Love You... Where's My Ham?


When my son was in his early teens, he started ending every phone call he made by saying "love you." He said it to me, his dad, his sisters, his friends of both genders. It was his signature signoff -- and it left anyone on the other end of the receiver with a smile. Until he tried to order pizza.

One day, I asked him to phone a local pizza place that defies New York City area tradition because it refuses to sell slices -- only pies, like most of the rest of the country. The place is run by first-generation Italians, with little use for social niceties -- or the prospect of someone placing an order he had no intention of picking up.

The woman who answered the call was clearly skeptical when my son ordered three specialty pies. They weren't cheap, and I can understand why she would have doubts. But, hey, I was feeding a family of seven.

My son reassured her, repeatedly. Then he screwed up. He said "love you" out of habit as he ended the call.

We never got our pies. In fact, she tossed the order -- and didn't even apologize when we stopped in to get it. Clearly, randomly saying "love you" is the mark of a prankster.

Now, we have apps to order pizza that reduce the odds that a restaurant is being punked by a kid who says "love you" with abandon. By entering a phone number, credit card, and other identification, the restaurant has greater assurance about the sources of orders.

In 2008, for example, Pizza Hut hired Baron Concors, who formerly worked as vice president of global retail technology for FedEx Corp., and as a management consultant for Deloitte & Touche and Ernst & Young, to focus on analytics and the use of big-data. "The main focus is improving speed and ease of ordering. We want to provide an experience that is easier and faster than a phone call. We have made the apps faster, easier to use and smaller in size," he said in a post on Nation's Restaurant News.

And what makes him most excited? Big-data. "We have so much data available -- from customers, suppliers, operations, sales, social media, etc. -- and there are more innovative tools coming out that allow you to better analyze and make smart decisions," he stated.

Yes, but, how can we make the most of state-of-the-art analytics, the most innovative tools, and a myriad of key performance indicators and metrics, unless we also invest in the people who use them -- on the front line?

Should we intrinsically trust the source of an online pizza order, or do we still question orders that seem large or unusual, even with a credit card on file?

How do we teach the most entry-level members of an organization to trust (or question) the data?

Consider this: For grocery stores, one of the top self-service applications to boost return on investment is deli ordering. As far back as 2010, Zebra Technologies, a provider of barcode and RFID technology, was describing self-service kiosks for deli ordering as a great way to improve both incremental sales and employee efficiencies:

Research showed that incremental sales increase 6 percent to 8 percent when a customer orders through a kiosk, and in turn, clerks can process 11 percent to 16 percent more orders during peak shopping hours with the same staff. That's because they can spend less time taking orders, and more time fulfilling them.

Don't Blame Analytics
Blame lack of common sense for this
2007 mistake at an NYC grocery store.
Blame lack of common sense for this
2007 mistake at an NYC grocery store.

But let's fast forward to real life.

Two weeks ago, a friend placed an order at a self-serve deli kiosk at a New York City-area grocery store. He waited patiently. But his number was never called. Eventually, he just shrugged it off, went to the counter and ordered in person.

The next week, the same thing happened again. This time, he was annoyed. "So I asked what happened to my order. And do you know what they deli guy said? He said he thought it was a joke," my friend explained.

What weird thing had he ordered? Two pounds of baked ham.

Doesn't sound that odd to me. So, what's the solution? How can businesses invest in technologies that are convenient, efficient, and likely to boost the bottom line if employees who deal with those solutions at the most basic level don't understand them? How far down in the human capital chain does an organization have to train to get the most out of its analytical solutions?

Noreen Seebacher,

Noreen Seebacher, the Community Editor of Investor Uprising, has been a business journalist for more than 20 years. A New York City based writer and editor, she has worked for numerous print and online publications. Her work has appeared in The New York Times, the New York Post, New York’s Daily News, The Detroit News, and the Pittsburgh Press. She co-edited five newsletters for Real Estate Media’s GlobeSt.com and served as the site's technology editor.

