How the cloud has moved advanced analytics from exclusive to accessible

By Henning Soller

Thanks to the evolution of cloud software, database technology has become a commodity. Where companies used to invest in software upgrades to enable advanced analytics, now access to quality data-related insights requires a minimum amount of hardware and computing power, which are becoming less and less expensive. This democratization should have ushered in the widespread adoption of advanced analytics technologies across industries. Certainly, digital natives were quick to embrace them, but many traditional companies still haven’t taken advantage of the insights they can provide.

A few key issues have impeded progress. Database technologies can create added complexity in setup, interface, and visualization. In addition, many executives don’t fully grasp the potential impact of advanced analytics, which can lead them to assume the advantages aren’t worth the investment. As a result, operational processes and organizational mindsets have not yet caught up to the new database technology landscape. But we have found that most traditional companies are better able to integrate advanced analytics into their organizations than they think.

The power of database technology and advanced analytics

Numerous specialized database technologies are emerging to facilitate specific tasks such as real-time marketing, product searches, and data logging, paving the way toward a more distributed technology landscape. The emergence of these technologies means companies can trade their traditional approaches for more advanced tools, such as the execution of search functions on dedicated graph databases (those that use graphs to interpret data). Complete advanced analytics workbenches1 are also available as cloud-based offerings, facilitating their deployment and putting technologies that were once differentiators within the reach of every company. These new technologies are also increasingly inexpensive.

From a data perspective, it used to be that the exploration of potential correlations and behaviors required analytics professionals to handle sophisticated modeling and analysis. Today, modern neural networks and machine learning can automatically explore behaviors and correlations within historical data to extract insights without relying on these modeling techniques.

Harnessing the benefits of new database and analytics technologies

On a strategic level, executives at traditional companies recognize the benefits of the latest data-related technology: access to quality data across business functions and the ability to make data-driven decisions. Yet they too often assume their organization lacks the needed capabilities.

In our experience, three key organizational and operational strategies can help traditional companies take full advantage of cutting-edge technologies that enable advanced analytics:

  1. Moving analytics to the cloud. On-premise technology is no match for the capabilities, tools, and support offered by modern databases on current cloud technology. Whenever regulatory restrictions allow, companies should move toward cloud-based offerings when building new analytics capabilities.
  2. Creating a culture of data. Insights lie within the data, but the ability to see those insights requires an organizational culture that believes in the importance of data, encourages curiosity, and uses data in all decision making. This includes communicating a change story of new decision making within the organization, being a living example of new data-based decision making, and close monitoring of the adoption of new solutions, including mitigating measures in cases of nonadoption.
  3. Making technological fluency a priority. At traditional companies, the leaders and the organization as a whole lag behind digital natives in their knowledge and comfort with technology and advanced analytics. This growing fluency gap can be bridged only by equipping leadership with the right tools and knowledge, typically through learning boot camps. Doing so will help build commitment for the journey toward a data-driven company.

By focusing on these three commitments, traditional companies can be in a better position to harness the power of cloud-based advanced analytics. The result will be more effective, data-driven decision making.

1 Advanced analytics workbenches are cloud-based solutions that allow users to explore data in depth and use advanced modeling and insight-visualization techniques.

Henning Soller is a partner in McKinsey’s Frankfurt office.