Six Tips to Prevent Big Data From Bogging You Down

Customer Experience
Customer Experience
Big Data is giving organizations the ability to acquire a lot of actionable insights. But with so much data in hand, some companies are overwhelmed. Experts share six tips to stop the Big Data overload.

It is no secret that the amount of data is growing exponentially. According to EMC, the digital universe is going to grow to more than 40,000 exabytes by 2020. The number alone is intimidating. Making the most of data can be even more daunting.

As Jeff Winsper, president of Black Ink, notes, "organizations of all sizes are drowning in data." For years, companies have made it a point to collect as much data as possible. With so much information at hand, many are feeling overwhelmed and unsure what the next steps need to be to make the most out of the data they already have as well as what to collect next.

One major problem lies with the fact that the hype around Big Data has caused organizations to shift their focus from analysis to collection, explains Wilson Raj, global customer intelligence director at SAS. But as Raj notes, "It's not just about the volume of data captured." What's more important is what organizations do with this data and how they're using it to help them achieve their business goals. In fact, in a recent article, Forbes described Big Data as "the killer technology of our time." Having the right data and using it to extract actionable insights has become one of the most important achievements for organizations.

Experts share a number of steps that companies need to take so they don't get bogged down by Big Data.

  1. Take inventory of your data: Brands tend to make the mistake of just collecting data without stopping to take inventory of what they have and how this information can help them improve their business. "They just collect data and just hope that something will come out of it," says Hal Bloom, vice president of research at Sage. This becomes even more complicated when data is dispersed across different departments that are operating in silos and not sharing information with each other. A clear view into the data that's available will also help better understand the strengths of each piece of data, explains Jerry Jao, CEO and co-founder of Retention Science. Dan Darnell, vice president of product marketing at Baynote, recommends starting with the data you already have before hunting for new sources. As Dario Priolo, chief strategy officer for Richardson, notes, one challenge that organizations face is not having good quality data. "You need real-time quality control," he stresses. Unless organizations have quality data in hand, they will have to go back to carry out major clean-up operations, slowing them down and stopping them from achieving their goals.
  2. Determine your goal: One of the first steps that organizations need to take is to decide what they want to get out of their data. What's the business goal or the question they need data to answer? "Think about the desired outcome," stresses Kurt Andersen, executive vice president of sales enablement and marketing at SAVO. Darren Vengroff, chief scientist at RichRelevance, agrees. "Rather than look at the data and try to find out what you need to do with it, come up with your objective." This direction will then allow business leaders to determine what insights they need to achieve that goal or answer that question, explains Raj. "Keep a crystal clear focus on your goals and how you want to use the data," stresses Graeme Grant, president and COO of CQuotient. "A razor-sharp focus on the end game is critical or else you can easily become overwhelmed or distracted by data," he notes. Keeping the goal in mind will also help companies be in a better position to understand what other data they need and should start collecting. "Look at the data you have to see whether what you need is available or if there are any missing holes that need to be filled," advises Raj.
  3. Prioritize your issues: At the point when organizations have determined their goals and know what data they have available, they can create a priority list outlining where they should start. "Concentrate on issues that have the highest priority for your enterprise," stresses Daniel Ziv, Verint's vice president for voice of the customer analytics. This is especially important for organizations with limited resources which might otherwise get lost working on different projects that never get finished. "After a proven win, move on to the next challenge," Ziv says.
  4. Create a virtual database: While having a centralized repository of data is a good practice, many organizations struggle to bring data from every part of the company in a central database. This means that they won't have visibility into all data. SAS' Raj says a solution would be to use data federation, a layer of virtualization which aggregates data from disparate repositories within a virtual database. This solution solves the problem of having to create a central repository, which can take time, especially if certain departments are reluctant to share their data. Raj explains that this system can help create a single customer profile while at the same time making sure that departments don't get access to data they don't need, for example a customer's social security or banking details.
  5. Invest in data scientists: Having data is not enough. A common issue that's afflicting companies is insufficient planning. Organizations are using data to uncover problems within their firms without first making sure they have the resources to find a resolution, notes Matt McConnell, CEO of Intradiem. Organizations need the right people to analyze the data, extract the right insights from it, and then act on it. However, Don MacLennan, cofounder and CEO of Bluenose Analytics, notes that many times analysts spend precious time organizing the data rather than exploring it. "Don't waste data scientists' talents with mundane activities. Instead let them take care of the more complex analytics projects," he stresses.
  6. Get down to action: Jeff Nicholson, vice president of marketing at Provenir, stresses the need to act on data rather than sit on it. "The key to achieving business value is to actually apply that insight to affect a desired outcome, ideally in real time," he notes. "The core to your successful strategy will be finding the right balance of technology and human interaction." In order to take action, data insights need to be shared within the rest of the organization. Elissa Fink, CMO at Tableau, recommends using graphics and charts to help the rest of the organization grasp the meaning in one glance.

Finally, organizations need to make sure that data projects are backed by the C-suite which understands their value and is willing to invest in specialized teams. "Find an executive sponsor," stresses Verint's Ziv. "Make sure there's somebody senior who will help drive the success of the project."