How enterprises can prepare for ‘continuous intelligence’

Real-time analytics will be increasingly integrated into business operations

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Both the dynamics and complexity of digital business are increasing, with more intense competition and more demanding customers. Together, this means decision making must improve in terms of speed, accuracy, personalisation, scalability and adaptability.

The decisions that businesses make today shouldn’t be based on yesterday’s situation awareness, but on the here and now. This requires what Gartner calls continuous intelligence – when real-time analytics are integrated into business operations, processing current and historical data to prescribe actions in response to business moments and other events.

Gartner predicts that more than half of major new business systems will incorporate continuous intelligence that uses real-time context data to improve decisions by 2022.

In response, data and analytics leaders are faced with growing demand for decision automation and augmentation. In instances where full automation is inviable or undesirable, decision makers need to be optimally supported by business intelligence (BI), or even augmented by artificial intelligence (AI) powered analytical systems.

In other words, it’s important to apply either decision automation, augmentation or support depending on the decision case, feasibility and other criteria.

What are the differences?

Decision automation totally leaves the decision making to a system, mainly using prescriptive analytics, and if needed, predictive analytics. Benefits include speed, scalability and consistency of decision making, leveraging the growing availability of contextual data and AI capabilities.

Decision augmentation, or augmented decision support, semi-automates decision making by using prescriptive analytics, and predictive analytics if needed, to recommend a decision. It offers several decision alternatives to humans, who still make the final decision. Synergies are created between human knowledge, expertise, common sense and emotions, with the capability of AI and other digital technology to deal with more data and greater complexity.

Decision support leaves the decision making fully to humans, but supported by descriptive, diagnostic or predictive analytics. This may include knowledge management, collaboration and communication facilities. The main benefit lies in the combined application of data-driven insights and human knowledge, expertise and common sense, including “gut-feel” and emotions.

Data and analytics leaders need to make several key decisions, including identifying opportunities within the organisation for the deployment of decision automation, augmentation or support; assessing the viability of each of those options; and identifying enabling technology.

Identify how improvements can be made

Organisations target their most important business moments and uses to improve decision making in terms of speed and accuracy, using as much relevant data as possible to create a more complete and more up-to-date situation awareness.

Identify where and how decision making should be improved by comparing the benefits of decision automation, augmentation or support. Work closely with stakeholders, particularly in areas most relevant to your organisation’s competitive strength, customer interaction, operational excellence or compliance.

Determine if automation makes sense

The application of decision automation, augmentation or support doesn’t only depend on the business relevancy to improve decision making, but also extensively on the complexity, timing and risks of the different decision making activities.

First, evaluate the timing of decision making, particularly the duration between the occurrence of an event and the decision on how to respond. Time may vary between microseconds in the case of high frequency stock trading, and months or even years in the case of strategic merger or acquisition decisions. Full automation makes sense when decisions must be made in real-time.

Complexity is another important factor to evaluate. Decision making and its level of automation must be differentiated based on the nature of the context or situation in which it takes place and applies to, whether it be simple, complicated, complex or chaotic. Automation is currently only feasible when complexity isn’t too high. For example, decision making in a crisis situation, such as a power outage, would best be supported, not automated.

The risks of making the wrong decision should also be determined. The very benefits of automation – scale and efficiency – magnify a small mistake quickly to unmanageable proportions. Without human common sense, autonomous systems may quickly cause massive problems when automated decisions are wrong, incompliant, biased or go haywire. If the risks are too high, then decision augmentation makes more sense than full automation.

Identify enabling technology

As a starting point for building decision making solutions, identify technologies that are relevant for the decision type at hand, again using complexity and time as main criteria.

Empower decision automation with real-time event stream processing and decision management rule inferencing or optimisation techniques for continuous intelligence.

For decision augmentation, prescriptive analytics is required. In more complex decision cases, complement this with other AI and BI techniques to create a synergy between human intelligence and AI.

To improve decision support, apply technologies that go beyond conventional business intelligence, such as interactive visualisation and augmented analytics. Enrich descriptive and diagnostic analytics with storytelling, collaboration, personalisation and other complementary technologies.

Pieter den Hamer is a senior director analyst at Gartner, focusing on the creation of societal and business value from real-time data and artificial intelligence as the key enabler of digital innovation in an increasingly complex world. Pieter is speaking at the upcoming Gartner Data & Analytics Summit in Sydney, 17-18 February.

Copyright © 2019 IDG Communications, Inc.

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