Process mining is defined as the analysis of application telemetry including log files, transaction data and other instrumentation to understand and improve operational processes. Log data provides an abundance of information about what operations are occurring, the sequences involved in the processes, how long the processes are taking and whether or not the processes are completed successfully. As computing power has increased and storage costs have decreased, the economics of collecting and...
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Topics:
Analytics,
Business Intelligence,
Process Mining,
AI and Machine Learning
The learning management system technology market has evolved dramatically over the past two decades. Learning management systems, now commonly referred to as learning experience platforms, are an integral resource for any organization concerned about productivity, organizational agility and operational excellence. These technologies enable organizations to demonstrate an investment in people, as the LMS not only facilitates regulatory and legal compliance and other forms of cost and risk...
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Topics:
Human Capital Management,
Learning Management
I have recently written about the organizational and cultural aspects of being data-driven, and the potential advantages data-driven organizations stand to gain by responding faster to worker and customer demands for more innovative, data-rich applications and personalized experiences. I have also explained that data-driven processes require more agile, continuous data processing, with an increased focus on extract, load and transform processes — as well as change data capture and automation...
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Topics:
Cloud Computing,
Data Management,
Data,
data operations,
Analytics & Data
Workday held its first in-person Rising user group meeting since 2019 in Orlando. Three topics are worth commenting on: Workday’s Extend offering, its industry accelerators and its progress with the Workday Adaptive Planning offering.
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Topics:
Office of Finance,
Business Planning,
Financial Performance Management,
ERP and Continuous Accounting,
digital finance
In my first perspective on cloud computing realities, I covered some of the cost considerations associated with cloud computing and how the cloud costing model may be different enough from on-premises models that some organizations are taken by surprise. In this perspective. I’d like to focus on realities of hybrid and multi-cloud deployments.
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Topics:
Cloud Computing,
Digital Technology
Organizations are collecting data from multiple data sources and a variety of systems to enrich their analytics and business intelligence (BI). But collecting data is only half of the equation. As the data grows, it becomes challenging to find the right data at the right time. Many organizations can’t take full advantage of their data lakes because they don’t know what data actually exists. Also, there are more regulations and compliance requirements than ever before. It is critical for...
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Topics:
Business Intelligence,
Data Governance,
Data Management,
data operations,
AI and Machine Learning
Kinaxis recently announced it has acquired a Netherlands-based company, MPO, a cloud-based software offering that orchestrates multiparty supply chain execution. The combination is designed to enable Kinaxis to extend its concurrent planning platform to handle core elements of supply chain execution. Kinaxis acquired all the shares of MPO for approximately US$45 million, with some of the final consideration dependent on performance. MPO will continue to operate as a standalone business, but...
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Topics:
Business Intelligence,
Business Planning,
Operations & Supply Chain,
Enterprise Resource Planning,
continuous supply chain,
AI and Machine Learning
The data catalog has become an integral component of organizational data strategies over the past decade, serving as a conduit for good data governance and facilitating self-service analytics initiatives. The data catalog has become so important, in fact, that it is easy to forget that just 10 years ago it did not exist in terms of a standalone product category. Metadata-based data management functionality has had a role to play within products for data governance and business intelligence for...
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Topics:
business intelligence,
Data Governance,
Data Management,
Data,
data operations,
Analytics & Data
I have written about vendor efforts to use artificial intelligence (AI) and advanced analytics in their applications targeted at sales and revenue teams to improve focus and prioritize activities, both for pipeline management as well as individual opportunities. Since then, vendors have continued to innovate, and there have been more releases showcasing efforts to aid sales and revenue. And with this continuing innovation, we believe that by 2026, two-thirds of revenue leaders will begin...
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Topics:
Revenue Management,
Sales Engagement,
Office of Revenue,
AI and Machine Learning
Today’s contact centers need to revisit core assumptions around measuring agent performance. Changes in business conditions influencing agent engagement raise new questions about whether traditional performance models are sufficient to address the more complex customer needs that have taken center stage in recent years.
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Topics:
Customer Experience,
Voice of the Customer,
Contact Center,
agent management,
Customer Experience Management,
Field Service,
customer service and support