Oracle recently held its second ERP Cloud Summit with industry analysts. The all-day event wasn’t just about ERP. The company covered a range of its business applications, including financial performance management as well as its Adaptive Intelligent Applications. And it wasn’t just about the cloud. After more than a decade of steady developments, ERP systems have begun to change fundamentally, facilitated by the growing availability of new technologies including cloud computing, advanced database architecture, collaboration, user interface design, mobility, analytics and planning. Here are my key takeaways from the event:
Topics: Big Data, data science, Mobile, Customer Experience, Human Capital Management, Machine Learning, Office of Finance, . cloud computing, revenue recognition, Analytics, Data Integration, Internet of Things, Cognitive Computing, HRMS, Financial Performance Management, Mobile Marketing Digital Commerce, Digital Marketing, Digital Commerce, Operations & Supply Chain, Enterprise Resource Planning, ERP and Continuous Accounting
Business process reengineering was a consulting fashion in the early 1990s that spurred many companies to purchase their first ERP systems. BPR proposes a fundamental redesign of core business processes to achieve substantial improvements in market and customer responsiveness, productivity, cycle times and quality. ERP systems support business process reengineering by guiding the step-by-step execution of the redesigned process to ensure that it is performed consistently. They also automate the handoffs between individuals and departments to accelerate completion of that process.
Topics: Big Data, data science, Mobile, Customer Analytics, Customer Experience, Machine Learning, Office of Finance, Wearable Computing, cloud computing, Continuous Planning, business intelligence, Analytics, Data Integration, Internet of Things, Financial Performance Management, digital technology, Digital Marketing, Mobile Marketing, Digital Commerce, Operations & Supply Chain, Enterprise Resource Planning, Machine Learning and Cognitive Computing, ERP and Continuous Accounting, Sales Planning and Analytics
More businesses are using software to implement and support a strategic pricing strategy designed to optimize revenue and margins in business-to-business (B2B) transactions because it can help improve results at the bottom line. “Optimize” in this instance means managing the trade-off that usually exists between revenue and profitability objectives in order to support a company’s strategy and capabilities in a given market. Business-to-business pricing management is Ventana Research’s term for such processes and applications. Software built for this purpose centralizes control and enforces consistency in pricing while assisting sales agents in negotiating prices that achieve desired business objectives. It enables agents to use techniques that can increase the revenue from a transaction, the margin on the sale or the probability of closing the sale.
Topics: Big Data, data science, Office of Finance, cloud computing, Sales Performance Management, Financial Performance Management, analytics, sales, Price and Revenue Management, Pricing and Promotion Management, Sales Enablement and Execution, ERP and Continuous Accounting
Senior finance executives and finance organizations that want to improve their performance must recognize the value of technology as a key tool for doing high-quality work. Consider how poorly your organization would perform if it had to operate using 25-year-old software and hardware. Having the latest technology isn’t always necessary, but it’s important for executives to understand that technology shapes a finance organization’s ability to improve its overall effectiveness.
Topics: Big Data, data science, Mobile, Mobile Technology, Office of Finance, cloud computing, Continuous Planning, revenue recognition, Business Intelligence, Collaboration, analytics, Financial Performance Management, recurring revenue, Price and Revenue Management, Inventory Optimization, Billing and Recurring Revenue, Operations & Supply Chain, Enterprise Resource Planning, Sales and Operations Planning, Machine Learning and Cognitive Computing, ERP and Continuous Accounting, Collaboration for Business
Price and revenue optimization (PRO) is a business discipline used to produce demand-based pricing; it applies market segmentation techniques to achieve strategic objectives such as increased profitability or greater market share. In essence, PRO enables companies to surf the demand curve using dynamic rather than fixed pricing to achieve the most desirable trade-offs between revenue volume and profit margins. The trade-off is defined by strategic factors such as the company’s market position, product and service portfolio, and marketing strategy.
Topics: Big Data, data science, Office of Finance, cloud computing, Sales Performance Management, analytics, Financial Performance Management, sales, Price and Revenue Management, Pricing and Promotion Management, Sales Enablement and Execution, ERP and Continuous Accounting
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: Big Data, data science, Planning, Predictive Analytics, Social Media, forecasting, FP&A, Office of Finance, Operational Performance Management (OPM), Budgeting, Connotate, cryptic, equity research, Finance Analytics, Human Capital, Kofax, Statistics, Analytics, Business Analytics, Hadoop, Business Intelligence (BI), Customer Performance Management (CPM), Data, Datawatch, Financial Performance Management (FPM), Kapow, Sales Performance Management (SPM), Supply Chain Performance Management (SCPM), import.io