Big data and analytics are at the top of the corporate agenda. In fact, a recent EY survey  found that 80 percent of senior executives think that data should be at the heart of all decision-making. However, 50 percent of these executives identified adapting organizational culture to integrate with big data as a key challenge.

The human element of big data and analytics is probably the most critical factor in building a successful program, but it’s also the least understood. When people think of analytics, they often think of technology and data – and while the sophistication of technology is enabling the capability, the true value lies in the hands of the human beings interpreting and applying the analytics. In other words, analytics provides the greatest value when big data enables big judgment. However, that value will always be limited by how well team members are prepared to work in an analytics-driven business.

So where does an organization start? Leaders must first recognize that analytics skill sets must be developed in all of their people, not just the data analysts. For optimal results, leaders should think carefully about the particular mix of skills and talents needed – bringing together information technology, business and analytics capabilities. Broadly speaking, there are three principal roles that need to have a seat at the table for analytics to move forward efficiently and effectively (as also illustrated in the accompanying infographic):

  • Suits (consumers) – The domain and sector business specialists who have a strong understanding of the organization’s broader business goals and strategy. They use analytics to optimize their business by providing deeper insights and increased efficiencies. They tend to be less focused on the “how” of big data and more focused on the “why.”
  • Math whizzes (producers) – The analytics specialists who construct databases, develop analytics scripts / models and design visualizations and dashboards for analytics consumers. They tend to be more focused on crafting the solution using innovative techniques and advanced technology, but generally don’t have as deep of an understanding of the business problem as the suits.
  • Techies (enablers) – The architects, who create the infrastructure, configure and implement analytics software, and establish data standards and management procedures. They are focused on enabling the sustainable operation of analytics solutions at an enterprise level, and tend to spend limited time on the specific business analytics solutions.

An individual can possess some capabilities from each of these personas but they typically specialize in one. An individual that encompasses all three of these skill sets is very rare. In fact, they are called “unicorns” in the analytics world.

Companies should not strive to create individual “unicorns,” but rather focus on building cross-functional teams that can integrate their skills. This will produce better results and provide the ability to scale across the organization. Some key steps companies can do to achieve this include:

1)     Educating their people on the intersecting capabilities and cross-functional teaming

2)     Training their people on the core analytics skill sets relevant to their personas/roles

3)     Aligning diverse cross-functional teams with capabilities and experience across IT, analytics and the relevant business functions

Through repetition, interaction and experience, these steps will help change the way people think and operate-building analytics into their DNA.

To put this in practice, organizations should first anchor on a standard approach with the analytics value chain at its core.

In its simplest form, the analytics value chain consists of acquiring data, developing analytics, and delivering insights, all in context of a specific business issue. The coalescence of these steps requires collaboration across all of the analytics personas - something we call mission perfect teaming. 

This integrated approach is the key to asking the right business questions, using the right tools, and developing the insights that will maximize value for the business. By working toward a singular purpose, employees become more loyal, satisfied and engaged. In fact, an EY study shows that employees are 1.4 times more engaged, 1.7 times more satisfied and three times more likely to stay in that organization.

Deriving value from data doesn’t just happen; it needs focus on both the technology and the human element of an analytics program. In the fast-changing digital economy, understanding the different skills needed to deliver business insights is essential to big data enabling big judgment as part of a data-driven organization.

Chris Mazzei is Ernst & Young Global Analytics COE leader and global chief analytics officer, Ernst & Young LLP. Andrew J. Tanner is senior manager, Ernst & Young LLP. The views expressed herein are those of the author and do not necessarily reflect the views of Ernst & Young LLP.

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