We live in a time of uncertainty, not unpredictability. Especially when a business finds itself on an undefined journey with an unclear destination—whether caused by internal events or the world at large—having plans to deal with a range of outcomes increases the odds of success. Or, at least enduring the least amount of damage. Managing an organization in uncertain times is always hard, but tools are available to improve the odds of success by making it easier and faster to plan for...
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Topics:
Machine Learning,
Office of Finance,
Supply Chain Planning,
Business Planning,
Supply Chain,
Enterprise Resource Planning,
Artificial intelligence,
digital finance,
Generative AI
Founded as Software Development Laboratories in 1977, Oracle is a behemoth in the software industry, generating more than $50 billion in revenue in its fiscal year 2024. Originally focused solely on the relational database market, the software provider operated as Relational Systems, Inc. for several years before adopting the name Oracle in 1982. The company went public in 1986 and became one of the largest software providers in the world, eventually amassing a large portfolio of business...
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Topics:
Machine Learning,
Artificial intelligence,
Data Platforms,
Generative AI
As enterprises seek to expand and accelerate the adoption of artificial intelligence (AI) many are finding that longstanding analytics and data challenges are a barrier to success. As was explained in ISG’s State of Generative AI Market Report, AI requires data that is clean, well-organized and compliant with regulatory standards. The need for good data management is by no means new, but the expectations and demands associated with AI are a forcing function for enterprises to take long-overdue...
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Topics:
Machine Learning,
Analytics,
Data,
Artificial intelligence,
natural language processing
AI, like analytics, must lead to action. Too often, in both cases, too much of the exercise is left to the reader. We have tools to provide sophisticated analyses, including AI platforms that can be used to predict many types of behavior, but we fall short in helping the workforce know what to do with that information. Some examples are more obvious, such as fraud detection. If a transaction is predicted to be fraudulent, the transaction should be blocked. But even this example is not as cut...
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Topics:
Artificial intelligence
In the technology industry, 2023 will be remembered as the year of generative artificial intelligence. Yes, the world was made aware of GenAI when ChatGPT was publicly launched in November of 2022, but few knew the impact it would have at that point in time. Since then, GenAI has taken the world by storm, with vendors applying the technology to make it easier to ask questions about data, write code (including SQL), prepare data for analyses, document data pipelines and use software products...
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Topics:
Artificial intelligence,
Analytics and Data,
AI and Machine Learning
I have previously written about the impact of intelligent operational applications on the requirements for data platforms. Intelligent applications are used to run the business but also deliver personalization, recommendations and other features generated by machine learning and artificial intelligence. As such, they require a combination of operational and analytic processing functionality. The emergence of these intelligent applications does not eradicate the need for separate analysis of...
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Topics:
Analytics,
Artificial intelligence,
Analytics and Data,
AI and Machine Learning
Unstructured data has been a significant factor in data lakes and analytics for some time. Twelve years ago, nearly a third of enterprises were working with large amounts of unstructured data. As I’ve pointed out previously, unstructured data is really a misnomer. The data is structured; it's just not structured into rows and columns that fit neatly into a relational table like much of the other information enterprises process. Consequently, it requires different skills, different technology...
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Topics:
Artificial intelligence,
Computer Vision,
Analytics and Data,
AI and Machine Learning
We’ve been saying for years that natural language processing (NLP) and natural language analytics would greatly expand access to analytics. However, prior to the explosion of generative AI (GenAI), software providers had struggled to bring robust natural language capabilities to market. It required considerable manual effort. Many analytics providers had introduced natural language capabilities, but they didn’t really resonate with enterprise requirements. They required significant effort to...
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Topics:
business intelligence,
Artificial intelligence,
natural language processing,
Analytics and Data
Ventana Research recently announced its 2024 Market Agenda for Artificial Intelligence, continuing the guidance we have offered for two decades to help enterprises derive optimal value from technology and improve business outcomes.
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Topics:
Artificial intelligence,
natural language processing,
Model Building and Large Language Models,
Computer Vision
Roughly half of my more than 30-year career in human capital management was spent as a line manager responsible for HR technology strategy, selection and deployment. I learned a number of lessons during these years — some just in time, some after the fact. If I had to identify one common thread that unites these insights, it would be that inadequate attention to change management is an ROI-killer on these strategic initiatives every time.
