Vibrant network ecosystems are turning supply chains into competitive weapons
The old paradigm for supply chain networks has run its course, and the future is in multi-enterprise, or multi-party business networks
The new world of knowledge management: Q&A with Sagi Eliyahu, CEO of KMS lighthouse
Being able to provide consistent information across an organization's various systems offers customers a more efficient experience and improves the customer journey
How e-discovery requirements are changing: 5 questions with Relativity CTO Keith Carlson
Keith Carlson, Relativity's new CTO, recently reflected on the role of unstructured data, changing views about data privacy, and how the e-discovery space is evolving
Building smarter robots: A new era combines content intelligence and RPA
For RPA to progress beyond automating simple repetitive tasks with fixed rules, enterprises will need to turn their RPA robots into "smarter" robots that can process a wide variety of unstructured content
3 Departments with Untapped Data Opportunities: CX, HR, and Sales
Three departments in particular—customer service, human resources, and sales—are sitting on a goldmine of data. Now, it's time to show those departments the potential they've yet to harness, and to do so, they need to ask some questions.
Digitally Transforming in a Regulated Industry: How You Can and Why You Should
No organization is exempt from the increasing pressure to innovate and digitally transform its processes. The taxi industry, for example, learned this the hard way.Ridesharing startup apps like Uber and Lyft rose up seemingly overnight, flouting any regulations while state and local governments rushed to create them. The regulations did eventually come for the apps, but it was too late for taxis - consumer behavior was the changed for good. Now, urban-dwellers want to order rides from their phones and skip the manual payment process altogether, something taxis never were and still aren't equipped to offer.
Three advances in AI and ML: From Awareness to Action and Decision
The possibilities of AI and ML are numerous—we are already witnessing some of its disruptive potential through personalized healthcare, weather predictions, inventory management, smart city design and more. There is one constant that will accelerate these advancements in AI further—the desire to create machines that are domain fungible with the ability to self-learn.
The End of Data Bulldozing: File Analysis
Migrating from one enterprise collaboration system to a new version or even new system can be overwhelming. Unfortunately due the immensity of this project type, organizations tend to take a bulldozer approach to moving their content.
Cognitive Computing and Knowledge Management: Sparking Innovation
Video and transcript from from the keynote at KMWorld 2015. Susan E. Feldman (CEO, Synthexis Cognitive Computing Consortium), a long-time technology analyst, discusses a new innovative approach to knowledge management that addresses the complex problems enterprises face today.
What is Cognitive Computing?
Video and transcript from a keynote speech by Susan Feldman on cognitive computing at KMWorld 2015. How cognitive computing can help spark innovation.
How Cognitive Computing Systems Differ from Traditional Information Systems
Video commentary from an interview with Sue Feldman, Founder & CEO, Synthexis, at the KMWorld 2015 conference on knowledge, content, and document management.
Retailers Harness Big Data and Big Content for Big Profits
Many savvy retailers have already implemented tools and strategies for turning their Big Data into more sales and more efficient operations, which in turn leads to more profit.
Why big volume is not the Big Data story
Organizations have witnessed an unprecedented surge in information generation in what has come to be seen as the era of Big Data—leaving many at a loss as to how all this information can be managed and used.
Big Data Delivering Big Knowledge
Is your organization limiting its knowledge? This question usually leads to discussions about an organization's view of big data. It's typically centered only on internal transaction data available in their customer relationship management (CRM), electronic resource planning (ERP) or other cloud-based enterprise applications. However, this contradicts what most IT business leaders want.