The study, The State of Enterprise Wearable Adoption, focused on the IT or business decision makers in 201 companies with 500 to more than 5,000 employees, and from a range of industries. The industrial enterprise sector was the focus of the study, with government, non-profit, education, professional services, media, hospitality, health care and financial services industries excluded since those areas do not have a direct use for wearables relevant to the study. The 93% of companies interested in wearables are split across almost every industry included, with manufacturing and life sciences "very big" and transportation and retail smaller than anticipated, Ballard said.
Leveraging Big Data insights is well known for its ability to provide quality prospects for businesses, but another lesser known feature is its ability to shed light on low quality prospects or frustrated clients. Advanced analytics tools allow insurers to target individuals who are apt to be a long term loyal customer, and also to weed out individuals who are a high risk of canceling coverage. Predictive analytics is used to track and reveal signal behaviors that indicate an impending cancellation. This allows insurance agents to reach out to unhappy consumers before their final decision has been made, and tailor opportunities to encourage them to stay with the company.
Although the new SDK does not introduce as many new or enhanced features as iOS 8, which included more than 4,000 new APIs, it does still provide a wealth of new functionality and enhancements. Along with the new SDK, iOS 9 is also marked by new developer tools to support some of its features, and new releases of Apple’s major programming languages, Swift and Objective-C. This series aims at introducing all that is essential for developers to know about building apps for the latest release of Apple’s mobile OS. It comprises five articles that will cover what’s new in iOS 9 SDK, new features in Swift, Objective-C, and developer tools, and Apple’s new bitcode.
The latest findings suggest that investing time and effort up front to design a transformation’s initiatives also matters. According to the new results, the most effective initiatives involve four key actions: role modeling, fostering understanding and conviction, reinforcing changes through formal mechanisms, and developing talent and skills. These actions are critical to shifting mind-sets and behaviors. But it’s not enough to design a portfolio of initiatives based on one, or even two, of these actions. When executives report that their companies used all four, the odds of a successful transformation are much higher than if just one were used. The process of howinitiatives are designed is critical too.
CEB data show that HIPOs produce 91% more valuable work for the company and exert 21% more effort than non-HIPOs. Managers are right to worry about identifying them (only 1-in-7 high performing employees classify as HIPOs) and to worry twice as much about keeping hold of them, and developing them so that all that glittering potential is realized. And it’s not only their managers. A full 50% of HR professionals worry about their company’s HIPO program (the initiatives in place to identify, retain, and develop HIPOs). HR teams ask questions like, “My high-potential program is expensive – am I investing in the right people?”, “How should we prepare our HIPOs to take on more challenging senior roles in the future?” and, “Why is my high-potential program not working? People we thought of as high-potential are failing when placed into more senior roles.”
Routers are attractive to hackers because they operate outside the perimeter of firewalls, anti-virus, behavioral detection software and other security tools that organizations use to safeguard data traffic. Until now, they were considered vulnerable to sustained denial-of-service attacks using barrages of millions of packets of data, but not outright takeover. "If you own (seize control of) the router, you own the data of all the companies and government organizations that sit behind that router," FireEye Chief Executive Dave DeWalt told Reuters of his company's discovery. "This is the ultimate spying tool, the ultimate corporate espionage tool, the ultimate cybercrime tool," DeWalt said.
"You could do things like emulate an Apache server and make it look like Apache is running somewhere when it isn't," Pingree said. "Or you could run a real copy of Apache that's monitored." As soon as an attacker sends data to the honeypot, it issues an alert. The attacker will most likely start rummaging around, performing passive scans of hosts on the network. The beauty of a honeypot is, legitimate users know it is fake. So the only people accessing it are cybercriminals and hackers, meaning there are no false positives, there is no need to filter out the noise that occurs in most fraud-detection systems. "The biggest problem with security-transaction monitoring is you have to filter out what's good and what's bad," Pingree said. "But if it's a decoy, everyone that's hitting it is bad."
Despite its technical and economic superiority to distributed platforms, a surprising number of industry voices still contextualize the mainframe as a “legacy” platform from which enterprises need to migrate their core applications if they are to succeed in the digital economy. This makes no sense. First of all, why would any organization migrate its most critical applications from a supremely reliable, secure, scalable and secure platform to a relatively risky and expensive one? And why would any CIO allocate limited resources to a low- or negative-ROI migration project when so many other urgent imperatives clamor for his or her limited IT resources? The answer is that there is no reason. That’s why analysts like Gartner are reporting minimal migration activity—and why 88% of CIOs assert that their mainframes will run existing and even net new workloads for at least another decade.
For many of us, the concepts of customer engagement and customer resource management (CRM) are murky at best. We understand the general idea, and we appreciate the results when customers are happy and buying, but the mechanics of how those sales are accomplished are lost to us. And, for the most part, that is okay, because we don't really need to know how it all comes together. However, if you're a salesperson, the tools provided by applications like Microsoft Dynamics CRM are vital to your success. Without those tools, sales are not made, revenues are not realized, commissions are not calculated, and people don't earn a living. With that being said, for an enterprise of any size operating in today's highly competitive environment, a well-designed CRM solution is required for any sort of success.
All data monetization efforts require that data is ultimately used to drive actions or decisions that solve a problem for an end consumer. This fundamental requirement is where most businesses fail when attempting to monetize data because the typical approach is “How can we sell data to increase our revenues?” which assumes that the value is the sale of the data itself. In order to successfully monetize data, organizations must flip this approach and start with the end in mind. The questions should be “What problem can our data solve?” and “How valuable would it be to the end consumer if these problems were solved?” It is important to note that “end consumer” does not always mean customer either. Monetized data solutions can be for internal end consumers as well.
Quote for the day: "Cream always rises to the top...so do good leaders" -- John Paul Warren