Process-mining software isn’t exactly new, but it’s also not widely known in the software technology market. The discipline has been around for at least a decade, but is generating more interest these days with both specialist vendors and major enterprise software vendors offering process-mining products and services. We assert that through 2022, 1 in 4 organizations will look to streamline their operations by exploring process mining.
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Topics:
business intelligence,
Analytics,
Digital Technology,
AI and Machine Learning
Organizations are accelerating their digital transformation and looking for innovative ways to engage with customers in this new digital era of data management. The goal is to understand how to manage the growing volume of data in real time, across all sources and platforms, and use it to inform, streamline and transform internal operations. Over the years, the adoption of cloud computing has gained momentum with more and more organizations trying to make use of applications, data, analytics...
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Topics:
business intelligence,
embedded analytics,
Analytics,
Collaboration,
Data Governance,
Information Management,
Internet of Things,
Data,
natural language processing,
AI and Machine Learning
Data is becoming more valuable and more important to organizations. At the same time, organizations have become more disciplined about the data on which they rely to ensure it is robust, accurate and governed properly. Without data integrity, organizations cannot trust the information produced by their data processes, and will be discouraged from using that data, resulting in inefficiencies and reduced effectiveness.
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Topics:
business intelligence,
Analytics,
Data Governance,
Data Preparation,
Information Management,
Data,
data lakes
Organizations are always looking to improve their ability to use data and AI to gain meaningful and actionable insights into their operations, services and customer needs. But unlocking value from data requires multiple analytics workloads, data science tools and machine learning algorithms to run against the same diverse data sets. Organizations still struggle with limited data visibility and insufficient insights, which are often caused by a multitude of reasons such as analytic workloads...
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Topics:
business intelligence,
embedded analytics,
Analytics,
Collaboration,
Data Governance,
Data Preparation,
Data,
Information Management (IM),
data lakes,
AI and Machine Learning
Every organization performing analytics with multiple employees needs to collaborate. They should be collaborating in the analytics process and in communicating the results of those analyses. As I continue my evaluation of analytics and data vendors, I have to admit some disappointment at the level of collaborative capabilities some analytics vendors provide. To be fair, the level of capabilities vary widely, but I expected collaborative capabilities to be more uniformly available as a standard...
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Topics:
business intelligence,
Analytics,
Collaboration,
Data Governance,
Data Preparation,
Information Management,
Data,
Digital Technology,
collaborative computing
I’ve written before about blockchain’s significant potential. A lot of the current discussion on the topic centers on cryptocurrencies and financial trading platforms, both of which are already in operation. However, my focus is on its applicability to business generally, especially in B2B commerce, where I believe there is significant potential for it to serve as a universal data connector. There’s also a great deal of potential for blockchain to provide individuals with greater power in ...
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Topics:
Sales,
Human Capital Management,
business intelligence,
Collaboration,
Internet of Things,
Data,
Product Information Management,
Digital Commerce,
Enterprise Resource Planning,
blockchain,
candidate engagement,
collaborative computing,
continuous supply chain
Sage Intacct recently hosted its annual user group meeting, Advantage, and earlier this year met with industry analysts. Both meetings shed light on how the company is addressing two key opportunities. One is building a robust offering to address rapidly evolving technology requirements for the Office of Finance. The other is broadening the scope of its offering to address the financial management and administration needs of its customers.
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Topics:
Office of Finance,
business intelligence,
Financial Performance Management,
ERP and Continuous Accounting,
robotic finance,
Predictive Planning,
revenue and lease accounting,
AI and Machine Learning
For interactions with customers to go well, organizations must manage an ever-increasing array of engagement channels. Our research finds that organizations expect to see interaction volumes increase on all channels, especially digital ones such as text-based messaging, chat, mobile and social apps. Unfortunately, the systems that manage these channels are typically disparate and uncoordinated and may not use the same underlying technology. This makes it difficult for organizations to...
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Topics:
Customer Experience,
Voice of the Customer,
business intelligence,
embedded analytics,
Analytics,
Collaboration,
Data Governance,
Data Preparation,
Information Management,
Internet of Things,
Contact Center,
Data,
Digital Technology,
Digital Commerce,
blockchain,
natural language processing,
data lakes,
Intelligent CX,
Subscription Management,
agent management,
extended reality,
AI and Machine Learning
Today’s intense competition requires that companies know as much as they can about their customers in order to anticipate their needs and deliver a superior customer experience. However, many organizations struggle to do this well. Implementing initiatives to improve customer value across any department or process involving customers requires both in-depth visibility into current operations and excellent metrics.
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Topics:
Customer Experience,
Voice of the Customer,
business intelligence,
embedded analytics,
Analytics,
Collaboration,
Data Governance,
Data Preparation,
Internet of Things,
Contact Center,
Data,
Digital Commerce,
blockchain,
natural language processing,
data lakes,
Intelligent CX,
Conversational Computing,
collaborative computing,
mobile computing,
Subscription Management,
agent management,
extended reality,
AI and Machine Learning
Organizations’ use of data and information is evolving as the amount of data and the frequency with which that data is collected increase. Data now streams into organizations from myriad sources, among them social media feeds and internet-of-things devices. These seemingly ever-increasing volumes of devices and data streams offer both challenges and opportunities to capture information about a business and improve its operations.
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Topics:
business intelligence,
embedded analytics,
Analytics,
Collaboration,
Data Lake,
Information Management,
Internet of Things,
Data,
Digital Technology,
AI and Machine Learning