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
I’ve long advocated the use of effective technology in the tax function, especially for organizations that operate in multiple jurisdictions or have complex legal structures manage direct tax provision and analysis using outdated or inappropriate tools. Our Office of Finance benchmark research reveals that most organizations use spreadsheets to manage their tax provision and analysis: Half (52%) rely solely on spreadsheets, and another 38 percent mainly use them. I recommend to corporations that operate in multiple countries and that have even a moderately complex legal entity structure that they consider establishing what I call a tax data warehouse of record.
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.