From basic to predictive processes: The “insights” leap enterprises must make to fuel growth

• According to a recent study conducted by HFS Research, only one in five enterprise leaders say they are getting forward-looking operational insights from predictive analytics applied to their process data. The remaining 80% risk falling behind with valuable insight data going to waste.
• Proper usage of underlying data is the key to mining insights to drive process improvements. The first step for enterprises is to have a vision in place for connected data to be available across business functions. The next is to focus on making planned investments to make the data accessible, and the last but important bit is change management—educating talent on how to use the available data.
• With these in place, enterprises can use data to anticipate market challenges and issues. For example, once process intelligence has identified inefficiencies in workflows, reasons for slow downs can be mapped against historical data to enable the enterprise to preempt when and how those slow downs might happen again. And that’s just a stop-gap. Removing inefficiencies opens the way to new growth.
• Out of the 80% of firms yet to embark on their predictive insights journey, 31% are yet to even start their journey toward using data for predictive insights and only expect to do so over the next two to five years. Getting predictive with data is a work in progress right now for many, but it needs to be a part of the broader enterprise roadmap to tap unused data potential within enterprises. The good news is two in three enterprises have got the message and are already making the shift toward predictive insights. By being able to look further ahead than their competitors, they will be able to plan for change and move faster.

The Bottom Line: Predictive insights will be table stakes within two years. If you aren’t moving now, your future looks bleak.

Attaining predictive process insights can no longer be a five-year plan. Enterprises must take action now to break siloes and use data more productively to power forward-looking operational insight.

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