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: Big Data, Predictive Analytics, Software as a Service, IT Analytics & Performance, Operational Performance, Analytics, Business Analytics, Business Intelligence, Business Performance, Cloud Computing, Information Management, Operational Intelligence, Data, Information Optimization
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: ERP, Office of Finance, Reporting, close, closing, Controller, dashboard, Tax, Analytics, Business Intelligence, Business Performance, Cloud Computing, Collaboration, Financial Performance, CFO, Data, finance, Financial Performance Management, FPM
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: Big Data, Microsoft, Predictive Analytics, SAS, Social Media, alteryx, Customer Performance, Operational Performance, Analytics, Business Analytics, Business Intelligence, Business Performance, Operational Intelligence, Oracle, Information Optimization, SPSS, Rapidminer
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: Big Data, Sales Performance, Social Media, Customer Analytics, Customer Experience, Marketing, Mobile Technology, Speech Analytics, Wearable Computing, Customer Performance, Analytics, Business Analytics, Cloud Computing, Customer Service, Call Center, Contact Center, Contact Center Analytics, CRM, Text Analytics
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: Big Data, Microsoft, Predictive Analytics, SAS, Social Media, alteryx, Customer Performance, Operational Performance, Analytics, Business Analytics, Business Intelligence, Operational Intelligence, Oracle, Information Optimization, SPSS, Rapidminer
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: Customer Analytics, Customer Experience, Customer Feedback Management, Speech Analytics, Voice of the Customer, Customer Performance, Analytics, Business Analytics, Cloud Computing, Customer Service, Call Center, Contact Center, Text Analytics
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: Big Data, Sales Performance, Software as a Service, Mobile Technology, Customer Performance, Operational Performance, Analytics, Business Analytics, Business Collaboration, Business Intelligence, Business Mobility, Cloud Computing, Information Management, Operational Intelligence, Data