Enterprise intelligence initiatives are becoming more purpose-built to drive specific business outcomes, focusing on enabling faster and higher-quality data analysis and decision support. Organizations can become more agile and resilient by arming their employees with the right insights at the right time to make the best possible decisions.

The future of intelligence

IDC defines enterprise intelligence as consisting of:

  • The ability to synthesize information
  • The capacity to learn from that information
  • The ability to apply those insights at scale
  • A strong data-driven culture that enables organizations to improve business outcomes (Figure 1)

A modernized technology platform forms the foundation of these four attributes that enable enterprise intelligence. However, IDC research consistently shows that organizations need more than technology investments to increase their enterprise intelligence.

It's about more than technology

According to IDC's Future of Intelligence Survey (August 2021), seven of the top 10 most difficult enterprise intelligence challenges had more to do with people — particularly, how people relate to each other and to the data they need to make decisions — than a lack of a technology platform. Figure 2 shows the top 10 enterprise intelligence-related challenges receiving a rating of either 9 or 10 on a scale of 1–10, where 1 meant "easily overcome" and 10 meant "insurmountable."

Improving business outcomes using data-driven insights requires systems that leverage technology, data, people and processes to increase enterprise intelligence. At a deeper level, it requires understanding how different personas (both internal and external) use data and insights to make decisions, creating applications that deliver highly relevant insights and more seamless interactions and experiences.

Building the team

Thinking about enterprise intelligence as a team sport can be a helpful starting point for considering where to focus investments. If finding appropriate skills and capabilities within the organization is a challenge, the right partner can provide the talent to augment internal initiatives.

Enterprise intelligence teams will look different for every organization, but likely involve a similar roster of players:

  • Executives use data and enterprise intelligence to make strategic decisions. They are also responsible for establishing and promoting a data culture across their organizations.
  • Managers typically own specific outcomes in departments or processes they oversee and use operational insights to make the decisions in those roles.
  • Employees, no matter what they are doing, interact with data and make decisions in their work. They also build knowledge and subject matter expertise that becomes essential to maintaining enterprise intelligence.

In addition to these internal players, organizations need to consider how their broader ecosystem — industry partners, customers, suppliers, regulators, academia, etc. — impact their enterprise intelligence strategy.

For example, improving customer experience using data-driven insights requires understanding customers’ behaviors and needs and predicting the next best actions based on that understanding. As simple as this concept sounds, in practice it can require redesigning data flows and business processes and considering new ways to apply various pieces of related information and knowledge to solve business problems, at scale and at speed.

Depending on the industry, those “next best actions” may rely upon intelligence and actions in other business functions, such as supply chain management, financial planning, regulatory compliance and facilities management, to name a few examples. Increasingly, matters of environmental and social sustainability and business ethics influence customer experience and engagement with brands, and a changing tide of consumer sentiment can now start with a social media post.     

Technology platforms provide access to capabilities such as artificial intelligence, analytics, automation, data management and cloud, which augment human capacity to consume vast amounts of data with the speed and accuracy required for the pace of business decision making. Professional services providers play critical roles in helping organizations to construct and manage enterprise intelligence platforms through service offerings such as IT consulting, systems integration, custom application development, managed services, and hardware and software support.

Services firms also help organizations navigate the complexity involved in building enterprise intelligence capabilities in ways beyond deploying technology, such as providing strategic advice, best practices, methodologies, domain expertise, technology skill augmentation, co-innovation, business analysis and training. These firms can help with the following areas:

  • Data – Services firms help craft strategies for data acquisition, architecture, governance, trust, security, monetization and sharing across ecosystems.
  • People – Services firms help supply and develop in-demand skills in enterprise intelligence technologies and data literacy, and provide advice and support for new talent models, culture and organizational change management, user experience design and human-machine collaboration.
  • Processes – Services firms help reengineer enterprise intelligence workflows, establish centers of excellence, and provide frameworks for implementing the various required "Ops" (e.g., DataOps, MLOps, DevOps, AIOps, DevSecOps) and responsible AI principles.

Partnerships between services providers, technology platforms, and organizations themselves will be critical to ensure enterprise intelligence investments deliver improved business outcomes. 


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About the author

About the author

Jennifer Hamel is a research director for IDC’s Worldwide Services team, responsible for the Analytics and Intelligent Automation Services research program. In this research, she covers the entire life cycle of services related to adoption of analytics and intelligent automation.