearly and conduct experiments to determine if your ideas work.
User experience is key. There are many software solutions available that produce KPIs. It may prove critical to choose a user-friendly system appropriate for the scale of your business. If you need a data scientist to interpret the charts and graphs developed by a certain software solution, this solution probably isn’t for you (unless you happen to be a data scientist). Owners and employees both need to feel comfortable reading and interpreting the data presented. If not, the KPIs may quickly be ignored.
Provide incentives to employees. The purpose of using KPIs is to identify opportunities for change. That implies employees must go through with the changes for the company to benefit. Providing them with incentives tied to KPIs may improve the chances that they will follow through on the recommendations.
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A version of this article was originally published on October 30, 2015.