Business intelligence continues to be a top priority for CIOs, because organizations driven by analytics show faster revenue growth, greater return on invested capital, and higher earnings per share than those that are not. A Nucleus Group study showed the return for every dollar spent on analytics is over $13, and that number is growing.
To realize that return, analytics should consistently guide every decision in all departments by all workers. Users must be able to apply analytics across all time perspectives, including predicting what action to take in the future. That means you have to put BI in the hands of every single user who needs it, no matter what their skill or experience level is.
With the self-service capabilities of today’s BI solutions, your users can quickly create guided drag-and-drop dashboards from a desktop or mobile device. The interactive content can be personalized for each consumer and can be delivered to any user at device so that analytics is always at their fingertips. Our Big Data and Analytics team can show you how.
Let our consultants show you how the following areas can drive value into your business:
- Data Visualization: Previous versions of business intelligence required IT assistance at almost every step of the way. New generations of technology meet the stringent requirements of the new generation of user. Knowledge workers can now find their own answers and independently explore data housed on premise or in the cloud. Text search capabilities present users with content needed to build and understand their own analyses.
- Predictive Analytics: It’s not always enough to understand what happened yesterday or last month. You need to understand what is likely to happen or what the next best action should be. Use predictive output from your data to improve customer experience, detect fraud, optimize operations, or increase customer lifetime value.
- Cognitive Analytics: Predictive insights are more valuable than backwards-looking BI, but not every knowledge worker is capable of building a predictive model, and waiting for a data scientist to build a model and score data takes valuable time. Cognitive analytics insulates users from algorithms and models while uncovering hidden relationships and patterns in your data at will, telling you what’s likely to happen, and suggest what you may want to do next.