As technologists, analysts and marketers, we have plenty of data and for the most part we already have the data we need. The problem is that we’re not very good at analyzing this data and reporting on the insights, trends and best next actions. In short, the business value is not yet rising up from the abundance of data.
While “Big data” has made many of the lists of most important business issues in 2013, a survey conducted by Pitney Bowes Software found that 80 percent of senior executives report that their organization struggles to get value out of their data.
Technology research firm Gartner has increased its forecast for worldwide IT spending in 2013 to $3.7 trillion.1 According to the DMA, global advertising expenditures will grow 4.7% to $480 billion in 2012. Both spending projections will be largely driven by Big Data initiatives, but if executives cannot glean real business value from this data, how can they ensure this spending will be allocated properly?
Organizational Challenges
There are myriad issues for why organizations struggle to obtain business insight from Big Data, and it will be a critical task for executives to tackle these challenges head on in 2013. For one thing, there is huge variation in what is considered Big Data across companies and consequently, there are a number of different departments interacting with a company’s data. As underscored by Pitney Bowes’ survey, there is no corporate consensus about who owns data management and therefore the expectations of how to govern and analyze an organization’s data are widely different across companies, but also within an individual company.
The absence of people skills becomes particularly important when examining what is the biggest factor holding Big Data insight back
Because senior level executives and managers on the ground interact with big data differently, they also experience different challenges with data. Whereas lower-level managers have more challenges with the velocity, volume and variety of data, senior executives are challenged by extracting business value from Big Data. Having too much data and too few resources has consistently been a major challenge facing organizations; in fact, resource shortages and people skills contribute to over half of the challenges survey respondents report for extracting value from Big Data.
But the absence of people skills becomes particularly important when examining what is the biggest factor holding Big Data insight back. Thirty-eight percent of survey respondents reported that lack of analytics capabilities and skills is the biggest inhibitor to gaining business value from Big Data, and this sentiment shoots up to 70% among senior level executive respondents.
This insight is key as organizations turn the corner on Big Data because they will need to realign staffing goals to address these challenges. Smart organizations will take time to evaluate whether centralizing data, data management and/or data analytics will help deliver business value. Centralizing these processes and the teams that manage them makes it possible to develop best practices and consistent reporting across the enterprise, helping managers at every level gain business insight.
Furthermore, it will be important for organizations to staff these teams with not only enough people, but with people possessing the right skills. Organizations will need more than number crunchers to meet senior leadership’s high expectations and vision for Big Data. A new breed of analyst will be necessary to translate Big Data value to the C-Suite to inform solid business decisions.
Fortunately, organizations appear to recognize this need and looking ahead, staffing (full-time, part-time, and external staff) represents the majority of Big Data spending (52%). Hiring employees with a solid command of appropriate skills will be an important initiative, as will forecasting the future Big Data needs of the organization to identify skills that will be required, such as analyzing new and different types of data, to either train or hire people equipped with these skills.
Business Value
There is no clear-cut data type that will transform an organization over the short or long term. Currently organizations rely on traditional, structured forms of data for making their business decisions, and their success with types such as Customer Profile, Web, Partner or Supplier and Location data, makes it no coincidence that they are more optimistic about these types of data as short-term opportunities. The time is now to master and capitalize on Location data, as many organizations are confident with harnessing insights from this type of data and are backing it with significant effort and investment.
These non-traditional types of data will require investments in people and talent to make use of the data, as mentioned before, but also the right technology to assist them.
What presents the more challenging obstacle—and where key people, skills, tools and resources will need to be deployed—is with unstructured data, like Enterprise Dark data, Social Media and Mobile data. Organizations are least successful with unstructured data, yet these are all sources of data, particularly Enterprise Dark data and Social Media data, from which organizations are most keen to derive value. While few organizations profess mastery of unstructured non-traditional data types, survey respondents all rank these types high as short-term and long-term opportunities. Although organizations see opportunities in the immediate future, they are planning more for long-term growth from non-traditional data types. This is more an indication that organizations recognize the importance of these data sources over the long-term, yet are eager to master them quickly to gain competitive advantage.
These non-traditional types of data will require investments in people and talent to make use of the data, as mentioned before, but also the right technology to assist them. Investments in infrastructure, software and hardware should coincide with investments in supplementing Master Data Management with various analytics tools, increasing capacities of data warehouses, and investigating new and inexpensive technologies which can efficiently process big data and make use of Predictive Analytics.
The data organizations need is there—it now requires proper investments in empowered people and advanced tools to communicate its value and make it actionable.
Note:
1. Gartner, Inc., Forecast Alert: IT Spending, Worldwide, 4Q12 Update, John-David Lovelock, January 2, 2013.
