Attrition Expedition: Using AI to Chart a Course to Retain Call Center Employees


Call center turnover is high everywhere, and it was no different for us. However, that's not where our story ends, as we weren't willing to accept that as inevitable. As we reviewed several years of artifacts that had accumulated in our efforts to tackle the turnover problem, we realized our hypothesis had been the same each time: It was a talent acquisition problem. Each time, we'd set out to fix what we thought was wrong with recruiting. The familiar pattern repeated itself numerous times: When turnover spiked, we'd make a tweak somewhere in the recruiting process and then walk away.

Machine learning, Deutsche auction and repo haircuts - Risk.net


Watchdogs ask EC to delay repo haircut floors. It should come as no surprise that credit card companies supplement their revenues by selling real-time access to consumer transaction data – albeit aggregated and anonymised – and even less of a surprise that enterprising hedge funds have found a way to monetise it. This week, Risk.net reported how scrutinising data from millions of credit card transactions allowed a quant team to infer whether a company's sales are on the up or trending lower – without the need to wait for quarterly sales reports to be published. The analysis was delivered through a machine learning implementation of the random forest technique in which multitudes of decision trees combine to produce predictions. In this case, the algorithm enabled the quant shop to get an early warning on the health of companies whose options it held.

Is a robot tax, or even an AI tax, really a good idea?


Critics of such an idea have, in the past, argued that any tax on a machine, be it a robot, a car or an AI tax, would be anti-business -- but then it would be stretching credibility to suggest Bill Gates is anti-business. "You ought to be willing to raise the tax level and even slow down the speed of automation," said the co-founder of Microsoft. He warned: "You cross the threshold of job replacement of certain activities all sort of at once. If you want to do [something about] inequality… government's got a big role to play." There are multiple problems with the idea.

Honor CEO Seth Sternberg: 'We're Using the Past to Predict the Future' - Home Health Care News


Home care is often singled out for being slow to embrace and implement technology, but as the demand for care services grows, providers are forced to think outside of the box when it comes curbing caregiver turnover. San Francisco-based home care startup Honor understands this all too well, according to CEO Seth Sternberg. The company is using insights gleaned from machine learning to examine and address turnover internally and with its network of home care partners. Honor, which has raised $115 million since launching in 2014, teams up with independently owned and operated agencies by taking over caregiver recruiting, onboarding and training, in addition to day-to-day logistics. Currently, the company operates in Arizona, California, New Mexico and Texas.

The Case for AI and Machine Learning in Talent Management


A preview of just one of the topics to be covered in a live, virtual event on July 18: Deconstructing Talent Best Practices to Find What Really Works. Artificial Intelligence in the workplace is more than a catch phrase in organizations today. With the pace of technology advancements and usage rapidly accelerating, the acceptance and reliance on such tools is also growing. The first thing HR leaders need to understand is what artificial intelligence (AI) is and what it includes. According to Ben Eubanks, an industry expert from Lighthouse Research, "AI is a term that encompasses multiple types of computerized programs. In fact, someone talking about AI can be discussing anything from facial recognition tools powered by neural networks to machine learning that predicts the best word to use in a subject line to improve email open rates."

Walmart Announces A New Addition To Its Workforce: Thousands Of Robots


A new tech trend has emerged at the world's largest retailer, as Walmart brings on board thousands of robots in nearly 5,000 of its 11,348 stores. According to CNN Business, these robots will be scrubbing floors, scanning boxes, unloading trucks and tracking shelf inventory at mostly domestic U.S. locations. Robots will replace lower-level jobs--serving in janitorial functions as well as performing basic inventory work--in order to manage rising costs. A new robot unloader has already been used on the docks in hundreds of stores, pulling boxes from delivery trucks while automatically scanning and sorting merchandise. The unloader will be deployed at over 1,100 retail locations in the near future.

Why Walmart's robot army won't be a job killer


Since the dawn of the self-checkout, automation in retail has sparked anxiety and spread fear over an impending robotic takeover and the fate of human workers. Those fears were stoked again this week when retail giant Walmart announced that it was adding thousands of new robots to its stores nationwide. But a closer look at Walmart's announcement suggests that its robotics push is less of a job killer and more so a response to its own digital operations. As for Walmart's exact robotic plans, the retailer says it will add 1,500 new autonomous floor cleaners, 300 more shelf scanners, 1,200 additional FAST Unloaders, and 900 new Pickup Towers to its US stores. Many of these systems have been in testing throughout select Walmart stores since 2017, meaning that this isn't necessarily a new endeavor for Walmart as it is a broader deployment of an existing program.

How Humans and Robots Will Work Side-by-Side in the Supply Chain - Supply Chain 24/7


Merril Douglas paints a picture of a time in the near future when robots and humans will work side-by-side to help companies gain speed, increase accuracy, cut costs, and handle the grunt work. E-commerce sales continue to climb, forcing retailers to pick up the pace in their fulfillment and distribution centers," Douglas writes. "But these days, it's hard to find workers to keep product moving in any kind of warehouse e-commerce or otherwise." We're already seeing examples of robots being designed to take over the supply chain's least attractive tasks. "In some cases, robotic systems do this work entirely on their own, freeing humans for more complex functions," Douglas points out. "In other instances, bots collaborate with humans.

The Robot That Recruited Me


As a recruiter, you have almost certainly used software to organize CVs according to their relevance, saving you hours of troublesome screening. You simply define the profile with specific criteria--for example, a master's degree and fluency in English--and the software takes it from there. The algorithm selects CVs with complete objectivity, based on the rules you choose. Bear in mind that humans make the decisions using specific filter criteria, not the machine. When it comes to the preliminary sorting of CVs, the notion that a human does better than a machine is difficult to justify.

How AI can to help traders make better decisions?


Dark pools are electronic trading platforms that have emerged in the past decade in advanced markets. They allow traders to buy or sell large blocks of shares without having to disclose their identities, the volumes or prices, unlike traditional exchanges. They are popular with asset-management companies, pension funds and insurance firms which need to conduct a lot of large transactions, because they are cheaper and easier to carry out via electronic trading platforms. Merrin founded Liquidnet in 2001 in the US and later expanded into Europe and Asia-Pacific. The platform has seen trading volume in Asia-Pacific of US$42 billion so far this year, up 57 per cent from a year earlier.