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Power & Process of Data-Driven Organizations

Andrea Fryrear
7 min read

This is the third article in a series about data-driven executives and organizations. You may want to start by reading Part 1 on Data-Driven Strategy and Part 2 on Data-Driven Product Development.

Once data has worked its way into an organization’s strategic planning and product development roadmap, the benefits of spreading it to every corner of the business become clear.

Unfortunately, joining the ranks of the truly data-driven isn’t simply a matter of paying for the right software and forcibly rolling it out to every single department. Without an adoption plan and a long-term data management system, organizations run the risk of becoming data rich and information poor.

Simply collecting data isn’t enough. You also need a detailed, documented plan for how that data will impact each department’s activities.

In this final installment of our series on the data-driven business, we’ll take a look at how companies are succeeding in spreading the light of data to every department and employee.


Begin with the End in Mind

Before investing tens of thousands of dollars in software, systems, and new hires, managers and executives should first ask themselves why becoming data driven is important to the business.

In a recent McKinsey article, Dominic Barton and David Court point out that, “a clear vision of the desired business impact must shape the integrated approach to data sourcing, model building, and organizational transformation.”

Without this foundational understanding, executives can fall into the trap of starting out by asking what the data can do for them. This mindset can skew data collection, analysis, and action away from truly useful insight.

Focusing on our needs is tempting, however, because effectively using big data often requires thoughtful organizational change, which can be scary and difficult to handle.

But, as Barton and Court remind us, such change will ultimately be worth it:

“executives should concentrate on targeted efforts to source data, build models, and transform the organizational culture. Such efforts help maintain flexibility. That’s essential, since the information itself—along with the technology for managing and analyzing it—will continue to grow and change, yielding new opportunities.”


Laying the Foundation: A Four-Step Process

Changing organizational culture can be a massive undertaking, but there’s no need to try and conquer the whole overhaul at once. A thoughtful, step-by-step approach can achieve incremental improvement across the business without causing too much disruption.

The Harvard Business Review suggests these four steps:

  1. Improve the data: The decisions you make are only as good as the data they’re based on, so make sure your data are properly, clearly, and consistently defined across the organization. Take steps to improve data quality, while also promoting sharing across departmental lines. This isn’t an “IT only” project; it requires company-wide commitment.
  2. Build “data to discovery to dollars” processes: Once you have solid data coming in, it’s time to create processes that will allow you to put it to work across the organization. As HBR puts it, “Here we include processes to deliver more to customers; to repeatedly and forever seek hidden truths in data; and to seek out novel data and integrate them with existing data into a more potent whole.”
  3. Invest in people: There’s a serious shortage of qualified analytics professionals that your hiring team will need to tackle head on, but managers who are comfortable working in a truly data-driven environment may be just as hard to come by. The McKinsey report on Big Data suggests the U.S. alone faces a shortage of roughly ten analytically-competent managers for each deep analyst, which means most companies need to start by gathering a critical mass of these managers.
  4. Strive to empower all with data: Executives should lead by example, with the goal of shining the light of data into every nook and cranny of the organization. With this leadership in place, managers can show people how data make them more effective, and encourage experimentation. The transition may happen slowly, but over time data-driven employees will start making better, more confident decisions, seeking opportunities to improve their work, and engaging with others on larger, more complex issues.


Managing Data By Committee

Design by committee never turns out well, but when it comes to big data having a governing body who is responsible for its administration can actually help the organization use it more effectively.

The name of this group isn’t critical, but its makeup and function are.

In order to be effective, a governance group needs to include stakeholders from throughout the organization, as well as representatives from any agencies or third-party vendors who have a stake in the data that’s coming in or its function.

In his MarketingLand column, David Booth, a co-founder and Partner at Cardinal Path, suggests considering representatives from these areas of the business:

  • Web/Apps: Representation from website/app analysis, project management, content, customer/user experience, e-commerce, and other functional areas.
  • Business Intelligence: Representatives from traditional business intelligence, ad-hoc analysis, shared analytics and data services, data modeling, and operations groups.
  • Customer: Individuals from direct marketing, customer lifecycle management, customer loyalty, CRM, and consumer insights teams.
  • Digital Marketing: Key stakeholders that manage digital channels like search, display, social, programmatic, email, video, and often those involved with a data management platform (DMP).
  • Sales, Pricing, and Promotions: Sales leadership functions as well as those responsible for price and promotion decisions.
  • Strategic Planning: Perspective and guidance from organizational leadership with respect to strategic planning is often included to tie together initiatives across functional areas and support broader organizational goals.
  • Finance: One or more representatives from those producing and consuming the organization’s financial data.
  • Information Technology and Systems: Those responsible for the hardware and software required to support the larger data stack, but also extends beyond the “pipes” and includes acute knowledge of how business processes are integrated within those systems.
  • Agency/ Third Party: People from your digital, creative, & media agencies, vendor professional services resources, as well as data and analytics experts to bring industry insights and an outside perspective.

Most of the members of this group should be at a fairly senior level, which precludes the governance group from serving a tactical function. Instead, its role should be primarily strategic.

But, simply creating and maintaining this governing body can prevent different parts of the organization adopting the same (or competing) software, reducing costs for implementation, licenses, and training.

It’s also a ready-made site for discussing strategy and ensuring the data the organization has worked so hard to collect is being put to good use.


Start Your Journey Toward Data-Driven Innovation

The advantages to incorporating data throughout your organization, regardless of its size, are clear. “Data-driven managers, departments, and organizations have always enjoyed distinct advantages,” say Thomas C. Redman and David Walker. “The data-driven have crafted the best strategies, uncovered wholly new markets, and kept operational costs low.”

But the road to data is littered with obstacles, and without a roadmap it’s easy to lose your way.

Begin by clearly identifying your destination, laying a firm foundation, and creating a robust governing body, and you’ll be well on your way to driving decisions with data.

For an easy-to-use, secure data collection option that can scale across your organization, check out SurveyGizmo’s Team Edition.

Andrea Fryrear is the chief content officer for Fox Content, where she uses agile content marketing principles to drive content strategy and implementation for her clients. She also writes for and edits The Agile Marketer, a community of marketers on the front lines of the agile marketing transformation. She geeks out on all things agile and content on LinkedIn and Twitter

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