What is Decision Management?
Modern-day business operations are centered around processes and data. However, when knowledge and expertise are forced into hard-coded, inflexible systems, bottlenecks occur. By adopting and scaling the capabilities of business rules, decision modeling, and machine learning, Digital Decisioning leverages data and expertise to create business value, improve results, and deliver a great user experience to effectively meet today’s operational requirements. For Digital Decisioning to deliver true value, it must initially focus on solving business problems that will, ultimately, contribute to positive and desirable business outcomes. Technology, automation, and methodologies are essential for Digital Decisioning, but they are always at the service of business decisions.
The foundation for successful Digital Decisioning projects is applying a Decision Management approach. Decision Management models business decisions first. These decisions, for the most part, have to do with customers and how you engage with them, deliver services to them, or handle their transactions.Once you have a good grasp of what decisions your business needs to make and how these decisions will advance your business, Decision Management shows which technology and analytics tools you need to invest in and how to integrate them. Finally, Decision Management focuses on the processes and infrastructure needed to ensure continuous improvement and business engagement. To maximize success, adopt a proven approach such as the DecisionsFirst™ approach from Decision Management Solutions.
Research Report and Infographic
Identifying the right analytic capabilities for success
Our recent research study looked at the increasingly broad portfolio of analytic capabilities available to enterprises today. These range from traditional Business Intelligence (BI) capabilities like reporting and ad-hoc query to modern visualization and data discovery capabilities and advanced analytics. These capabilities are often presented as part of a maturity curve, where enterprise customers are expected to keep moving “up” the curve to get more value.
In fact, enterprises adopt these technologies in different sequences and ultimately need a mix of these capabilities. Most, if not all, enterprises have a real business need for all of them. The real questions are, what situations need which capabilities, who is the target user for these capabilities, and how can this portfolio of capabilities be managed most effectively in an era of Big Data?
The Analytics Capability Landscape Research Report answers these key questions to help your planning and purchase decisions now and in the coming months. Fill out the form to get the Infographic and the full Analytics Capability Landscape report.