Big Data meets HR meets Call Center Management

We have already written in the past about the use of data analytics to best route customers to agents based on demographics and other characteristics.  The NY Times has an interesting article on the use of data analytics to improve retention and employee-employer relationships (“Big Data, Trying to Build Better Workers“)

The article discusses the broader appeal of these ideas, but focuses on applications to call centers. Why call centers? In contact centers, customer service agents, that are hourly workers handle a steady stream of calls under challenging conditions, yet their communication skills and learning capabilities play a crucial role in determining both the employee’s tenure and performance. The article discusses a new startup, Evolv, which helps firms find better-matched employees by using predictive analytics.

Transcom, a global operator of customer-service call centers, conducted a pilot project in the second half of 2012, using Evolv’s data analysis technology. To look for a trait like honesty, candidates might be asked how comfortable they are working on a personal computer and whether they know simple keyboard shortcuts for a cut-and-paste task. If they answer yes, the applicants will later be asked to perform that task.

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Education, Online Learning and MOOCs

There is so much talk and doom about the “ending” of traditional education by the disruptive innovation of online learning and massively open online courses.  I can’t help but to think back to the end of the 1990s and the first boom & bust in ecommerce, as illustrated by Webvan delivering a pack of gum from Oakland to San Jose for less than $1…

When it comes to education, though, we must distinguish between learning and signaling.  All debate and hype is about the learning but I have not heard anything about the latter, which I believe is at least as important (for better of worse).  Just ask any parent (whose kid now just heard about college acceptance) about the strength of their desire to be admitted to certain institutions.  We seldom hear the point that their kid will learn more at that desirable institution; so what is its attraction? Signaling (as Nobel laureate Spence wrote about quite a while ago).

Admittedly, this distinction pertains mostly to top or “brand” schools, whose value proposition of the degree is signaling selectivity—that will not change by MOOCs or any online learning.  The desire to signal uniqueness and distinction (and to self-classify as the BCC wrote about recently in their study and poll of “class” in the UK) is so human it is timeless.  Add to that the desire to be surrounded by similar people or those one looks up to, and the opportunity to build lifelong relationships and networks, and to belong (to the club). Traditional US higher-ed is the best in the world to respond to these desires.

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Supply Chain Coordination and Anti-Trust: The Japanese Car-Parts Keiretsu

One cannot discuss the Japanese automotive industry without mentioning the Car-Part Keiretsu.  The Wal Street Journal has an interesting article on the anti-trust investigations and lawsuits regarding these arrangements (“Japan Probe Pops Car-Part Keiretsu“)

 First: what’s a keiretsu? A keiretsu is a cluster of interlinked Japanese firms, usually centered on a large corporation that holds equity in the smaller firms.

Japanese auto makers have long seen keiretsu as a way to ensure quality over the long term by building trusted relationships with suppliers. The brand-name companies often own significant stakes in keiretsu parts makers and often enjoy the right of first refusal for newly developed technology. Typically, they work closely from the design stage onward, sharing proprietary technology.

By combining forces and coordinating their actions, these companies are able to reduce costs and risk, better facilitate communication, while building trust and reliability. The Toyota Group is considered to be the largest of the “vertically-integrated” keiretsu groups.  There were always discussions that the practice of such a scheme may lead to cartel-like behavior. Recently, due to changes in the Japanese automotive market, several investigations and law suits regarding illegal practices of these Keiretsus:

But there was a lot going on behind the scenes and some of it wasn’t legal. In fact, some areas of the Japanese auto-parts business were rife with bid rigging and collusion, according to confessions by companies and executives to antitrust officials around the globe that have produced multimillion-dollar fines and a dozen prison sentences.

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Outsourcing at Boeing (…Revisited)

While the initial reaction to Boeing’s 787 electrical problems was to blame outsourcing, there is more and more understanding that outsourcing itself is not the issue. Boeing has always outsourced the production of batteries. There are several explanation that emerged since.
(1) It’s not outsourcing. It is the trend of modularization: We know that more modular designs allow for lower cost, but come at the expense of quality and performance. One should say that this is a very valid argument, since modularization is clearly the enabler of the excessive outsourcing trend.

(2) An alternative explanation is that It’s not outsourcing itself, but rather the specific method of outsourcing where Boeing outsources the design and control over sub tiers.  This is the main focus of The Seattle Times’s article (“Boeing 787’s problems blamed on outsourcing, lack of oversight“).

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Disney Uses Technology to Build Lotaltly, Increase Sales and … Hopefully Improve the Experience

The NY Times has an interesting article on a new system Disney is implementing in Disney World (“At Disney Parks, a Bracelet Meant to Build Loyalty (and Sales)“).  As part of this system, visitors would wear rubber bracelets encoded with credit card information. The system will track every interaction in the park including every ride, every product purchased, and every picture you take with a mouse. The system will connect with your smartphone and would signal when it is time to use a specific ride without standing in line.

There are clearly privacy issues with the new system, and the marketing side this system deserves a discussion of its own. Yet, there are clear opportunities to improve both vistor’s experience and ability to plan from the operational point of view, which should improve the experience even further.

