For years I’ve viewed with skepticism the claim that one technology or another will reduce audit costs. For one, there’s rarely a silver bullet. An array of moving parts drive audit fees. For example, the complexity of the corporation, accounting data management and the audit staff’s familiarity with the industry and the company all affect the time auditors must spend. Also, most of the time I’ve found that achieving significant savings was not the result of going from good to great, but from fixing deep-seated issues. If a company’s books and accounting practices are a mess, it can achieve considerable savings simply by cleaning up its act. In this circumstance, technology can play a part of a broader initiative that addresses the people, process and data management elements that are behind the mess.
The traditional office of finance has five main organs: accounting keeps the books; financial planning and analysis (FP&A) analyzes performance and manages the forward-looking activities of the company such as planning, budgeting and forecasting; corporate finance raises outside money; treasury takes care of the cash and bank accounts, and tax. The modern office of finance requires a sixth: Finance IT (FIT).
Topics: Office of Finance, Analytics, Financial Performance Management, Price and Revenue Management, Digital Technology, Operations & Supply Chain, ERP and Continuous Accounting, blockchain, robotic finance, Predictive Planning, Conversational Computing, AI and Machine Learning, revenue and lease accounting, collaborative computing, subscription management
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