Enterprises like to talk about data, but what you may not hear as often is how they are actually exploiting the data they collect. According to a report entitled "How organizations can unlock value and insight from the information they hold," from Pricewaterhouse Coopers (PwC) and Iron Mountain, companies have a lot of progress to make before they start making better use of the data.\n\nThe study surveyed 1,800 senior business leaders in North America and Europe at mid-sized companies with more than 250 employees and enterprise-level organizations with over 2,500 employees. And the results were surprising, -- only a small percentage of companies reported effective data management practices. \n\n"Data is the lifeblood of the digital economy, it can give insight, inform decisions and deepen relationships," according to Richard Petley, director of PwC Risk and Assurance. "It can be bought, sold, shared and even stolen -- all things that suggest that data has value. Yet when we conducted our research very few organizations can attribute a value and, more concerning, many do not yet have the capabilities we would expect to manage, protect and extract that value."\n\nBusinesses lack data strategies\n\nThe study found that while 75 percent of business leaders from companies of all sizes, locations and sectors feel they're "making the most of their information assets," in reality, only 4 percent are set up for success. Overall, 43 percent of companies surveyed "obtain little tangible benefit from their information," while 23 percent "derive no benefit whatsoever," according to the study.\n\nThat means three quarters of organizations surveyed lack the skills and technology to use their data to gain an edge on competitors. Even further, three out of four companies haven't employed a data analyst, and out of companies that do, only one quarter are using these employees competently, according to the survey.\n \nIt's not just a problem for tech companies. This lack of data understanding spans across manufacturing and engineering, pharmaceuticals, financial services, legal services, insurance, energy and healthcare. Using the data, PwC was able to create what it calls an Information Value Index, which measures how well businesses use the information they collect and how much value they derive from data. \n\nDerived from a sample of 1,650 businesses that responded to 36 survey questions, the Information Value Index gives businesses a score from 0 to 100, with 100 being the best use of data possible. This index evaluates a company's general awareness and understanding of the importance of data, how aligned the company is with data driven goals, the skills and tools used to gain value from data and overall benefits the company has gained from tapping into data. Mid-market companies earned an average score of 48.8, while enterprise businesses earned an average score of 52.6; combined, the overall score for all companies surveyed came in a just over 50. \n\nPetley concludes that "data is so pervasive that it is taken for granted or is seen as a by-product. Often it is only when disaster strikes that this assumption is broken." Alternatively, some companies see data as the responsibility of IT and data architects, rather than an important resource that should be employed across the company. And that's an important shift to make; the idea that data isn't just a problem for IT, but rather a valuable asset that reaches far beyond the technical side of the business. \n\n[ Related Story: 5 tips for working with data science interns ]\n\nGaining a competitive edge with data\n\nData strategy is the biggest resource in gaining a competitive edge against other companies, according to the study. By ignoring data or treating it as unimportant, business leaders do their companies a huge disservice when it comes to staying ahead of the game. \n\n"The essence of analytics is for business units, marketing, emerging business offices, etc. to determine what they want to learn from the data and then use the records information management team, IT, data analysts and scientists to identify data sources, understand access controls, execute the analysis, and deliver the results in a user friendly, typically visual, mode," says Sue Trombley, managing Ddirector of Thought Leadership at Iron Mountain.\n\nBusinesses might be investing significant money into data capture, but then drop the ball when it comes time to actually use that data. Instead, business leaders need to focus on figuring out how to take the data and boil it down into easily digestible formats for internal use. It's all about "having a strategy for data management," says Trombley. The first step, he says, is to identify data sources, then understand the importance of analytics to every department and, finally, create a plan to stay competitive. \n\nAnd the data suggests businesses aren't aware of the untapped resource they have in stored data. The study found that 16 percent of business leaders reported that they didn't believe their organizations knew what data it had, 23 percent said they didn't know how data transferred through their businesses or where it could be used best, and 20 percent didn't know where their data was most vulnerable. \n\nNot surprisingly, Trombley says that a quarter of C-suite executives report not seeing any value from data around decision-making, product development, cost savings or customer acquisition and retention. But that's because they simply haven't invested in a strategy. Analytics is quickly becoming one of the most valuable resources to a successful business, and every company will need a unique and tailored plan for managing data.\n\nShould your company hire a data scientist?\n\nBefore rushing to hire a data scientist or building an entire department dedicated to analytics, business leaders need to first sit down and figure out what they want to achieve with analytics, according to Trombley. Every company's needs are different and the best data strategy will depend on the overall mission and goals of the business. That means, your business might not necessarily need an entire department dedicated to data and instead tap into the skillsets of your current employees. \n\n"Companies with less sophisticated analytics requirements may be able to fill the skills gap using existing employees by sending them to focused training sessions such as data analytics boot camps [and] night courses," says Trombley.\n\nFor some companies, this might be the best option, considering there is currently a lack of capable data scientists since it is a relatively new and fast growing position. Simply getting an employee up to speed can help lessen the impact of a lacking data strategy, but it still might not be enough.\n\n[ Related Story: 4 traits good data scientists share ]\n\n"There is no one-size-fits-all regarding the CDO [Chief Digital Officer] position," Trombley says. "Whether they exist or not the basic responsibilities attributed to the role need to be assigned to one or more individuals in the current organizational structure. Also, there is the supply and demand dilemma -- not enough talent available to fill the CDO position in all organizations."\n\nCharacteristics of the 'data elite'\n\nOf the businesses surveyed, only 4 percent were classified as "data elite," with a typical business profile of medium or very large businesses within healthcare and manufacturing and engineering. These businesses, according to the study, first and foremost had a well-established "information governance oversight body." Furthermore, these businesses had fostered a "strong culture of evidence-based decision making," appointed analysts that can access data, had strong control over their data and had extensive analysis tools in place. \n\nThese progressive companies have tapped into the most valuable resource available to them and made it part of the company culture. Some of the most agile mid-market businesses are found in this category, which the study suggests is because they aren't bogged down by legacy and are in industries that are less regulated than others. However, less agile enterprises businesses are also found in the data elite, thanks to strong leadership, global information governance arrangements and relevant departments outside of IT in the data functions.