The concept and implementation of what is called big data are no longer new, and many organizations, especially larger ones, view it as a way to manage and understand the flood of data they receive. Our benchmark research on big data analytics shows that business intelligence (BI) is the most common type of system to which organizations deliver big data. However, BI systems aren’t a good fit for analyzing big data. They were built to provide interactive analysis of structured data sources using Structured Query Language (SQL). Big data includes large volumes of data that does not fit into rows and columns, such as sensor data, text data and Web log data. Such data must be transformed and modeled before it can fit into paradigms such as SQL.
Topics: Analytics, Business Analytics, Business Intelligence, Business Performance, Data, Information Management, Information Optimization, IT Analytics & Performance, Operational Intelligence, Operational Performance, Predictive Analytics, Software as a Service, Big Data, Cloud Computing
Many senior finance executives say they want their department to play a more strategic role in the management and operations of their company. They want Finance to shift its focus from processing transactions to higher-value functions in order to make more substantial contributions to the success of the organization. I use the term “continuous accounting” to represent an approach to managing the accounting cycle that can facilitate the shift by improving the performance of the accounting function. Continuous accounting embraces three main principles:
Topics: Analytics, Business Intelligence, Business Performance, CFO, close, closing, Collaboration, Controller, dashboard, Data, ERP, finance, Financial Performance, Financial Performance Management, FPM, Reporting, Tax, Office of Finance, Cloud Computing
One of the key findings in our latest benchmark research into predictive analytics is that companies are incorporating predictive analytics into their operational systems more often than was the case three years ago. The research found that companies are less inclined to purchase stand-alone predictive analytics tools (29% vs 44% three years ago) and more inclined to purchase predictive analytics built into business intelligence systems (23% vs 20%), applications (12% vs 8%), databases (9% vs 7%) and middleware (9% vs 2%). This trend is not surprising since operationalizing predictive analytics – that is, building predictive analytics directly into business process workflows – improves companies’ ability to gain competitive advantage: those that deploy predictive analytics within business processes are more likely to say they gain competitive advantage and improve revenue through predictive analytics than those that don’t.
Topics: alteryx, Analytics, Big Data, Business Analytics, Business Intelligence, Business Performance, Customer Performance, Information Optimization, Microsoft, Operational Intelligence, Operational Performance, Oracle, Predictive Analytics, Rapidminer, SAS, Social Media, SPSS
I recently attended my first U.S. Dreamforce, the annual salesforce.com event designed to showcase its products and services as well as those of its partners, and I was impressed. I was told that Dreamforce ‘15 would be big, and it was – just about every hotel, restaurant, meeting room in San Francisco seemed to have been taken over for the week, and still the company had to bring in a cruise ship to accommodate people and events. I was told it would be manic, and it was – more than 100,000 attendees, and buses and cabs blocking surrounding streets. I was told it would be busy, and it was – more than 600 conference sessions. I was told it would educational, and it was – I gained many insights into new product developments, both from salesforce and several of its partners. Here are some of the key takeaways for my research practice.
Topics: Analytics, Big Data, Business Analytics, Call Center, Cloud Computing, Contact Center, Contact Center Analytics, CRM, Customer Analytics, Customer Performance, Customer Service, Marketing, Mobile Technology, Sales Performance, Social Media, Speech Analytics, Text Analytics, Wearable Computing, Customer Experience
Our benchmark research into predictive analytics shows that lack of resources, including budget and skills, is the number-one business barrier to the effective deployment and use of predictive analytics; awareness – that is, an understanding of how to apply predictive analytics to business problems – is second. In order to secure resources and address awareness problems a business case needs to be created and communicated clearly wherever appropriate across the organization. A business case presents the reasoning for initiating a project or task. A compelling business case communicates the nature of the proposed project and the arguments, both quantified and unquantifiable, for its deployment.
Topics: alteryx, Analytics, Big Data, Business Analytics, Business Intelligence, Customer Performance, Information Optimization, Microsoft, Operational Intelligence, Operational Performance, Oracle, Predictive Analytics, Rapidminer, SAS, Social Media, SPSS
ResponseTek is a software vendor whose platform and services help companies collect and act on feedback from their customers. It supports a closed-loop process that collects feedback, analyzes it, provides customizable reports and analysis dependent on the user, and most importantly enables taking action based on the information. This allows companies to understand product and service issues, customer sentiment, intentions, and likely behaviors, and where necessary ensures the most appropriate actions are taken.
Topics: Analytics, Business Analytics, Call Center, Cloud Computing, Contact Center, Customer Analytics, Customer Feedback Management, Customer Performance, Customer Service, Speech Analytics, Text Analytics, Voice of the Customer, Customer Experience
As I discussed in the state of data and analytics in the cloud recently, usability is a top evaluation criterion for organizations in selecting cloud-based analytics software. Data access of cloud and on-premises systems are essential antecedents of usability. They can help business people perform analytic tasks themselves without having to rely on IT. Some tools allow data integration by business users on an ad hoc basis, but to provide an enterprise integration process and a governed information platform, IT involvement is often necessary. Once that is done, though, using cloud-based data for analytics can help, empowering business users and improving communication and process .
Topics: Analytics, Business Analytics, Business Collaboration, Business Intelligence, Business Mobility, Cloud Computing, Customer Performance, Data, Information Management, Mobile Technology, Operational Intelligence, Operational Performance, Sales Performance, Software as a Service, Big Data