Finding the “Why” in Big Data
How data analytics is the key to better business practices with the customer at the center
You might have seen the inspirational TED Talk, “Start with Why.” Listing out different spheres within the golden circle, Simon Sinek outlines his thoughts on how leaders can flip the script. He asserts that in order for companies to define themselves by purpose, they have to start with answering the “why”.
“How we are led to this purpose,” he says, “is by starting with the question, ‘Why do we do what we do?’”
Starting with “the why” is no easy task. Yet discovering how to lead a company with intention stems from answering this foundational question.
This is why reminders like Sinek’s TED Talk are so popular. We may mean well, but how do we incorporate “the why” into day-to-day work life? How can employees be inspired to live out a company’s value? Does the “why” ever evolve?
Incorporating data analytics into business best practices is one way to take the necessary steps toward finding – or, at least, affirming – your “why”. At its very foundation, data analytics requires the human discipline of asking why something has business value, why a certain behavior resulted in a different outcome, why specific trends should take priority when analyzing data at large. Through questioning and analysis, a customer-centric company can be built from the ground up.
Big data creates an opportunity and a challenge for modern business. It’s larger than life and can be used in a myriad of ways. The key to tapping into its potential is determining how to shape it to extract the biggest benefit, and in turn building your business around the data itself.
Judgment enables businesses to harness actionable intelligence; reflective managers at the helm prioritize certain insights, developing best practices out of big data to drive new business standards, encourage better customer service, acknowledge star performers and develop sustainable efficiency that translates into better business.
What can you gain once this foundation is established? Here are just a few examples of ways companies can find the promise of better business with big data, driven by the desire to better serve customers. Because after all, they’re at the center of everything we do.
- Discovering what matters most to customers. Doing so requires approaching customer interactions as less transactional and more relational. But let’s face it, the discovery phase of data analytics can be overwhelming. It’s helpful to assess macro trends with large data sets, but also spend time looking at smaller subsets of customer groups, down to the 1:1 relationship with a specific customer. This can be manually intensive work. It’s important to have tools to help streamline this process so that your analysts aren’t consumed by data and cross-referencing for data quality. Visualization helps make this journey easier, too. Data analytics is a form of storytelling, and patterns affecting a customer journey should be compelling with visuals to support hard figures.
- Remembering that data begets more data. It takes a village when making big data work in the modern workplace. Teams must own different aspects of data analysis, so that the data available can be interpreted for best use. So you have 10 glowing reviews or a handful of customer critiques? That data should not be left alone. What else supports these claims? What can be correlated or inferred? When patterns arise, it’s up to the team to decide the implications of different pieces of data. Those insights are then supported by a business structure to share that knowledge with relevant teams, management, and leadership.
- Looking inward to analyze employee behavior. Who are your star sales and customer support performers? What can be gleaned from their communications patterns? Every interaction matters, especially when customers have a plethora of choices in today’s market. Managers should take the time to regularly analyze their teams’ behaviors so that interactions are rooted in data. From there, employees can take to customer-generated data to see if internal team activity is resulting in improved customer experience.
- Supporting sales to customize experiences. Remember the last time you looked down and saw “unknown number” on your caller ID? Instantly, you’re ambivalent about the conversation; often, you’ll screen these calls to prevent an awkward, impersonal, or even misdirected call. For salespeople to be successful, they need information to tailor dialogue to meet a customer’s needs. Guess what? There’s technology for that; technology that helps humanize every customer on the other line, making interactions more meaningful and less wasteful, as well.
- Empowering end users to provide feedback. What is the point of having big data at your fingertips if you can’t use it to hear from the customer directly? Feedback is a crucial component of any data analytics strategy, and finding opportunities to deliver intuitive feedback mechanisms for customers should be high priority for businesses in the digital world. Whether over the phone, online or via social channels, make sure customers have a direct line to you so that there is transparency and a two-way dialogue at every turn.
Companies that take to heart the value behind “finding the why” will turn to big data and inspire employees to do so as well. By doing this, they’ll find themselves best equipped to tackle the demands of the modern customer. Though the tactics may differ based on specific requests, having the right foundation will make pursuits in big data more actionable and more rewarding, strengthening your business and creating a more loyal customer base in the process.