A recent ComputerWeekly article presents some startling figures concerning the amount of money businesses are investing in business analytics. The article1 reports that business intelligence software and services will reach $143 billion in 2016, with two-thirds of that being on services. That amount is double the current expenditure. If your son or daughter cannot hit a driver or sink a putt to make the PGA tour, maybe they should consider a career in sales of BI software and services.

BI software has been around for decades. Cognos was founded in 1969, and BusinessObjects in 1990, Crystal Reports in 1991, MicroStrategy in 1984 and Microsoft introduced SSRS in 2004, so these tools have been through iteration after iteration of product updates and platform enhancements. Companies have been installing and utilizing business analytic tools for decades. In my more than 30 years in the industry, I cannot remember a time when we did not rely on these tools for analytics reporting projects.

Several factors contribute to continual ongoing projects. First among them is the enormous amount of data companies now have to manage, analyze and digest to improve performance. It is not unusual for companies to retrieve, access, process and store more data in a day than they used to retrieve in a month. Some studies indicate companies are processing as much as 1,000 times more data today than they did a decade ago2. The intent of Business Analytics is to translate data into information to improve the business. Businesses can know more than ever before, but to make sense of it, to turn that pile of bricks into a building, requires a commitment to maintaining the right business analytics resources.

A second factor driving business analytics is metrics and reporting, which often drives the need for more metrics and reporting. As we get a set of metrics and analytical reports, our knowledge increases as does the need to ask more questions and the need for more data analysis. Insights lead us to seek more information to reach the next level of conclusion. It’s a self-propelling cycle that only grows more complex.
Considering that analytics software and services have been a major focus of companies for years, compounded with the large investments that come with their acquisition, installation and maintenance, by now most organizations should be “mature” analytics organizations. However, this often is not the case – as most organizations never examine their analytics maturity. Many companies continue to spend money on software, on expert staff, and on amassing and warehousing data. Few companies assess the practices involved in a mature analytics-based company. Nor do they step back and examine their processes, refining and maturing them to realize the full potential of their business analytics resources. 

An organization high on the analytics maturity scale should lower their continued investment in software and services while reaping greater value on their investment.  The key practices in analytics maturity are:

1. Measure: the processes to establish metrics, report metrics and utilize metrics
2. Extract business value: the processes to transition business questions to analytics questions, prioritize analytics activity, execute analytics requests and confirm business value
3. Support: the processes associated with how an organization supports the infrastructure and the and feeding of the analytics organization

Companies seem eager to chase the next software product, to rush to build larger data marts, and to add more BA staff. It seems rare for an organization to take a holistic approach and examine the analytics practices needed to secure the biggest return on the investment of time and money. It is time to put this triad of technology, people and process into balance by focusing more attention on maturity in the discipline of business analytics.