One of the key findings in our latest benchmark research into predictive analytics is that companies are incorporating predictive analytics into their operational systems more often than was the case three years ago. The research found that companies are less inclined to purchase stand-alone predictive analytics tools (29% vs 44% three years ago) and more inclined to purchase predictive analytics built into business intelligence systems (23% vs 20%), applications (12% vs 8%), databases (9% vs 7%) and middleware (9% vs 2%). This trend is not surprising since operationalizing predictive analytics – that is, building predictive analytics directly into business process workflows – improves companies’ ability to gain competitive advantage: those that deploy predictive analytics within business processes are more likely to say they gain competitive advantage and improve revenue through predictive analytics than those that don’t.
Operationalize Predictive Analytics for Significant Business Impact
Topics: Big Data, Microsoft, Predictive Analytics, SAS, Social Media, alteryx, Customer Performance, Operational Performance, Analytics, Business Analytics, Business Intelligence, Business Performance, Operational Intelligence, Oracle, Information Optimization, SPSS, Rapidminer
Business Case for Predictive Analytics is Simpler Than You Think
Our benchmark research into predictive analytics shows that lack of resources, including budget and skills, is the number-one business barrier to the effective deployment and use of predictive analytics; awareness – that is, an understanding of how to apply predictive analytics to business problems – is second. In order to secure resources and address awareness problems a business case needs to be created and communicated clearly wherever appropriate across the organization. A business case presents the reasoning for initiating a project or task. A compelling business case communicates the nature of the proposed project and the arguments, both quantified and unquantifiable, for its deployment.
Topics: Big Data, Microsoft, Predictive Analytics, SAS, Social Media, alteryx, Customer Performance, Operational Performance, Analytics, Business Analytics, Business Intelligence, Operational Intelligence, Oracle, Information Optimization, SPSS, Rapidminer
Predictive Analytics: Investing and Selecting Software Properly
To impact business success, Ventana Research recommends viewing predictive analytics as a business investment rather than an IT investment. Our recent benchmark research into next-generation predictive analytics reveals that since our previous research on the topic in 2012, funding has shifted from general business budgets (previously 44%) to line of business IT budgets (previously 19%). Now more than half of organizations fund such projects from business budgets: 29 percent from general business budgets and 27 percent from a line of business IT budget. This shift in buying reflects the mainstreaming of predictive analytics in organizations, which I recently wrote about .
Topics: Big Data, Microsoft, Predictive Analytics, alteryx, Customer Performance, Analytics, Business Analytics, Business Intelligence, Operational Intelligence, Oracle, Business Performance Management (BPM), Rapidminer