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Topics:
Human Capital Management,
Learning Management,
Analytics,
Workforce Management,
Digital Technology,
Artificial intelligence,
Total Compensation Management,
Continuous Payroll
Learning management technology, either as part of a larger HCM software suite or as a standalone niche solution, has evolved from its classroom-based, instructor-led origins. Modern systems deliver information the way many employees learn best, through informal social learning that is personalized and engaging. Some of these new, often mobile-enabled approaches deliver education via short (three to five minute) on-demand videos that are tailored to an individual’s specific job responsibilities...
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Topics:
Human Capital Management,
Learning Management,
HRMS,
Workforce Management,
Digital Technology,
Work and Resource Management,
Machine Learning and Cognitive Computing,
Artificial intelligence,
employee experience,
Chatbots,
Personalization,
Predictive HCM
The early days of my career were spent in HR and payroll systems inside brokerage houses and investment banks. The first CHRO I reported to thought the best way to develop a plan for automating payroll management was for me to run the function’s day-to-day operations. I had no previous experience in payroll but it was a good call, as the trenches of any operations area typically reveal a cornucopia of automation opportunities. Then again, it was a different time; back then the words strategy,...
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Topics:
Human Capital Management,
HRMS,
Workforce Management,
Digital Technology,
Work and Resource Management,
Machine Learning and Cognitive Computing,
Payroll Optimization,
Artificial intelligence,
Total Compensation Management,
RPA,
employee experience,
Chatbots,
Personalization,
Predictive HCM
After more than a decade of steady development, ERP systems today are changing fundamentally, facilitated by the availability of advances such as cloud computing, advanced database architecture, collaboration, improved user-interface design, mobility, analytics and planning. This was evident when Oracle recently held its third analysts-only ERP Cloud Summit in New York to coincide with its Modern Finance Experience event. Oracle now has an increasingly robust set of business applications that...
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Topics:
ERP,
Machine Learning,
Cloud Computing,
Robotic Process Automation,
Artificial intelligence,
blockchain,
AI
SAP recently held a teleconference to highlight its blockchain strategy. Lately, the major business software vendors have been calling attention to their blockchain initiatives. While the focus on this technology might seem premature to those who still equate it with cryptocurrencies, evidence is pointing to a future pace of adoption similar to the rapid take-up of the internet in the 1990s. That blockchain is useful for a wide range of business functions isn’t news – just google “blockchain...
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Topics:
Machine Learning,
Office of Finance,
finance transformation,
Robotic Process Automation,
Artificial intelligence,
blockchain,
AI,
bots,
robotic finance
Robots of the physical sort are not about to take over finance and accounting but we have arrived at the age of “Robotic Finance”. I coined this term to focus on four key technologies with transformative capabilities: artificial intelligence and machine learning, robotic process automation, bots and natural language processing and blockchain distributed ledger technology. Embracing these technologies will enable any department to redefine itself as a forward-looking strategic partner to the...
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Topics:
Machine Learning,
close,
closing,
Robotic Process Automation,
Artificial intelligence,
blockchain,
AI,
Accounting,
bots
We at Ventana Research recently published our research agendas for 2018. Analytics and business intelligence are evolving and so is our research on their use across practice areas. Earlier research has shown that analytics can deliver significant value to organizations; for example, our predictive analytics research shows that 57 percent of organizations reported achieving a competitive advantage and half created new revenue opportunities with predictive analytics. Waves of investment in...
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Topics:
Machine Learning,
Analytics,
Business Intelligence,
Collaboration,
Internet of Things,
IOT,
Artificial intelligence,
natural language processing,
Natural Language Generation
The Strata Data Conference is changing and it’s changing in a good way. At the recentStrata Data Conference in New York, Mike Olson, chief strategy officer atCloudera, which co-sponsored the event, commented that at prior events we used to talk about the “Hadoop zoo animals,” meaning the various components of the Hadoop ecosystem of which I havewritten previously. Following last fall’s Strata event,I observed that the conference was evolving to focus on the use of data. Advancing that...
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Topics:
Big Data,
Machine Learning,
Analytics,
Hadoop,
Artificial intelligence
Fra Luca Pacioli, a 15th-century Franciscan friar living in what’s now Italy, is credited with codifying double-entry bookkeeping, which is the foundation of accounting. Pacioli, a polymath, was well acquainted with his contemporary and fellow polymath Leonardo Da Vinci. So, given they were at times collaborators, it’s fitting that one of the most important applications of SAP’s Leonardo technology will be in helping to disrupt finance and accounting organizations in corporations.
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Topics:
ERP,
Machine Learning,
Office of Finance,
Internet of Things,
CFO,
Artificial intelligence,
AI,
Leonardo