Role of Data and Analytics in Digital Transformation

Role of Data and Analytics in Digital Transformation

Authored by Douglas Laney, Distinguished VP Analyst, Gartner

Information as an asset is still in the "early adoption" phase, which makes it a competitive differentiator for leading organizations as they focus on digital transformation. In turn, data and analytics become strategic priorities.

Data and analytics are the key accelerant of an organization's digitization and transformation efforts. Yet today, fewer than 50% of documented corporate strategies mention data and analytics as fundamental components for delivering enterprise value.

Gartner predicts that this will change quickly. By 2022, 90% of corporate strategies will explicitly mention information as a critical enterprise asset and analytics as an essential competency.

A company's ability to compete in the emerging digital economy will require faster-paced, forward-looking decisions. Data and analytics leaders need to assert themselves into corporate strategic planning to ensure that data and analytics competencies are incorporated within the highest-level public-facing enterprise plans.

Amplify the data and analytics discussion

Make data and analytics strategies a routine boardroom discussion topic. Leading organizations in every industry are wielding data and analytics as competitive weapons, operational accelerants and innovation catalysts.

Still, many companies continue to struggle under the weight of traditional business models and analog business process that discount the potential of data and analytics. Others recognize their potential but cannot make the cultural shift or commit to the information management and advanced analytics skills and technology investments necessary to realize that potential.

Strategies to elevate enterprise value

As the role of the chief data officer (CDO) takes hold — gaining authority and influence on par with other executives — organizations will move away from merely using data as resource and analytics as reporting and decision-making support tools. Data and analytics will become the centerpiece of enterprise strategy, focus and investment.

Some recommendations aimed at building and elevating an organization's data and analytics competency within the organization are:

  • Collect and socialize examples of the internal and external economic benefits from data and analytics that your organization (or other similar organizations or industries) has generated.
  • Offer or insist on being involved in corporate strategic planning to ensure that data and analytics competencies are incorporated, if not already featured, within these plans. Communicate this information internally and publicly in annual reports, investor conferences, etc.
  • Measure and communicate the value of the organization's information assets to help shift the culture into believing and behaving as if information is an actual asset.
  • Build, buy and borrow advanced analytics competencies (such as data science or machine learning) beyond traditional business intelligence and embed them throughout the business.
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