What comes to mind when you think of intelligence within your organization? Is it having access to the latest information on key metrics, such as revenue, costs, and profit? Is it a broader view of ‘all information’ you need to make a decision?
These have been and indeed remain the primary definitions of business intelligence at most organizations. But are they enough in today’s world of data abundances and attention scarcity? At IDC, we propose that it is time to redefine what enterprise intelligence means and set a new course for the future of intelligence – one that retains the best of business intelligence and analytics but extends them with other capabilities for synthesis of information and extends into learning.
Looking at the classic definition of intelligence, which defines it as the ability to acquire and apply knowledge and skills and the collection of information of business, military, or political value, IDC global Future of Intelligence market research practice has developed a definition for technology and business leaders.
The Future of Intelligence Defined
The future of intelligence is an organization’s capacity to learn combined with its ability to synthesize the information it needs in order to learn and to apply the resulting insights at scale. In order to separate themselves from their competitors, truly intelligent enterprises will need to focus on cultivating the ability to continuously learn at scale and apply that learning across the entire organization instead of in departmental silos quickly.
This requirement to combine synthesis of all information with capacity to learn and delivery insights at scale is not simply a set of theoretical concepts. When we conducted a study of 100 CEOs in mid-2019, fully 80% of these business leaders mentioned ‘using data in advanced decision models to affect performance and competitive advantage’ as an important priority for their enterprises for the next five years. Note that they didn’t say they want more data.
While analytics, business intelligence, and artificial intelligence strategies and technologies have made information collection and synthesis familiar to most businesses, most will need to address serious challenges to achieve future of intelligence capabilities.
Why? Because for almost every enterprise, silos prevent enterprise-wide access to data, data analysis, and insight delivery. Projects happen in departmental or organizational silos, and data, knowledge, and insights are corralled there when they could deliver tremendous value if deployed across the organization.
Enterprises able to overcome these challenges will learn as a single entity and at scale. In such enterprises, the data generated from products, services, experiences, and ecosystems will inform and drive intelligent automation of processes as opposed to being simply an ingredient for offline reports. Those that can achieve this economy of intelligence will have a competitive advantage just as those organizations in the past that achieved economies of scale and scope had an advantage over peers. This path to intelligence will depend on having the following capabilities:
Ability to Synthesize Information
This is the process of taking discrete, objective raw facts about people, places, things, and other entities and organizing them for some useful purpose for the business, usually by the addition of some context.
To enhance your ability to synthesize data to create knowledge, your organization will need to foster a culture that recognizes the value of data and access to data based on trust between the enterprise and its employees and delivers transparency about the data itself through data intelligence to derive value from it.
Capacity to Learn
Information on its own has limited value; understanding the relationships between discrete data points is where organizations can really take advantage of their intelligence efforts. The capacity to learn refers to this understanding of the relationships between individual pieces of information and between information and previously developed organizational knowledge. Additionally, it encompasses the ability to apply that understanding to a specific problem. Capacity to learn affects both humans and machines. People will learn not only from other people but also machines and machines will learn from both people and from other machines.
Enterprises that demonstrate mastery of this capability will focus a significant amount of effort into converting tacit knowledge into explicit knowledge and disseminating it across the enterprise. Creating an enterprise-wide knowledgebase of best practices, internal and external experts, and a collection of the data along with accompanying standards and policies is a key step towards the future of intelligence.
Delivery of Insights at Scale
Delivering insights at scale means supporting decision making and decision automation requirements for everyone in the enterprise, from the C-suite to the machines automating certain tasks. Enterprises that will achieve the mastery of this capability will recognize that whether to use AI platforms or rules engines and data warehouses or data lakes, whether to deliver intelligence at the core or at the edge, or whether to do so in the cloud or on-premises are not binary choices.
Enterprises will also recognize that the delivery of insights at scale, like the ability to synthesize information and the capability to learn, is a team sport that requires a mix of technical, analytic, and business skills. They will invest heavily in security and trust treating to protect data and proprietary algorithms. They will also invest in AI-based automation of the technology platform itself.
Ready to Pursue the Future of Intelligence?
The future of intelligence offers opportunity for both technology suppliers and business leaders to compete in the digital economy. Business leaders need to remember that these three capabilities are not individual elements; you will need to invest in all three to achieve economies of intelligence that deliver sustainable business value.
At IDC, we believe the future of intelligence is a critical component for the CEO’s new agenda and a differentiator in the digital economy. That’s why it is one of the nine new research practices we are launching this year. Stay tuned to hear more about the future of intelligence and learn more about the future of intelligence and the value it can create, see our latest research “Future of Intelligence: Insights at Scale“:
