Five Keys for Making Smarter Decisions

Five Keys for Making Smarter Decisions

Over a third of millennials in the workforce fear that Artificial Intelligence will kill more jobs than it creates, according to the Silicon Valley Business Journal. This is ironic, because 96% of the boomers and 88% of the Gen-Xers who employ them in the tech industry believe that AI will create more jobs. Perhaps the reason for the disconnect is that, intuitively, the leadership of the tech industry already knows that AI will only help lower the cost of making predictions, but by itself, it won’t make smarter decisions. Which leads one to ask, then, what does?

Extracting from Irving Wladawsky-Berger’s latest “CIO Journal” blog in The Wall Street Journal, five keys emerge for making smarter decisions – in the 21st century:

1) Insights extracted from Big Data can lead to making better predictions.
Irving posits that the growth of big data and advanced algorithms, like machine learning, enable us to analyze and extract insights from all that data. Which, in turn, allows us to make better predictions – and, thanks to Moore’s Law, to do so more cheaply. His conclusion: “decision making, the process of identifying and choosing alternatives, will be particularly affected by advances in AI.”

2) Data isn’t enough; sound decision making also requires judgment.
Once a machine – or banks of machines – have chomped through terabytes of data to make their prediction, a decision maker still needs to add “judgment” (forged by experience) to the secret sauce, resulting in a “smart decision.”

3) Avoid cognitive biases.
Savvy corporate leaders appreciate that even the smartest computers were programmed by humans with some unintentional degree of cognitive bias that can undermine good decision making. These biases include: “anchoring” – when the decision maker relies too heavily on an initial piece of information to make subsequent judgments; “loss aversion” – the tendency to prefer avoiding losses to acquiring equivalent gains; or: it’s better to not lose $5 than to find $5; and “confirmation” – when new evidence is interpreted as confirmation of one’s existing beliefs or theories.

4) Prioritize your decisions.
In “Untangling Your Organization’s Decision Making,” a recent McKinsey & Co. article, the authors define four levels of executive decisions: Big-bets (infrequent and high-risk), cross-cutting (more frequent, interconnected decisions made by different groups), delegated (frequent, low-risk, made by an individual or team, with limited outside input), ad hoc (low-stakes, less impacted by organizational ambiguity). While the article also details steps for making successful cross-cutting and delegated decisions, smart decision makers focus on getting their Big Bets right.

5) Use this 4-step process for Big Bet Decisions.
First, appoint an executive sponsor – who’ll work to frame the important decisions for senior leaders to weigh in on – starting with a clear, one-sentence problem statement.

Second, break things down, and connect them up: break down the multiple parts of large, complex decisions into bite-size chunks, with decision meetings at each stage. Watch out for interdependencies with other decisions – step back to connect the dots.

Third, deploy a standard decision-making approach – stimulating interaction and discussion, including quality debate, competing scenarios, and devil’s advocates; create a clear agenda that focuses on debating the solution (not elaborating the problem); do robust prework; and assemble the right people – with diverse perspectives.

Fourth, move faster without losing commitment: bring the available facts to the table and commit to the outcome of the decision. Executives need to get comfortable living with imperfect data, and being clear about what “good enough” looks like. Then once made, commit to the decision. And ensure, at the conclusion of every meeting, that it is clear who will communicate the decision, and who owns the actions to begin carrying it out.

The fact is, as long as judgment is required to make smarter decisions, workers – at virtually every level in the organization – are not going to be replaced by AI. But, used effectively, AI will enhance their decision making capability – particularly on the Big Bets.

by Mimi Grant, President, Adaptive Business Leaders (ABL) Organization – Round Tables and Events for CEOs of Technology and Healthcare Companies