Until recently most organizations deployed systems on their own premises to build communications and contact center infrastructures, which often required them to integrate products from several vendors. In the past few years many vendors have moved their systems to the cloud, and others have begun as cloud-based suppliers. This trend has opened up the opportunity for more organizations to take advantage of modern communication systems and contact centers. Using the cloud for either, or both can save money and resources, reduce risk, and make available more integrated, multi-channel systems. While the adoption of such systems has undoubtedly increased and is likely to continue to do so, our benchmark research into next-generation contact centers in the cloud finds that many organizations still prefer to remain on premises, and adoption of cloud-based systems occurs on a case-by-case basis. In addition, many organizations look for vendors that support multiple models so they have the option of starting out using one model but transitioning later to another, including to a hybrid model in which some systems are on-premises and others are cloud-based..
Topics: Big Data, Mobile, Customer Analytics, Customer Engagement, Customer Experience, Machine Learning, Wearable Computing, cloud computing, Business Intelligence, Collaboration, Internet of Things, Contact Center, workforce optimization, analytics, Digital Commerce, Subscription Billing
Big data initially was characterized in terms of “the three V’s,” volume, velocity and variety. Nearly five years ago I wrote about the three V’s as a way to explain why new and different technologies were needed to deal with big data. Since then the industry has tackled many of the technical challenges associated with the three V’s. In 2017 I propose that we focus instead on a different letter, which includes these A’s: analytics, awareness, anticipation and action. I’ll explain why each is important at this stage of big data evolution.
Senior finance executives and finance organizations that want to improve their performance must recognize the value of technology as a key tool for doing high-quality work. Consider how poorly your organization would perform if it had to operate using 25-year-old software and hardware. Having the latest technology isn’t always necessary, but it’s important for executives to understand that technology shapes a finance organization’s ability to improve its overall effectiveness.
Topics: Big Data, data science, Mobile, Mobile Technology, Office of Finance, cloud computing, Continuous Planning, revenue recognition, Business Intelligence, Collaboration, analytics, Financial Performance Management, recurring revenue, Price and Revenue Management, Inventory Optimization, Billing and Recurring Revenue, Operations & Supply Chain, Enterprise Resource Planning, Sales and Operations Planning, Machine Learning and Cognitive Computing, ERP and Continuous Accounting, Collaboration for Business
Ventana Research analysts recently published our research agendas for 2017. As we put together these plans we think about the forces that are shaping the markets that we cover and then craft agendas that study these issues to provide insights for our community. I’ve been working in the business intelligence (BI) and analytics market for nearly 25 years, and throughout that time the industry has been trying to make analytics useful to increasingly wider audiences. That focus continues to today. Better search and presentation methods, including visual discovery and natural-language processing, are promising ways to engage more users. We also see organizations supporting their users in specific functional roles with relevant and accessible analytics. My colleagues examine these issues as part of their agendas in the Office of Finance, Sales, Marketing, Customer Experience, Operations and Supply Chain, and Human Capital Management. While their agendas include analytics within specific domains, my own research focuses on a range of analytics issues across domains including cloud computing, mobility, collaboration, data science and the Internet of Things.
Topics: Big Data, data science, Mobile Technology, cloud computing, Business Intelligence, Collaboration, Internet of Things, analytics, Machine Learning and Cognitive Computing, Machine Learning Digital Technology, Collaboration for Business
The business intelligence market is bounded on one side by big data and on the other side by data preparation. That is, to maximize their performance in using information, organizations have to collect and analyze ever increasing volumes of data while the tools available are constantly evolving in the big data ecosystem that I have written about. In our benchmark research on big data analytics, half (51%) of organizations said they want to access big data using their existing BI tools. At the same time, as I have noted, end users are demanding self-service access to data preparation capabilities to facilitate their analyses.