The rise of “big data” has shown that there is value in diving deep into analytics to find ways to improve a business. For those that have yet to experiment with it, however, big data may still seem like an intimidating prospect.
Bernard Marr, author of Data Strategy, points out in a story for Forbes that businesses already generate a large amount of data. What they do with it is the key:
“If the business has a website, a social media presence, accepts credit cards etc., even a one-person shop has data it can collect on its customers, its user experience, web traffic, and more. This means companies of all sizes need a strategy for big data and a plan of how to collect, use, and protect it.”
How valuable is all this data? Tom Groenfeldt writes about the Economist Intelligence Unit report with Teradata in a story for Forbes. The report shows high marks: “Data-driven companies are more likely to outperform their competitors when it comes to profitability (59 percent vs 40 percent for companies with low reliance on data). They are more likely to have a culture of creativity and innovation, 63 percent vs. 37 percent for companies with low reliance on data.”
Here’s a look at how CEOs can integrate big data into their businesses, and some of the benefits that it can bring.
As with so many aspects of a business, the vision from the leadership is hugely influential. A CEO will need to clearly explain the reasons and motivations for bringing a new emphasis, and help to guide employees through it. In a story for Tech Republic, John Weathington writes that the CEO “must establish a vision of where the company is going,” and include how big data plays a part in it.
“If the CEO ignores or downplays big data in the company’s vision, adoption will be difficult, and it will be hard to keep employees motivated about a big data project,” he explains. “Motivation and inspiration is key as employees work their way to a more analytic future.”
Changes, especially major ones, can be difficult for longtime employees. Add the phrase “big data” into the equation, and that may contribute to uncomfortable moments. As Weathington writes, how the CEO handles these moments can help the transition.
“People who are comfortable trusting their instincts will be asked to trust their data instead,” he writes. “People who are accustomed to taking immediate action will be asked to run numbers first. It’s important for the CEO to keep the workforce motivated as they make the transition; this involves listening to their concerns, and spending a lot of time explaining why the company is taking a more analytic position.”
What data is the right data?
A mountain of numbers may be eye-opening, but the value of that information can be hit and miss. The figures that connect directly to the needs and buying habits of customers should be a primary focus. Phani Nagarjuna writes about this for CEO.com, advising business leaders to avoid “meaningless data.”
“It’s increasingly important to get beyond the ‘gather everything and sort it out later’ approach to big data, and instead track and capture the consumer-generated data that provides a direct value to your company. Look for correlation between customer characteristics and buying behavior to see how your customers interact with your products and services, and make a list of the big data analytics that will matter to your bottom line. Then work with your marketing and sales department to make sure that every metric you plan to capture represents accessible and actionable information.”
Data that helps to guide a business’ sales efforts may be top of mind, but the information can play a role in making improvements in internal processes as well. CEOs naturally put a premium on businesses running smarter, so big data can be worth exploring. Marr includes this in his Forbes story.
“From using sensors to track machine performance, to optimizing delivery routes, to better tracking employee performance and even recruiting top talent, big data has the potential to improve internal efficiency and operations for almost any type of business and in many different departments,” he says.
Smart data, smart solutions
Getting down to the crucial information is a key step in working with data. Jeremy Goldman takes it a step further in a story for Inc.com, calling for “smart data” over big data: “When companies are able to connect their institutional knowledge to the right data, great things will happen.”
An example: Goldman writes that the hotel chain Red Roof Inn examined flight cancellation data that determined the number of people who were stranded at airports in the United States each day. Then it learned how to track these delays and cancellations, to then target advertisements to people that could be in need of a place to stay.
“The campaign has resulted in some 10 percent growth year-over-year for Red Roof Inn,” Goldman writes. “… Other hotel chains had access to the same information as Red Roof Inn, but were unable to see how they could repurpose that information to help their businesses. In other words, the data that will drive growth for your company is out there — you just have to find a way to sift the gold from the silt.”
Few things can rival the importance of customer satisfaction, and big data, along with social media, can play a role in enhancing efforts to achieve it. Ryan Holmes writes about this in a story for Inc.com, describing a PR battle faced by Domino’s Pizza after an employee showed poor hygiene on a YouTube video, which then went viral. The pizza chain went beyond damage-control mode: Recipes were changed; money-back guarantees were introduced. Perhaps most importantly, the company analyzed social media to gauge public opinion, Holmes writes: “In the end, this multimillion-dollar ‘mea culpa’ was a dramatic success. Sales in U.S. locations increased 14 percent in the quarter after the campaign and share price rocketed 75 percent the following year. Today, this kind of nuanced sentiment tracking can be accomplished instantly. Social analytics software — which automatically scans the text of thousands of messages to reveal share of positive, negative, and neutral sentiment — can give companies a real-time window into how consumers feel about their product, their brand, competitors, or any combination of keywords. By monitoring search terms over time, brands can see how opinion evolves in response to events inside and outside the company and shift strategy accordingly.”
CEOs may find it difficult to get everyone on board the big-data movement. Employees may wonder how it affects their own value to the company, and show resistance to how their jobs change. Though the dynamics may be tricky, there are ways to navigate them. In a story for Harvard Business Review, Chris McShea, Dan Oakley and Chris Mazzei examine several ways for businesses to get over this initial discomfort.
- Select the right leader: The person leading the charge in bringing big data into the business will obviously play a huge role in how the company accepts it. Technical skills are a part of that role, but so should a strong desire to work as a team and to continually look forward, the authors write: “… The CEO should choose an analytics leader with three distinct qualities: (1) an ability to collaborate, have his or her ideas shaped by others and to champion the ideas of others; (2) an understanding of how the enterprise currently operates and a vision for how analytics could drive the company to a brighter, perhaps radically different, future; and (3) the hunger to create an environment of discovery, where the data is allowed to shape the future of the company.”
- Embrace innovation: There’s a lot that goes into changing “the way we’ve always done it,” and big data can be a challenge for those with that way of thinking. “High-achieving executives have been shaped by the pivotal experiences of their careers, yet analytics requires executives to think beyond these mental models,” the authors write. “The CEO must identify rigid modes of decision making among leaders, make it clear that the analytics era demands a new way of thinking, both individually and collectively, and guide them to that light.”
- Learn how to be nimble: The nature of big data can also create the need to make swift analysis and decisions. This is another area that may cause discomfort, thanks to “silos, incentives, and legacy behavior,” according the authors. “Successful analytics programs require a type of learning that few organizations are innately capable of. Analytics can enable breakthrough innovations but only if the environment supports open discovery and experimentation. If the analytics effort is anchored to traditional learning processes, it will not move fast enough to achieve meaningful change and competitive advantage.”