Five Rules For Successful Business Decision-Making

Pascal Bornet is an award-winning expert in AI and automation, Chief Evangelist at Aera Technology, best-selling author, and keynote speaker

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Effective decision-making is more important than ever before. Sixty-five percent of executives have to make more complex decisions today than they did two years ago, according to research from Gartner Inc., and 50% of them experience higher pressure to justify the decisions they make.

Companies succeed or fail based on the effectiveness of their decision-making. How can you ensure your decisions are objective, consistent and based on complete information? How can you avoid costly mistakes due to information overload, lack of time or bias?

Here are five rules about how to make effective decisions.

1: Be aware of your own bias

We are all subject to biases that affect our decision-making. By “biases,” I don’t just mean political hot-button issues like racism and sexism (although those can be a part of it), but the more fundamental cognitive biases that are part of the universal human mental architecture.

For example, we spot imaginary patterns in random data (pareidolia) and make predictions based on them (the gambler’s fallacy). We evaluate trade-offs differently depending on how they are worded (the framing effect). We over-value the current or default option (status quo bias) or options we’ve already invested in (sunk cost fallacy) at the expense of other options that might be more advantageous.

These biases are part of human nature, and you can never suppress them entirely. They are often useful: They provide mental shortcuts to decisions that are correct most of the time with minimal effort and minimal cognitive load, thus reducing stress and anxiety. The problem is that they’re only correct most of the time. If you’re using unexamined cognitive shortcuts to manage a budget of millions of dollars, the times when the shortcuts fail can be catastrophic.

There are 188 known cognitive biases. I don’t recommend learning them by heart, but you should read the list at least once in your life so that you’re aware of the potential traps you could fall into.

2: Don’t confuse good decisions with good outcomes

Luck impacts the outcome of all decisions. Therefore, the way we make decisions is the only input that we have control over.

It is by carefully rethinking the way we make decisions that we can reliably and sustainably improve their impact. Just like in scientific studies, a systematic approach underpinned by statistical tools will eliminate the random variation due to chance so that you can focus on the decision-making itself.

Today, in most enterprises, decisions are made differently by different people. Even experts in the same field will not have the same way of making the same decisions; hence the necessity to document decisions (decision maps), optimize the way decisions are made and standardize these maps. Only when this is done can we digitize and automate decisions—and by digitalizing the decisions, we ensure consistency in the way decisions are made.

3: Set clear goals and implement appropriate governance

Motivations and goals are necessary for decision-making. No goals, no decisions. Intrinsic motivations are always best. For example, the motivation of a doctor who is passionate about the meaningful action of saving lives (intrinsic motivation) is always stronger than that of a doctor who just works hard to receive a high income.

Collective performance indicators are preferred to individual ones: They help to ensure consistency of decisions and outcomes across individuals or departments over time.

Authority to make decisions should be given to the people closest to the point of impact of those decisions, increasing reactivity and learning.

4: Measure, monitor and learn from decision-making to improve it

The most reliable way to record and measure decisions is to digitize them. It’s important to have objective records of decisions rather than just people’s memories, especially as memory is an area that’s particularly vulnerable to cognitive biases. For example, hindsight bias is the tendency to see past events as predictable and to believe that you “knew it all along.” People can also be susceptible to positivity or negativity biases in their recall, or exhibit biases relating to misattribution of memory, like cryptomnesia (mistaking a memory for a new thought), or its inverse, false memory (where an imaginary event is mistaken for a real memory).

Once you have objective, digitized records of decisions made, you can measure the variance between the expected and actual impact of decisions, and you can track them over time using analytics.

5: Leverage decision intelligence technology

Leverage technology to support the previous four rules! In a world where an increasing amount of business processes are supported by technology, the same should be true for decisions.

Decision intelligence (DI) is a new field that crosses the streams of process automation and machine learning to produce a decision-focused technology that can support, digitize, augment, automate and monitor decisions.

Decision intelligence can help digitalize the four previous rules—even the governance piece, which can be digitalized by using workflow features and where decision performance can be measured using analytics. It lets you automate simple routine decisions, freeing you from decision fatigue and information overload and enabling you to focus on making high-quality, high-impact decisions rather than just reaching for obvious-sounding answers under time pressure.

Alongside automating simple decisions, DI helps leverage big data and machine-learning tools to support and augment the more complex decisions. This fills any gaps in your information and applies objectivity and consistency.

Finally, DI incorporates a systematic approach to feedback and continuous improvement so that both automated and human decisions can be measured, monitored and improved.

Conclusion

To improve the effectiveness of your decision-making, acknowledge your own biases, and measure and digitize your decisions and their outcomes. Leverage decisions intelligence technology to support, augment or automate your decisions, and monitor them over time. This way, you can increase the reliability and impact of your decisions.

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