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Seven In Ten Business Leaders Want Robots To Make Their Decisions For Them – Forbes

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It’s easier to make decisions when the economy is growing, as bad choices can get subsidized by the more well-targeted choices. But in a tighter economy, bad decisions are more exposed, and costly. But in this era of data analytics, there will be fewer bad decisions, right?

Hold that thought.

For starters, there is too much data, and not enough insight on how to get to the parts that really matter, that are of material importance to the matter at hand. It doesn’t appear that advanced analytics or artificial intelligence is ready to help, just yet. That’s the word from a survey of more than 14,000 business leaders and employees, of whom 91% agree that too much data is actually limiting the success of their organization. A majority, 73%, of business leaders say data overload and lack of trust in data has stopped them entirely from even making any decisions at all.

In fact, 64% of employees — and 70% of business leaders — would prefer to have a robot make their decisions. Many see analytics as simply out of their reach. No less than 72% believe the majority of data available is only truly helpful for IT professionals or data scientists that can interpret and leverage the insights in meaningful ways.

At least 32% are “overwhelmed” by analyzing data from so many different sources, and 30% don’t believe they have the analytics background necessary to use their findings effectively. Dashboards and other analytics portals are supposed to alleviate this, but 77% of business leaders say that the dashboards and charts they get do not always relate directly to the decisions they need to make.

In addition, most leaders do not believe data is driving decisions — instead, 78% believe their organizations first make a decision, then look for data to back it up. Another 74% of employees think businesses pull rank, putting the highest-paid person’s opinion ahead of data when making decisions, and 24% feel that most decisions made in business are irrational.

Even in the age of sophisticated data analytics and AI, there are tried-and-true best practices for improving decisions. In a recent Harvard Business Review article, Martin G. Moore, a decision management consultant, provides some key points:

  • Be open to multiple viewpoints. “The right people with the relevant expertise need to clearly articulate their views to help the accountable decision-maker broaden their perspective and make the best choice,” says Moore.
  • Base decisions on the advice of those close to the action. Rather than depend on the views of higher-ups, “seek input and guidance from team members who are closest to the action,” says Moore. “And give them credit for actually making your decision a better one.”
  • Address decisions holistically. “Identify the ‘what ifs’ of your choice,” Moore states. “Consider the possible impacts on budget, resource allocations, timeframe, quality, and customer satisfaction.”
  • Tie time spent on decisions to risk levels. “Many leaders procrastinate on decisions because they’re overwhelmed by fear of making a mistake or, even worse, of not being liked,” Moore states. “But the extent to which you might labor on any particular facet of the decision-making process should be determined by one thing: risk. Your assessment of risk will dictate whether you should take a more or less cautious approach.”

Data analytics and AI have become extremely effective mechanisms for making informed decisions that highlight the most relevant data. However, these technologies are merely tools, and decision makers need to keep their skills sharp.

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