Finance transformation” refers to a longstanding objective: shifting the focus of CFOs and finance departments from transaction processing to more strategic, higher-value functions. Our upcoming Office of Finance benchmark research confirms that most of organizations want their finance department to take a more strategic role in management of the company: nine in 10 participants said that it’s important or very important. (We are using “finance” in its broadest sense, including, for example, accounting, corporate finance, financial planning and analysis, treasury and tax functions.) Finance departments have the ability and at least an implicit mandate to improve business performance and enable a corporation to execute strategy more effectively. Yet the research shows that becoming strategic is a work in progress. Most departments handle the basics well, but half fall short in areas that can contribute significantly to the performance of their company. More than three-fourths of participants said they perform accounting, external financial reporting, financial analysis, budgeting and management accounting well or very well. But only half said that about their ability to do product and customer profitability management, strategic and long-range planning and business development.
Topics: Analytics, Big Data, Business Analytics, Business Collaboration, Business Performance, CFO, close, closing, Cloud Computing, Collaboration, computing, Controller, ERP, finance, Financial Performance, FP&A, FPM, Management, Mobile, Performance Management, Predictive Analytics, Reporting, Social Media, Tagetik, Tax, Office of Finance
When applying information technology to drive better business performance, companies and the systems integrators that assist them often underestimate the importance of organizing data management around processes. For example, companies that do not execute their quote-to-cash cycle as an end-to-end process often experience a related set of issues in their sales, marketing, operations, accounting and finance functions that stem from entering the same data into multiple systems. The inability to automate passing of data from one functional group to the next forces people to spend time re-entering data and leads to fragmented and disconnected data stores. The absence of a single authoritative data source also creates conflicts about whose numbers are “right.” Even when the actual figures recorded are identical, discrepancies can crop up because of issues in synchronization and data definition. Lacking an authoritative source, organizations may need to check for and resolve errors and inconsistencies between systems to ensure, for example, that what customers purchased was what they received and were billed for. The negative impact of this lack of automation is multiplied when transactions are complex or involve contracts for recurring services.
Topics: Analytics, Big Data, Business Performance, close, closing, computing, CRM, Data, Data Management, end-to-end, ERP, finance, FPM, Information Applications, Information Management, Management, Mobile, Operational Performance, Operations, Sales Performance, Supply Chain Performance, Office of Finance, Cloud Computing
“What’s next?” is the perennially insistent question in information technology. One common observation about the industry holds that cycles of innovation alternate between hardware and software. New types and forms of hardware enable innovations in software that utilize the power of that hardware. These innovations create new markets, alter consumer behavior and change how work is performed. This, in turn, sets the stage for new types and forms of hardware that complement these emerging product and service markets as well as the new ways of performing work, creating products and fashioning services that they engender. For example, the emerging collection of wearable computing devices seems likely to generate a new wave of software/hardware innovation, as my colleague Mark Smith has noted. This said, I think that the idea of alternating cycles no longer applies. It would be convenient if we could assign discrete time periods to hardware dominance and software dominance, but like echoes as they fade, the reverberations are no longer as neatly synchronized as they once were. Moreover, adoption and adaptation of technology by consumers reflected in the design of work, products and services always lags – and lags in different ways, further blurring the timing of cycles.
Topics: Analytics, Business Analytics, Business Collaboration, Business Performance, close, closing, Cloud Computing, computing, ERP, finance, Financial Performance, FPM, Management, Mobile, Operational Performance, Performance Management, Predictive Analytics, Reporting, Sales Performance, Supply Chain Performance, Wearable Computing, Workforce Performance, Office of Finance
IBM’s Big Data and Analytics Analyst Insights conference started me thinking about the longer-term potential impact of big data and related technologies on business management. I covered some of the near-term uses of big data and analytics in an earlier perspective. There are numerous uses of big data that can provide incremental improvements to existing processes and practices. Some of these will have a significant impact on changing business models, enabling new classes of products and services and improving performance. As well, the technology will have more profound, longer lasting effects. The ability to analyze large quantities of business-related data rapidly has the potential to set in motion fundamental changes in how executives and managers run their business. Properly deployed, it will enable a more forward-looking and agile management style even in very large enterprises. It will allow more flexible forms of business organization. None of these changes will be universal, and the old school will be with us for some time. Technology, however, will give executives and their boards of directors a powerful tool for strategic differentiation to achieve a sustainable competitive advantage.
Topics: Analytics, Big Data, Budgeting, Business Analytics, Business Collaboration, Business Intelligence, Business Performance, decision, FPM, IBM, Information Management, Management, Operational Performance, Planning, Predictive Analytics, Watson
I’ve frequently commented on the artificiality of the emerging software category of governance, risk and compliance (GRC). The term is used to a cover a combination of what were once viewed as stand-alone software categories, including IT governance, audit documentation and industry-specific compliance management, to name three examples. While it’s still common for specific types of software to be purchased piecemeal by different departments, these disparate areas have started a long convergence process. Since just about all controls and risk management efforts require a secure IT environment to be effective, there is a growing interdependence between effective IT governance and everything else connected with enterprise GRC.
Topics: Analytics, Business Performance, compliance, finance, Financial Performance, financial risk management, Governance, GRC, IT Risk Management, Management, Operational Performance, Performance Management, Predictive Analytics, Risk, Sarbanes Oxley, SOX, Customer Experience, Big Data