IBM Planning Analytics with Watson is a comprehensive, cloud-based business planning application that supports what Ventana Research calls integrated business planning. We coined this term in 2007 to describe a high-participation approach to business planning that integrates strategy, operations and finance. Our Next Generation Business Planning Benchmark Research demonstrated the value of IBP: Organizations that link planning processes get better results. Sixty-six percent of organizations that have an integrated method say it works well or very well, compared to only 25% that have little or no connection between plans.
Topics: Predictive Analytics, Office of Finance, business intelligence, embedded analytics, Business Planning, Financial Performance Management, Watson, Digital transformation, AI and Machine Learning, profitability management
The use of artificial intelligence (AI) using machine learning (ML) will be the single most important trend in business software this decade because it can multiply the investment value of such applications and provide vendors an important source of differentiation to achieve a competitive advantage in what are today very mature software categories. I assert that by 2025, almost all Office of Finance software vendors will have incorporated some AI capabilities to reduce workloads and improve performance. However, software vendors will be challenged to apply innovations in this area quickly while ensuring that the AI capabilities function well enough in the real world to foster rapid adoption while avoiding user frustration. The failures of the Apple Newton and Microsoft’s Clippy office assistant stand out as examples of too-ambitious-too-soon attempts at infusing intelligent automation.
Unit4’s Financial Planning and Analysis (formerly Prevero) is a planning and budgeting application designed for the requirements of midsize corporations and the public sector. These organizations are challenged in buying software because they have almost all the requirements of larger enterprises but have a smaller budget and limited technical resources.
Topics: Office of Finance, embedded analytics, Analytics, Business Intelligence, Business Planning, Financial Performance Management, Price and Revenue Management, Digital Technology, ERP and Continuous Accounting, AI and Machine Learning, collaborative computing
IBM Planning Analytics, formerly known as TM1, is a comprehensive planning and analytics application designed to integrate and streamline an organization’s planning processes. It can support multiple planning use cases on a single platform, including financial, headcount, sales and demand planning. The software automates enterprise-wide data collection to make it repeatable and scalable across multiple users and departments. It supports sophisticated driver-based modeling that enables rapid what-if or scenario-based planning, while its built-in analytics provide deep business intelligence capabilities. This enables senior executives and managers to work interactively to immediately assess their current position and consider the impact of various options to address opportunities and issues rather than laboring through a lengthy process.
The financial planning and analysis (FP&A) group is the linchpin of any transformation effort in the Office of Finance. Our recently completed Office of Finance benchmark research was conducted against the backdrop of the idea that finance organizations must play a more strategic role in the management of the modern organization. This transformation envisions a finance department that’s more of a partner to the rest of the company — one that is less focused on “bean counting,” instead directing its resources and energy to providing more insightful analytics, facilitating transactions of value and communicating actionable data analyses that enable managers to make better decisions more consistently. The research uncovered advances in how corporations handle analytics as well as budgeting and planning. Yet the research also indicates that there is much left to be done in most companies.
By itself, data isn’t useful for business; the application of analytics is necessary to transform data into actionable information. Data analysis of one sort or another has long been a core competence of finance departments, applied to balance sheets, income statements or cash flow statements. Today, however, Finance must go beyond these basics by expanding the scope of the data being examined to include all financial and operational information that can yield actionable insights. Analysis thus should include, for example, data from the systems that manage sales operations, human resources and field service and that data must be available to all departments and applications that need it.
Topics: Customer Experience, Human Capital Management, Marketing, Voice of the Customer, business intelligence, embedded analytics, Learning Management, Analytics, Collaboration, Data Governance, Data Lake, Data Preparation, Information Management, Internet of Things, Contact Center, Data, Product Information Management, Sales Performance Management, Workforce Management, Financial Performance Management, Price and Revenue Management, Digital Technology, Digital Marketing, Digital Commerce, ERP and Continuous Accounting, blockchain, natural language processing, robotic finance, Predictive Planning, candidate engagement, Intelligent CX, Conversational Computing, Continuous Payroll, AI and Machine Learning, revenue and lease accounting, collaborative computing, mobile computing, subscription management, agent management, extended reality