More businesses are using software to implement and support a strategic pricing strategy designed to optimize revenue and margins in business-to-business (B2B) transactions because it can help improve results at the bottom line. “Optimize” in this instance means managing the trade-off that usually exists between revenue and profitability objectives in order to support a company’s strategy and capabilities in a given market. Business-to-business pricing management is Ventana Research’s term for such processes and applications. Software built for this purpose centralizes control and enforces consistency in pricing while assisting sales agents in negotiating prices that achieve desired business objectives. It enables agents to use techniques that can increase the revenue from a transaction, the margin on the sale or the probability of closing the sale.
Topics: Big Data, data science, Office of Finance, cloud computing, Sales Performance Management, analytics, Financial Performance Management, sales, Price and Revenue Management, Pricing and Promotion Management, Sales Enablement and Execution, ERP and Continuous Accounting
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
Big data has become an integral part of information management. Nearly all organizations have some need to access big data sources and produce actionable information for decision-makers. Recognizing this connection, we merged these two topics when we put together our recently published research agendas for 2017. As we plan our research, we focus on current technologies and how they can be used to improve an organization’s performance. We then share those results with our readers.
Topics: Big Data, data science, Data Governance, Data Integration, Data Preparation, Information Management, Internet of Things, analytics, Machine Learning and Cognitive Computing, Machine Learning Digital Technology
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