The Fundamentals of a Data-Driven Approach

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data-driven approach

Organizations with a data-driven approach cultivate a culture that uses data and business insights to drive all company decisions. A data-driven organization encourages all stakeholders to base everyday business activities on data and insights instead of relying on their gut. In this data-focused business environment, data analysts safely serve as the “eyes” of the business, working collaboratively with others to drive strategy. According to a recent research paper, “data-driven organizations are 162% more likely to significantly surpass revenue goals than their laggard counterparts.”

When organizations continuously gather, monitor, and analyze data to develop their businesses, they make intelligent decisions – leading to greater growth and efficient strategies. Data helps organizations do a better job by actively highlighting areas of improvement and providing insights that reinforce decisions. 

As data keeps piling up, organizations will be more eager to adopt data analytics, data privacy, and data security solutions. Value-added data can only emerge when ordinary business users, who are domain experts, start taking advantage of self-service analytics platforms and collaboration tools.  

9 Barriers to Becoming Data-Driven

Most companies still struggle to take a data-driven approach, while business leaders continue to make decisions based on gut feelings rather than data. The truth is that some organizations lack leadership teams who establish an expectation that decisions should be made around data-driven evidence. 

So, what are the real-world challenges faced by businesses attempting to implement a data-driven approach today? They include: 

  • The inability of a legacy system to work with “live data” to derive insights makes it difficult to identify relevant data points used for decision-making. Companies that still use manual analytics techniques on legacy systems cannot reap the benefits of real-time, actionable insights that can guide decisions on demand. 
  • Organizations using traditional Data Management approaches are stuck with outdated data integration processes. Finding Data Management systems with full integration capability is way beyond the financial strength of mid-sized or smaller businesses. One solution to this problem is investing in automated processes and a centralized Data Management system. With this approach, the time is substantially reduced to explore and locate where decisions are made. 
  • Though currently in focus, addressing the lack of data skills still has a long way to go. Data literacy issues have to be universally embraced for businesses to become data-driven. To transform into a data-driven organization, the business leaders must encourage ordinary employees to use data for every business decision.  
  • Availability and accessibility of enterprise data is still a nagging concern. Enterprise data must be available and accessible across business units and departments and, in ideal situations, the employees get a “single view” of data across processes and systems. Data access problems can be quickly minimized through a solid network of data technologies, processes, and personnel. To confront this challenge, everyone within an organization should understand why decisions are being made using data, and how the data is being used to inform those decisions. 
  • Absence of a safe data environment can impede data-powered cultures. Most important, IT and BI teams can work toward building the foundation for an enterprise-wide data culture by developing strong Data Stewardship practices. 
  • Isolated data teams. The data powerhouses – data centers and their data scientists – are often far removed from the business corridors, which creates miscommunication and lack of understanding between the different operating teams and executives. Aligning leadership and teams around data is key to succeeding with a data-driven approach. 
  • Absence of a data leadership role with accountability. To unlock opportunities for growth and innovation through data, the chief data officer (CDO) is becoming increasingly important for organizations around the world. The CDO role can make significant strides in making an organization data-driven. The best way to combat this problem is to begin the “data-first” movement in higher levels of a company.
  • Organizations that lack sufficient visualization platforms will wrestle with data comprehension challenges, which may hamper strategic planning. Corporate dashboards are one way to facilitate quick data access among executive team members, who usually lack sufficient time and skill to perform data analysis on their own. 

What Organizations Need for a Data-Driven Approach 

Policy-wise, some steps can help an organization become more data-driven:

  • Establishing a true data-driven culture means that each individual, regardless of background or job role, needs to be empowered to make decisions with data. Companies with data-driven cultures use well-managed data to inform their decisions and to drive changes to how businesses work, instead of acting based on assumptions or traditions.
  • Forward-looking companies are tolerant of questions – even disagreements – about corporate decisions, so long as those questions are grounded in the data and its analysis. 
  • Organizations aspiring to build successful data cultures hire people with the right data skills and expertise, but also empower business employees to develop their analytics skills through training and other activities. 
  • While many businesses may not have the financial resources to hire an entire room of data scientists, they can identify existing employees who are curious, well-aware of the organization’s overall mission, and passionate about data. These identified employees can then motivate the others in a data team to build and continuously improve tools that ordinary business users can use to make daily decisions. 

The Data-Driven Approach: In Review

Data is undoubtedly emerging as a key enterprise resource, but its real value depends on its use in making strategic business decisions. Without the proper data sets, data analytics tools, and data scientists supporting a company, the challenges of managing data can prove to be insurmountable. 

With lack of skills and knowledge, and ineffective or inefficient business processes, companies may spend countless hours trying to rationalize contradictory data, differing metrics, and preferred programming languages. 

Collibra’s IDC research suggests that the most data-mature organizations are three times more likely to adopt the following practices than less-mature organizations:

  • Clearly delineate roles and responsibilities around data and analytics 
  • Adopt a holistic data-intelligence approach
  • Consistently expect that data intelligence will guide decisions
  • Continuously measure outcomes 

Data culture is not a matter of technology: Without an effective data culture, the introduction of new technologies, such as an enterprise-wide, self-service data portal, is likely to be unsuccessful. It is important that leaders demonstrate that making decisions using data is worth it, even when mistakes are made along the way. 

With technological advances in data analytics, it is becoming increasingly feasible for companies of any size, in any sector, to overcome the challenges mentioned earlier and take a data-driven approach. Leveraging data and analytics to efficiently lead businesses has just as much to do with culture, processes, and workflows as it does with analytics platforms and analysts. Organizations that use data for advanced, precise decision-making are competitive in today’s digitally driven world.

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