AI, machine learning and predictive analytics are already driving big performance gains for CFOs and their teams. The ability for cognitive tools to learn at speed helps Finance progressively improve company intelligence and efficiency, including proactive identification of late- and non-paying customers. Get up to speed on the potential of cognitive, with Finance thought-leaders from Oracle and AICPA (American Institute of Certified Public Accountants).
It is important to understand the different business situations where traditional predictive analytics can be best applied and where anticipatory analytics may be a more appropriate approach to solve the business problem. One is not necessarily superior to the other – it’s about which methodology is best utilized in solving the specific business problem. Conventional response modeling, revenue potential modeling, wallet share analysis, traditional risk scoring and other analytic practices will always be important tools for businesses far-and-wide, but as more companies focus on analytics to inform growth, they’ll have employ the right team and identify the right partners to work with in order to successfully leverage anticipatory analytics to gain a competitive advantage.
Looking forward, we anticipate anticipatory analytics playing an important role in your future. Download this white paper to learn more.
From protecting customer experience to preserving lines of revenue, IT operations teams face increasingly complex responsibilities and are responsible for preventing outages that could harm the organization. As a Splunk customer, your machine data platform empowers you to utilize machine learning to reduce MTTR. Discover how six companies utilize machine learning and AI to predict outages, protect business revenue and deliver exceptional customer experiences.
Download the e-book to learn how:
Micron Technology reduced number of IT incidents by more than 50%
Econocom provides better customer service by centralizing once-siloed analytics, improving SLA performance and significantly reducing the number of events
TransUnion combines machine data from multiple applications to create an end-to-end transaction flow
Predictive IT is a powerful new approach that uses machine learning and artificial intelligence (AI) to predict incidents before they impact customers and end users. By using AI and predictive analytics, IT organizations are able to deliver seamless customer experiences that meet changing customer behavior and business demands. Discover the critical steps required to build your IT strategy, and learn how to harness predictive analytics to reduce operational inefficiencies and improve digital experiences.
Download this executive brief from CIO to learn:
5 steps to an effective predictive IT strategy
Where AI can help, and where it can’t
How to drive revenue and exceptional customer experiences with predictive analytics
Published By: BMC ESM
Published Date: Aug 20, 2009
There is a natural progression from reactive to proactive, and ultimately predictive technology, and this progression corresponds to the maturity level of your IT organization and the tools you leverage.
To address the volume, velocity, and variety of data necessary for population health management, healthcare organizations need a big data solution that can integrate with other technologies to optimize care management, care coordination, risk identification and stratification and patient engagement. Read this whitepaper and discover how to build a data infrastructure using the right combination of data sources, a “data lake” framework with massively parallel computing that expedites the answering of queries and the generation of reports to support care teams, analytic tools that identify care gaps and rising risk, predictive modeling, and effective screening mechanisms that quickly find relevant data. In addition to learning about these crucial tools for making your organization’s data infrastructure robust, scalable, and flexible, get valuable information about big data developments such as natural language processing and geographical information systems. Such tools can provide insig
Predictive analytics is powerful. It can help drive significant improvement to an organization’s bottom line. Look for ways to use it to grow revenue, shrink costs and improve margins.
Provide a platform that enables your data scientists to work efficiently using tools and algorithms they prefer. Enhance your analyses with internal and external data, structured and unstructured data. Then make the analytics accessible in order to reap the full benefits of these valuable analyses.
Stay ahead of the curve in your market with predictive analytics, and give your organization a competitive advantage and an improved bottom line.