Dreamforce has become the largest enterprise software event for businesses in the United States, and it is evident why when looking at it this year. With over 170,000 business and IT professionals attending, Salesforce came to show off upcoming product announcements and innovations. This year's biggest focus was on Einstein Voice (a personalized and intelligent conversational assistant), integration with other platforms, and Salesforce Customer 360. The last of these is the start of an answer to a problem we have well documented; businesses struggle getting a full view of the customer and provide a frictionless response to issues and interactions. For the full breakdown of Dreamforce 2018, and my analysis of all the largest announcements, watch my hot take video.
Topics: Customer Experience, digital technology, Digital Marketing, Marketing, Intelligent CX, Voice of the Customer, AI, Machine Learning, natural language processing, Robotic Process Automation, Sales Performance Management (SPM), SPM, CRM, Salesforce.com, Dreamforce
We now are well beyond the year depicted in 2001: A Space Odyssey, a cinematic perspective on the future of artificial intelligence in which HAL 9000, a computer, is able to simulate human behavior and control machines. Anyone reviewing the past two years of marketing around AI in the business technology industry can be forgiven for believing that we have arrived at the futuristic state Stanley Kubrick imagined. We have not.
Topics: Analytics, business intelligence, Cloud Computing, Collaboration, data science, Internet of Things, Mobile, Big Data, Data Integration, Data Governance, Data Preparation, Information Optimization, Machine Learning, Customer Experience, Billing and Recurring Revenue, Contact Center, Customer Analytics, Customer Engagement, Customer Service, Workforce Optimization, digital technology, collaboration for business, Cybersecurity, Machine Learning and Cognitive Computing, Mobile Technology, Wearable Computing
Advancing the potential of any business requires continuous improvement in the processes and technology that support it. Many companies have embraced attempts at a digital transformation, and it’s become a goal to which organizational resources and budgets have been dedicated around the globe.
Topics: Analytics, Business Intelligence, Cloud Computing, Collaboration, data science, Internet of Things, Mobile, Big Data, Data Integration, Data Governance, Data Preparation, Information Optimization, Machine Learning, Customer Experience, Billing and Recurring Revenue, Contact Center, Customer Analytics, Customer Engagement, Customer Service, Workforce Optimization, digital technology, collaboration for business, Cybersecurity, Machine Learning and Cognitive Computing, Mobile Technology, Wearable Computing, Human Capital Management, Marketing, Digital Marketing, Digital Commerce, Marketing Performance Management, Pricing and Promotion Management, Product Information Management, Office of Finance, Operations & Supply Chain, Sales
If we look at the focus of technology vendors for analytics and business intelligence or business applications providers deploying these capabilities in the last five years, we see that they have elevated the importance on the value of visualization and dashboards. These promotions might be understandable, but will they make business and the people using them more intelligent?
The importance of analytics for sales organizations is clear and, as I pointed out in my recent analyst perspective on the next generation of sales analytics, these capabilities optimize revenue potential. However, utilizing sales analytics requires a set of data skills that most organizations still find challenging and are thus not fully prepared to support. The efficient access and preparation of data underlies any analytics processes, which must meet demanding needs that are not always automated. Our research into next generation sales analytics has found many impediments that must be addressed and is a critical part of our expertise agenda for sales organizations.
Topics: Analytics, Machine Learning, digital technology, Big Data, Cloud Computing, Machine Learning and Cognitive Computing, Product Information Management, Sales and Operations Planning, Sales, Digital Commerce, Sales Enablement and Execution, Sales Performance Management, Sales Planning and Analytics, Office of Finance, Collaboration
Cloudera provides database and enabling technology for the big data market and overall for data and information management. As my colleague David Menninger has written, the big data and information management technology markets are changing rapidly and require vendors to adapt to them. Cloudera has grown significantly over the last decade and now has approximately 1,000 customers and provides support and services in countries around the world. Its product and technology strategy is to provide a unified data management platform, Cloudera Enterprise, that can meet the data engineering and science needs for a range of analytic and operational database applications. Its primary focus is its Enterprise Data Hub, which as a data lake can handle organizations’ big data and analytical needs. As David Menninger asserts, the data lake is a safe way to invest in big data. It also helps shift the focus away from the V’s (volume, velocity and variety) of big data to the A’s, which are analytics, awareness, anticipation and action.
Topics: Business Intelligence, data science, Internet of Things, Big Data, Data Integration, Data Governance, Data Preparation, Information Optimization, Machine Learning, digital technology, Cybersecurity, Cognitive Computing, Analytics, Cloud Computing
I am happy to provide my personal perspective on the potential of sales organizations, processes and technology to supercharge business activity in 2017. The sales processes of organizations – whether they involve digital commerce or direct or indirect physical selling – should be part of continuous optimization efforts to reach maximum results. To do this, the people leading and running sales processes must be able to use technology that supports their responsibilities and analyzes the crucial information coming into the business. For almost 15 years, we have advocated for sales applications and tools that are necessary to optimize sales effectiveness and improve the outcomes of their sales efforts. The available portfolio is much larger than sales force automation (SFA) and involves more than the continued use of CRM, which has clear limits in its ability to manage customer relationships. The applications on offer include many facets of sales: coaching, compensation management, contract management, configure price quote (CPQ), forecasting, quota and territory management, planning and optimization, pricing and revenue optimization, and target or market intelligence. New applications designed for sales also enable digital effectiveness that can transform organizations. Let me provide my perspective on six topics that are shaping the way sales can and should operate in 2017, and which are part of our sales research agenda for the year.
Topics: Machine Learning, digital technology, Big Data, Machine Learning and Cognitive Computing, Mobile Technology, Operations & Supply Chain, Product Information Management, Sales and Operations Planning, Sales, Digital Commerce, Sales Enablement and Execution, Sales Performance Management, Analytics, Office of Finance, Cloud Computing, Collaboration
IBM Watson blends existing and innovative technology into a new approach called cognitive computing. At the simplest operational level it is technology for asking natural language-based questions, getting answers and support appropriate action to be taken or provide information to make more informed decisions. The technology relies on massive processing power to yield probabilistic responses to user questions using sophisticated analytical algorithms. A cognitive system like Watson accesses structured and unstructured information within an associated knowledge base to return responses that are not simply data but contextualized information that can inform users’ actions and guide their decisions. This is a gigantic leap beyond human decision-making using experience based on random sources from the industry and internal sets of reports and data.
Topics: Big Data, Business Analytics, Business Performance Management (BPM), Cognitive Computing, Customer Performance Management (CPM), Financial Performance Management (FPM), IBM, IBM Watson, Information Management (IM), IT Performance Management (ITPM), Machine Learning, Operational Performance Management (OPM), Sales Performance Management (SPM), Supply Chain Performance Management (SCPM), Workforce Performance Management (WPM), Business Intelligence, Expert Systems