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Regulating Quality of Service by Law in Israel

Not many times the parliament of a country requires its government to enforce strict quality of service requirements on call centers of firms in the private sector.  But this is the case since December 12^th, 2012 in Israel (“Israel: New Law Demands Live Telephone Support” and in Hebrew).  I am not sure what I find more alarming and hilarious: the law (and its specificity) or the decision to begin the regulation on 12/12/12:

 A Knesset committee has taken a step forward towards protecting and assisting consumers, now setting into place a new regulation. When one calls a company for support, a live person must be on the line within three minutes. Alternatively, the company must offer a call back option during this same period, and the caller must received a call back within three hours of calling the company for assistance.

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Where are the Kiva Robots Amazon Bought?

Several months ago Amazon bought Kiva, a firm that develops robotic fulfillment systems.  Several photos and tours of Amazon’s newest warehouses were released this week, and people were shocked to see that the warehouses are still built for human pickers, with no robots in sights. Bloomberg’s BusinessWeek ran an article trying to explain this observation. (Amazon’s Robotic Future: A Work in Progress)

After all, aren’t robots supposed to be the future of such places as distribution centers and warehouses? Didn’t Amazon buy a robot manufacturer, Kiva, in March? The online retailer announced in October that it was taking on 50,000 additional part-time workers for the holiday season. Shouldn’t some of those spots be taken up by mechanical arms and wheels?

The article provides several explanations:

Bruce Welty is chief executive officer of Quiet Logistics, an order-fulfillment company that manages the online inventory and distribution for retailers like Gilt, Zara, and Bonobos. He uses robots made by Kiva, the company Amazon purchased, but his warehouse in Massachusetts is not bereft of humans. “Robots aren’t very good at picking up things,” he says. “They aren’t very good at looking at a bin of different things and distinguishing one item from another.

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Disruption Risk Management Before and After Sandy

We already wrote about Sandy and its impact on operations immediately after the storm here. Several stories began to emerge on how firms managed to handle the storm.  Recently, the NY Times had an article on how Eileen Fisher managed the pre-storm preparation and the recovery (“Retailer Shakes Off the Storm“).

Recovery was both an urgent and a daunting task. A broad insurance policy helped a lot. So did some planning and a good amount of luck. As did an almost out-of-body detachment on executives’ parts to see past the emotion of sewage-soaked shirts and stained rolls of fabric to the prize of reopening a ravaged business.

When we talk about Disruption Risk Management, we discuss the three levels that need to be managed well: strategic, tactical and execution. The strategic level requires creating a resilient operations network (internal and external) and instituting effective risk-management process. The tactical level requires identifying and mitigating vulnerabilities in the current operations network, including threat identification and outlining an action plans. The execution level includes monitoring evolving risks and activating pre-planned contingencies. The article provides an excellent example of the interplay between the tactical level and the execution one.

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Sandy and Holiday Shopping

Sandy is going to affect holiday shopping… I know, you probably say that with many people without houses this is a very minor issues, but not if you livelihood depends on sales you are making during the holidays season.

When a hurricane hits, of course, there is the usual shutting down of shipping terminal and submerged warehouses. Due to the extreme nature of the storm, we saw deliveries being disrupted due to downed power lines, closed roads and scarce gasoline. All of these cause delays that affect every business, but the NY Times article “A Storm-Battered Supply Chain Threatens Holiday Shopping“ brings an interesting angle on the effect of these disruptions on small business, and especially due to the proximity to the holiday season.  The article tells the story of Robert Van Sickle

His pet supply company, Polka Dog Bakery, was relying on a shipment of cardboard tubes from China with a merry design, intended to hold popular holiday dog treats. The products represent about 15 percent of sales at the company. But the New York Container Terminal in Staten Island, where the tubes arrived shortly before the storm, was devastated, and Mr. Van Sickle’s freight forwarder has been unable to track down the containers. It is too late to reorder the tubes from China in time for the holidays, and Mr. Van Sickle has tens of thousands of baked dog treats piled up at his Boston headquarters.

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The Complexity of Managing the Deceased-Donor Kidney Allocation System

The NY Times (“In Discarding of Kidneys, System Reveals Its Flaws“) had an interesting article on one of the main issues of Kidney allocation:

 Last year, 4,720 people died while waiting for kidney transplants in the United States. And yet, as in each of the last five years, more than 2,600 kidneys were recovered from deceased donors and then discarded without being transplanted, government data show.

The question is why. One may conclude that the system is just inefficient, yet a closer look reveals that this inefficiency is rooted in many important principles, regulations, and incentives, all while attempting to create a fair system.  In order to better understand the issues, we need to understand how kidneys are being allocated in the US: The country is divided into 58 districts. When a kidney of a deceased person becomes available, the system allocates it to the person with the highest priority within that region. This priority is a function of the waiting time, whether a recipient is a child or not, as well as other factors. The system does not consider the projected life expectancy of the recipient or the urgency of the transplant. The allocation is initially local, and only when there is no match, the search expands to other regions. All of that is done while competing against the clock: Kidneys start to degrade after 24-36 hours.  The system is allowed to make offers to only a limited set of hospitals at any point in time, and these, in turn, have an hour to respond.

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