In 2016 Unit4 acquired Prevero, a financial performance management software company. The acquisition reflects a trend toward the convergence of transactional and analytical business applications. ERP and financial management software vendors increasingly are adding analytic capabilities – especially in financial performance management (FPM) – to the core functions of transaction processing and accounting in order to broaden the scope of their offerings. The integration of transaction processing and analytical software is especially valuable to Unit4’s core customer base of midsize organizations, which we define as those with 100 to 1,000 employees. Midsize entities have almost the same systems requirements as larger ones but lack the resources the latter enjoy.
Topics: Marketing, Office of Finance, Continuous Planning, Analytics, Business Intelligence, Cloud Computing, Collaboration, Workforce Management, Financial Performance Management, FPM, Work and Resource Management, Operations & Supply Chain, Sales Planning and Analytics
Recently Hortonworks announced some significant additions to its products at the DataWorks Summit. These additions reflect the fact that the big data market continues to evolve, as I have previously written.
Centage recently released Budget Maestro Version 9, a complete revamping of its longstanding budgeting application designed for midsize companies. The software, now offered as a multitenant cloud-based offering, delivers several structural improvements that can enhance the effectiveness of a company’s planning processes and at the same time is easier to use. Budget Maestro Version 9 is designed to support what Centage is calling a “Smart Budgets” approach to replace traditional budgeting. This approach is consistent with what we have been calling integrated business planning.
Natural language generation (NLG), the process of generating text or narratives based on a set of data values, can reach a broader audience. NLG narratives can be used for a variety of purposes, but in this perspective I focus on how NLG can be used to enhance business intelligence (BI) processes. In the case of BI, NLG can be used to explain what has happened and why it is happening, and even what actions to take. The NLG narratives can be understood by a broader range of business users than the tables and charts of data that are the typical output of most BI applications or analytics tools.
Many organizations continue to struggle with preparing data for use in operational and analytical processes. We see these issues reported in our Data and Analytics in the Cloud benchmark research, where 55 percent of organizations identify data preparation as the most time-consuming task in their analytical processes. Similarly, in our Next-Generation Predictive Analytics research, 62 percent of companies report that they’re unsatisfied because data needed for access or integration is not readily available. In our Big Data Integration research, 52 percent report spending that in working with big data integration processes, they spend the most time reviewing data for quality and consistency. And nearly half of companies (48%) report this same issue in our Internet of Things research. We are currently conducting further research into this critical issue with our Data Preparation benchmark research.