Organizations are managing and analyzing large datasets every day, identifying patterns and generating insights to inform decisions. This can provide numerous benefits for an organization, such as improved operational efficiency, cost optimization, fraud detection, competitive advantage and enhanced business processes. By bringing the right, actionable data to the right user, organizations can potentially speed up processes and make more effective operational decisions.
Palantir Operationalizes Analytics and Data for Actions and Decisions
Posted by
David Menninger on Aug 26, 2022 3:00:00 AM
0 Comments Click here to read/write comments
Topics: embedded analytics, Business Intelligence, Internet of Things, AI and Machine Learning, Streaming Analytics
Don’t Rely on Dashboards for Real-Time Analytics
Posted by
David Menninger on Mar 31, 2022 3:00:00 AM
I have written previously that the world of data and analytics will become more and more centered around real-time, streaming data. Data is created constantly and increasingly is being collected simultaneously. Technology advances now enable organizations to process and analyze information as it is being collected to respond in real time to opportunities and threats. Not all use cases require real-time analysis and response, but many do, including multiple use cases that can improve customer experiences. For example, best-in-class e-commerce interactions should provide real-time updates on inventory status to avoid stock-out or back-order situations. Customer service interactions should provide real-time recommendations that minimize the time to resolution. Location-based offers should be targeted at the customer’s current location, not their location several minutes ago. Another domain where real-time analyses are critical is internet of things (IoT) applications. Additionally, use cases like predictive maintenance require timely information to prevent equipment failures that help avoid additional costs and damage.
0 Comments Click here to read/write comments
Topics: business intelligence, Analytics, Internet of Things, Data, Digital Technology, AI and Machine Learning, Streaming Analytics, Analytics & Data, Streaming Data & Events
The 2022 Market Agenda for Office of Revenue: New Performance Priority
Posted by
Stephen Hurrell on Feb 8, 2022 3:00:00 AM
Ventana Research recently announced its 2022 Market Agenda for the Office of Revenue, continuing the guidance we have offered for nearly two decades to help organizations realize optimal value from applying technology to improve business outcomes. Chief sales and revenue officers and their associated operations teams are experts in their respective fields but may not have the guidance needed to employ technology effectively. As we look to 2022, we are focusing on the entire selling and buying life cycle and the applications that simplify and improve interactions throughout the customer experience.
0 Comments Click here to read/write comments
Topics: Sales, Analytics, Internet of Things, Data, Sales Performance Management, Digital Technology, Digital Commerce, Conversational Computing, AI and Machine Learning, mobile computing, subscription management, extended reality, intelligent sales, partner management, Sales Engagement
The Digital Technology Market Agenda for 2022: Innovation for Business Resilience
Posted by
David Menninger on Jan 31, 2022 3:00:00 AM
I’m proud to share Ventana Research’s 2022 Market Agenda for Digital Technology. Our focus in this agenda is to deliver expertise to help organizations prioritize technology investments that increase workforce effectiveness and organizational agility, ensuring ongoing operations during any type of disruption.
0 Comments Click here to read/write comments
Topics: Analytics, Cloud Computing, Internet of Things, Data, Digital Technology
How does your organization define and display its metrics? I believe many organizations are not defining and displaying metrics in a way that benefits them most. If an organization goes through the trouble of measuring and reporting on a metric, the analysis ought to include all the information needed to evaluate that metric effectively. A number, by itself, does not provide any indication of whether the result is good or bad. Too often, the reader is expected to understand the difference, but why leave this evaluation to chance? Why not be more explicit about what results are expected?
0 Comments Click here to read/write comments
Topics: Analytics, Business Intelligence, Internet of Things, Data, Digital Technology, AI and Machine Learning, Streaming Analytics
