3 Ways to Move Beyond the “Digital Impasse” and Start Seeing Results

May 11, 2018
Roman Stanek's picture
Founder & CEO
Roman Stanek is a passionate entrepreneur and industry thought leader with over 20 years of high-tech experience. His latest venture, GoodData, was founded in 2007 with the mission to disrupt the business intelligence space and monetize big data. Prior to GoodData, Roman was Founder and CEO of NetBeans, the leading Java development environment (acquired by Sun Microsystems in 1999) and Systinet, a leading SOA governance platform (acquired by Mercury Interactive, later Hewlett Packard, in 2006).

Recently, I came across an article that mentioned that 59 percent of companies remain at a "digital impasse", where they have tried to introduce digital solutions but have seen few benefits. I have to say that this upsets me; there’s so much that analytics can offer, but these companies are unfortunately not seeing what all the fuss is about. To address this impasse, I wrote a recent BetaNews article, where I shared three key steps for moving up the analytics maturity curve to start seeing results.

1. Embed actionable insights into applications

The insights may be valid, but they’re most actionable and easily understood when they’re embedded into the application at the point of work. Not only does this allow employees to better understand how actions will affect the business, but it also enables actions to be taken more quickly so any issues can be addressed.

2. Use predictive analytics to make confident recommendations

The value of predictive analytics is enormous. By accessing historical data, analytics can recognize patterns that help companies to do anything from identifying potential fraud and reducing risk to setting prices and managing inventory. Predictive analytics can also respond to these patterns faster and more reliably than humans can, saving companies valuable time and resources.

3. Implement machine learning to automate decisions

Once predictive analytics are in place, a logical progression is to introduce machine learning to analyze current data and determine the most appropriate response. By completely automating the next steps based on the algorithm’s predicted outcome, companies are able to take action before an adverse event occurs.

By moving up the analytics maturity curve in this fashion, companies can soon realize the value and increased efficiency that analytics have to offer. However, the time to take these steps is now. Delaying their efforts any longer could cause these companies to fall even further behind their competitors, who have likely been leveraging the value of digital solutions for years.


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