Business analytics: two simple words that can cause a host of negative effects — elevated heart rate, paleness, sweating, fatigue, and severe anxiety. Whether in the form of data collected through in-house means, or via cloud-based software, this practice, intended to streamline a number of goals within company training and beyond, can be a major stress-inducer. In this quick guide, we’ll explore some fundamental questions that will hopefully lower the veil on and pique your curiosity towards this timely topic!
What Are Your Goals and How Can You Measure Them?
Are you just collecting data for fun? There are certainly worse habits a person could acquire, but this information won’t be terribly helpful to you or your organization if you don’t know what you are collecting it for.
Piyanka Jain, president and CEO of analytics consulting firm Aryng, says “the right answer comes from what the organization is trying to do, and the right metric is associated with the objective that you’re training people for.”
Big Data can serve an unlimited number of functions across your business, from optimizing department productivity to alleviating HR strain. To reap these benefits, it is essential to isolate data-driven goals and create a sustainable means of measuring them. This two-step process must precede any data collection or analysis.
Jain mentions, for example, if a company is looking to optimize its project management training, some tangible goals for it might be:
-increasing monthly average projects completed
-decreasing percentage of missed deadlines
From there, these objectives break down into metrics
-The number of projects completed per month
-The number of projects with missed deadlines/total number of projects (measured monthly)
It’s great if you already have this approach in place, but before you begin bouncing Google Docs around, there is another checkpoint you must clear. J.P. Medved, content editor at Capterra, a company that connects buyers and vendors of business software, says, “your goals should follow the SMART criteria— measurable is a key component of the process.” Medved stresses that companies need to pursue metrics that answer the question “did we accomplish this goal.”
“You want to have something testable like, ‘be able to test employees the month after the training and have them get a passing score on the new process,’” he adds.
Who Can Analyze Your Data and Where Should They Begin?
There are many different perspectives concerning best practices for analyzing business data, and even more for assigning talent to this role. For the most part, however, our experts agree that a reasonably intelligent and organized individual with an analytical mind will most often get the job done.
In her book, Behind Every Good Decision, Jain explores five essential traits of a strong analyst and how anyone can analyze data to find actionable insights:
Analytics Aptitude: This isn’t necessarily something that can be taught, but is more often the way a person is wired. You can take this test to assess your competency.
Curiosity: Analysts need to be curious people —“know-it-alls” often make for terrible analysts.
Focus and Motivation by Impact: People in these roles cannot lose sight of what their goals are or allow themselves to get bogged down by minutia.
Structured Problem-Solving: Associates should be able to think through a problem, plan for it, execute it, analyze it, and then place it into the context of their central goals.
Hypothesis-Driven Personality: The most important attribute for an analyst. Jain finds this trait especially important to analytics leadership roles, and elaborates, “You can’t dive into the ocean of data and expect to find an answer—you’ll just be lost and you won’t find insights. If you’re strategic and you identify five [in advance] you’re most likely to find them through your hypothesis-driven approach, then you’re more likely to find your gold.”
Andrew Edwards, digital marketing executive at efectyv and consistent columnist at ClickZ, cautions companies not to take these important characteristics for granted, especially on the hard analytics end.
“It pays to know something about statistics and many marketers really don’t know anything about statistics at all, so they end up getting hung up in minutia and mistakenly believe that they’re looking for exact matches between certain numbers, expecting one measure to be very correlative to the next. You have to be able to fall back on trend watching,” he says.
What Kind of Process Do You Need in Place to Have Success With Business Analytics?
Three factors are necessary to executing sustainable and productive business analytics strategies:
Ease of Use
Jain puts it simply: “The easier you make these processes, the more likely they are to be used by people.” Convenience wins the day. While there are a lot of great software options available, much of the data you need for improving customer service, saving money on programs, or streamlining HR can be housed and analyzed in free, simple-to-use platforms like Google Documents and Sheets. No one particularly likes entering data, but it is necessary, so working with your team to create a simple and user-friendly process for compiling it is paramount.
Medved expands on this point; “collecting the data is the biggest thing—there are a lot of organizations that do training and are trying to affect outcomes but they’re not entering the inputs. All the work on training is front-loaded with needs analysis and setting up goals and measurements because it’s very important to know your baseline and see if things are actually changing.”
Going hand-in-hand with the last point, creating an environment where your team is held accountable for entering data in a timely and accurate fashion is necessary to the success any analytics initiative.
Jain says, “You need to think about how to incentivize people to enter information correctly. If you’re not giving them time to input information correctly and you’re not holding them accountable, then obviously they’ll just go with the first thing that comes in—they’re not necessarily motivated to enter it correctly or enter all of the information.”
Finally, Medved stresses the big picture importance of regular testing in the training that results from data and insights. “A lot of people recommend doing skills testing periodically after training because a lot of times you’ll get skills decay and require a refresher course for people to strengthen retention of material,” he says.