Anaplan recently held Anaplan Hub, its annual user group meeting. The company offers a cloud-based business planning platform that incorporates a modeling and calculation engine. The tool makes it relatively easy to add or expand the scope of plans that can be connected and monitored as a central source. Companies typically use Anaplan software for financial planning or budgeting, sales, workforce, marketing and IT planning. These are the types of plans in which companies often need to create models that incorporate their specific requirements, their strategy and their business systems.
Topics: Customer Analytics, Marketing, Marketing Performance Management, Office of Finance, Recurring Revenue, cloud computing, Continuous Planning, revenue recognition, Business Intelligence, Collaboration, HRMS, Sales Performance Management, Workforce Management, analytics, Financial Performance Management, Price and Revenue Management, Work and Resource Management, Operations & Supply Chain, Sales Enablement and Execution, ERP and Continuous Accounting, Sales Planning and Analytics
Some 3,000 people attended Domo’s recent customer event, called Domopalooza. That’s nearly double the attendance of the previous event, which my colleague Mark Smith covered. Formerly a bit “stealthy,” Domo has started sharing more information, some of which I’ll pass along, as well as observations about product announcements made at the event.
Topics: data science, Mobile, Mobile Technology, cloud computing, Business Intelligence, Collaboration, analytics, Machine Learning and Cognitive Computing, Machine Learning Digital Technology, Collaboration for Business
Business process reengineering was a consulting fashion in the early 1990s that spurred many companies to purchase their first ERP systems. BPR proposes a fundamental redesign of core business processes to achieve substantial improvements in market and customer responsiveness, productivity, cycle times and quality. ERP systems support business process reengineering by guiding the step-by-step execution of the redesigned process to ensure that it is performed consistently. They also automate the handoffs between individuals and departments to accelerate completion of that process.
Topics: Big Data, data science, Mobile, Customer Analytics, Customer Experience, Machine Learning, Office of Finance, Wearable Computing, cloud computing, Continuous Planning, Business Intelligence, Data Integration, Internet of Things, analytics, Financial Performance Management, digital technology, Digital Marketing, Mobile Marketing, Digital Commerce, Operations & Supply Chain, Enterprise Resource Planning, Machine Learning and Cognitive Computing, ERP and Continuous Accounting, Sales Planning and Analytics
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.