How to Leverage Data and Intelligence to Avoid Decision Fails

We live in a world of big data, where Facebook can predict what ads you are likely to click on, Google can complete your sentences in emails and Netflix tells you what show you might like to watch next. Yet, when it comes to making big picture strategic decisions, most organizations are unable to forecast with confidence. They are still flying blind leading to many of the decision fails seen in the headlines.

In 2018 alone, Samsung released a product with faulty hardware that led to months of negative press and decreased sales, Snapchat introduced an unpopular UX update that resulted in lost users and plummeting stock prices, and FedEx was forced to cut annual profit targets due to issues with express delivery and an ill-advised acquisition. 

The good news is that the data needed to start making more informed decisions exists. It’s just a matter of leveraging that intelligence to its fullest potential. Here’s how to avoid decision fails in the new year:  

1. Stop analyzing the past and start looking forward.  

Today, companies spend most of their time evaluating what has happened in the past in order to inform their decisions.  But looking to the past doesn’t always help you understand the future. People and markets are changing constantly, and what if you are making a decision about something that has never been done before?   

There is a need for a faster way to forecast with confidence the impact of today’s decisions on tomorrow’s results.  If you’re able to evaluate the opportunity cost of various decisions by running “what if” scenarios, taking tradeoffs and long-term impact into account, you’ll be able to make smarter, more strategic decisions.

2. Build trust in your data and forecasting abilities.  

From business leaders to policy makers, there is a lack of faith in current forecasting abilities. Alan Greenspan, the former chairman of the Federal Reserve, recently stated that The Federal Reserve Board’s highly sophisticated forecasting system did not predict the Great Recession of 2008 until it hit, nor did the model developed by the International Monetary Fund. Macro-modeling, he said, “unequivocally failed when it was needed most.” 

There have been plenty of other instances in which forecasts have missed the mark. That’s why it’s important to understand how data is being collected. Contrary to popular belief, the data doesn’t need to be perfect. There will always be some level of error that can be accounted for during calibration against in market results, and that’s OK, as long as you trust your methodology.  

3. Democratize decision making.  

As advanced analytics powered by machine learning becomes the norm, there will be an opportunity to democratize decision making. Everyone within an organization will have access to forward-looking, accurate insights generated in minutes versus months. That is, as long as executives opt to share this information broadly.  

The more collaborative the process, the smarter the decisions – whether or not technology is involved. The most successful business leaders in this new era of decision making will harness collaboration and invite new team members to the table. Consider implementing an open forum for decisions about product innovation and beyond. With your entire team armed with insights, you can crowdsource information about customer needs, competition, sales goals and beyond.  

It’s time to get answers to the complex questions that keep us up at night. What’s more, it’s time to evaluate the impact of our decisions before taking action. The way we make decisions is changing and it will take time to adjust. But the result will undoubtedly be better business decisions based on a complete view of potential outcomes.

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