June 02, 2021
June 02, 2021
Contributor: Laura Starita
To make more effective business decisions, know when and why to complement the best of human decision making with the power of data and analytics and artificial intelligence (AI).
People make a lot of decisions in today’s organizations. Take pay, for example. Pay rates often reflect management discretion and intangible contributions valued by managers. And yet only 40% of employees believe their pay is fair. Would injecting AI in decision making about pay improve the outcome? More on that later.
Let’s consider first why it’s so hard to make good decisions today, and why AI could help. A recent Gartner survey found that 65% of decisions made are more complex — involving more stakeholders or choices — than they were two years ago. In short, decision making can’t keep up with the fast-changing context in which business decisions are being made today.
“With continually more dynamics and complexity in modern-day business — especially digital business — our capabilities must improve to make the best possible decision in the shortest possible time, in a scalable, risk-conscious, consistent, adaptive and personalized fashion,” says Pieter den Hamer, Sr. Director, Analyst, Gartner. “Moreover, the decisions that we make today can’t be based on yesterday’s situation awareness; they must reflect the here and now.”
Related webinar: Leverage AI to Boost Decision Intelligence for Better Business Outcomes
Humans may not be totally reliable or consistent in decision making, but they still bring important competencies to the table. Similarly, AI in decision making has its place.
Decision automation, decision augmentation and decision support represent the degrees to which AI and analytics can be deployed to pursue faster, more consistent, more adaptable and higher-quality decisions at scale.
The differences lie in the analytics techniques used at various points in the decision process, and who (or what) ultimately makes the decision:
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Whether a decision can be or should be AI automated, augmented or supported depends on two key variables: time, or how quickly the organization needs a decision; and complexity.
The dimension of time refers to the span between when the organization recognizes a threat or opportunity, and when it decides what to do about it and acts. The time span varies between microseconds, in the case of high-frequency stock trading; weeks, in the case of pay decisions; and months or even years, in the case of a strategic merger or acquisition.
Complexity likewise operates on a continuum — mapped by the so-called Cynefin framework, for example, as extending from simple to complicated, complex and chaotic:
Applying the dimensions of time and complexity together can enable leaders to assess individual decisions and determine the value and feasibility of automating, augmenting or supporting them.
Automation is an appealing option for simple decisions that need to be made within a few seconds up to 15 minutes. Decision augmentation is an option for complicated decisions, or those that need to be made within minutes or hours. For complex or even chaotic decisions, and those that aren’t urgent, leaders can explore decision support.
AI applies in all of these situations. Over time, as technology advances, leaders can expect the bounds of what can be feasibly automated to move further along the axis of complexity.
This brings us back to whether AI has a place in pay decisions.
Decisions around pay come in many forms and degrees of complexity, from deciding base pay for a particular role (simpler) to determining raises based on performance (more complicated and sometimes complex).
They are also nonurgent — leaders have days to weeks to make them. That places many pay decisions in the decision support zone, although experience and continuous improvement may give organizations the confidence to automate some pay decisions for some employees.
One in three organizations currently uses AI to make some decisions around pay, according to Gartner research. Seventy-nine percent of those report better pay standardization, and more than half report it has improved their efforts to match pay for performance.
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Recommended resources for Gartner clients*:
When to Automate or Augment Decision Making
Gain Support for Your Security Awareness Program
Should Machines Make Pay Decisions?
*Note that some documents may not be available to all Gartner clients.