The use of blockchain distributed ledgers in business processes is now a common theme in many business software vendors’ presentations. The technology has a multitude of potential uses. However, presentations about the opportunities for digital transformation always leave me wondering: How is this magic going to happen? I wonder this because the details about how data flows from point A to point B via a blockchain are critically important to blockchain utility and therefore the pace of its adoption.
Topics: Planning, Continuous Planning, Integrated Business Planning, FP&A, budget, Budgeting, Forecast, forecasting, Predictive Analytics, Analytics, Reporting, consolidating, Data Management, AI, Machine Learning, Cognitive Computing
Ventana Research uses the term “predictive finance” to describe a forward-looking, action-oriented finance organization that places emphasis on advising its company rather than fulfilling the traditional roles of a transactions processor and reporter. Technology is driving the shift away from the traditional bean-counting role. The cumulative evolution of software advances will substantially reduce finance and accounting workloads by automating most of the mechanical, rote functions in accounting, data preparation and reporting. (I recently summarized these in a “Robotic Finance”)
Topics: Planning, Continuous Planning, Integrated Business Planning, FP&A, budget, Budgeting, Forecast, Predictive Analytics, Analytics, Reporting, Data Management, AI, Machine Learning, Cognitive Computing
Ventana Research defines financial performance management (FPM) as the process of addressing often overlapping issues involving people, process, information and technology that affect how well finance organizations operate and support the activities of the rest of their organization. FPM software supports and automates the full cycle of finance department activities, which include planning and budgeting, analysis, assessment and review, closing and consolidation, internal financial reporting and external financial reporting, as well as the underlying information technology systems that support them.
Using information technology to make data useful is as old as the Information Age. The difference today is that the volume and variety of available data has grown enormously. Big data gets almost all of the attention, but there’s also cryptic data. Both are difficult to harness using basic tools and require new technology to help organizations glean actionable information from the large and chaotic mass of data. “Big data” refers to extremely large data sets that may be analyzed computationally to reveal patterns, trends and associations, especially those related to human behavior and interaction. The challenges in dealing with big data include having the computational power that can scale to the processing requirements for the volumes involved; analytical tools to work with the large data sets; and governance necessary to manage the large data sets to ensure that the results of the analysis are accurate and meaningful. But that’s not all organizations have to deal with now. I’ve coined the term “cryptic data” to focus on a different, less well known sort of data challenge that many companies and individuals face.
Topics: Analytics, Budgeting, Business Analytics, Business Performance, Business Performance Management (BPM), Connotate, cryptic, data science, Datawatch, equity research, Finance Analytics, Financial Performance, Financial Performance Management (FPM), FP&A, Human Capital, Kapow, Kofax, Marketing, Office of Finance, Operational Performance, Operational Performance Management (OPM), Planning, Predictive Analytics, Sales Performance, Sales Performance Management (SPM), Social Media, Statistics, Supply Chain Performance, Big Data
The ERP market is set to undergo a significant transformation over the next five years. At the heart of this transformation is the decade-long evolution of a set of technologies that are enabling a major shift in the design of ERP systems – the most significant change since the introduction of client/server systems in the 1990s. Some ERP software vendors increasingly are utilizing in-memory computing, mobility, in-context collaboration and user interface design to differentiate their applications from rivals and potentially accelerate replacement of existing systems (as I noted in an earlier analyst perspective). ERP vendors with software-as-a-service (SaaS) subscription offerings are investing to make their software suitable for a broader variety of users in multitenant clouds. And some vendors will be able to develop lower-cost business systems to broaden the appeal of single-tenant hosted cloud deployments for companies that cannot adapt their businesses to share with other tenants or prefer not to.
Topics: Analytics, Business Analytics, Business Performance, Consolidation, ERP, Financial Performance, Financial Performance Management, FP&A, FPM, Human Capital, Performance Management, Reconciliation, Reporting, Uncategorized, Office of Finance