The Demand for Business Intelligence


The Demand for Business Intelligence


Business Intelligence strategies and solutions have been top of mind for executive leaders for close to a decade and are showing no sign of letting up.  The Global Business Intelligence (BI) Market is expected to grow from $15.64 billion in 2016 to reach $29.48 billion by 2022 with a CAGR of 11.1.  

This growth is to be expected as organizations continue to understand better how measuring, reporting and reviewing results and key data are critical to an organization’s effectiveness.  Organizations always have an abundance of data available to them, and this will only grow with the help of the Internet of Things, but this does not always translate into actionable, evidence-based business intelligence.  Why? Here are three, high-level reasons organizations are not using data efficiently.   


All  data is not equal   

Data is generated in amounts that are difficult for us to comprehend. Let’s avoid focusing too much on the different types of data, structured, unstructured, metadata, open, etc. and focus on the simple concept that too much data is merely that - too much.  What are the organizations priorities and what data will help execute against those priorities?  This should be determined at the organizational level in addition to the business unit or department level for analytics capabilities to reach their full potential.  Cut out as much noise as possible by focusing on the data that is valuable, reliable and can be used effectively.  


If data is data to find we won’t consistently search for it

The abundance of data organizations have typically resides in multiple systems without an automated process to access it quickly. At a minimum, this makes searching for or extracting data time consuming and inefficient.  Most likely, it means people are not consistently looking for it.


If data is difficult to view we won’t consistently absorb it

As an executive sales leader for a previous organization, I fondly remember the day IT told me that the extraction and collection of data I’d asked for had been automated.  With a mixture of fear and excitement, I couldn’t wait to get the data. My concern quickly ran over my excitement as the output was a mess of bar graphs, colors, and charts.  My eyes glassed over trying to process it all and in time, after numerous discussions on how to have the data better visualized, I went back to working around the system than working with it.  Like the previous point, this was time-consuming and inefficient.  Instead of being drawn to data that was supposed to help keep my pulse on the business and make relevant quick decisions, I was only looking at it when necessary which translated to reactive decision making.  

Some of the fastest growing organizations, like Facebook, Google, Uber, and Amazon understand the value of advanced data and analytics. They’ve proven that the right data, extracted, refined and presented effectively will continue to help differentiate organizations that execute with speed, precision, and excellence.  

The proper business intelligence strategy will determine what data will have the greatest impact on an organizations strategic and tactical decisions.  The right business intelligence tools will make the information easy to find and pleasing to see.