She also championed the commercial real estate beat at The Journal News, a Gannett publication in suburban New York City, and co-founded a Website focused on personal finance. Through her own company, Stasa Media, Noreen has produced reports, whitepapers, and internal publications for a number of Fortune 500 clients. When she's not writing, editing, or Web surfing, she relaxes in an 1875 Victorian with her husband and their five kids, four formerly homeless cats, and a dog.

Big-Data Draws Attention at Interop New York

Even at a trade fair better known for seminars on information technology, big-data was too significant to ignore.

Time to Tame the Meta-Monster

All Analytics readers have serious issues with the data hidden in digital photos.


Re: False positives...
  • 12/28/2012 12:00:52 PM
NO RATINGS

..

MNorth writes


 Every business must deal to some extent with the frustrating balancing act of filling orders that aren't real vs. orders that don't look real but are and need to be filled.


 

When I was a kid, it was in vogue to order pizza over the phone to be delivered to some unsuspecting grumpy neighbor, then peek out the window and do the equivalent of ROFL over the confusion when the delivery boy arrived with the undesired pizza.

These days, I would want to perform "enhanced interrogation techniques" upon the perpetrators (whether I were the delivery guy or the recipient) ... but anyway, I would think that the amazing benefits of today's Big-Data/Analytics world, where they can trace you from your phone number (and who knows what else?), and then the increasing practice of requiring a credit card confirmation, are all conspiring to increasingly squelch opportunities for pranksterism.

With the undelivered orders of ham, I suspect something else may be in play...

Re: False positives...
  • 12/28/2012 6:56:14 AM
NO RATINGS

Yep, employee training is a must. How many times do you see an ad for a store special and questions an employee about it and come up with a blank stare.

Data is great and using it can improve the bottom line, but management must increase employee training to make it work successfully without making bad impressions on customers.

ham for the holidays
  • 12/11/2012 9:05:44 AM
NO RATINGS

I've seen the picture of ham offered for Hanukah. While it strikes many as strange, the fact is that many celebrate the holiday who do not keep kosher. So there really is a possible market. Perhaps someone thought it would go well with latkes. 

Re: False positives...
  • 12/11/2012 9:01:58 AM
NO RATINGS

@Noreen from the perspective of the woman who took the order, it sounded suspect. Perhaps she got in trouble in the past for putting through orders that no one ever picked up. So she was being circumspect. In contrast, I recently tried to order pizza from a new place that opened in my neighborhood and now expect that they won't stick around very long.

The phone was busy, busy, busy. Finally, a woman picked up the phone but refused to take the order, telling me to call back in 10 minutes. I tried. It was busy, busy, busy, busy, then ringing with no one to pick up, then busy, busy. Finally, after I don't know how many tries, a woman picked up the phone, and I finally gave in my order to be ready with more than 45 minutes to spare. She took down my name and phone number. But when my husband went to pick it up at the time, they had nothing ready and no record of the order. They said it would be another 20 minutes until pizza would be ready. When my husband called to ask if he should wait, I told him not to. We ended up picking up pizza at a shop that's been here for over a decade and knows to have pies ready at meal times -- even without orders. 

 

Re: False positives...
  • 12/11/2012 8:04:29 AM
NO RATINGS

I think I've heard this one before http://www.inquisitr.com/29647/million-dollar-ham/

There are inside jokes and other external factors that can lead to people doing odd things.  I've been in situations where I had to question if a person really wanted what they were asking for and if they understood what they were asking for.  In the two pounds of ham example I wouldn't be surprised if a local TV channel mentioned something outrageous like what the government spent for two pounds of ham and it resulted in deli's getting calls checking on the price of sliced meats.  These kinds of things are hard to catch from a data standpoint so while they look like outliers it's possible that they have a common thread.

Re: False positives...
  • 12/10/2012 2:28:45 PM
NO RATINGS

Wanna hear a joke, SaneIT? "Two pounds of ham!"

Re: False positives...
  • 12/10/2012 8:53:56 AM
NO RATINGS

I think the examples here are more issues of perception not data indicating that the orders were suspect.  Now if that deli had been experiencing a high number of people ordering 2lbs of ham and then not picking it up I could see where their excuse would be valid but I suspect that it was probably more of a catch all.  Rather than saying, "we're really busy and I lost your order"  they just said "oh I thought it was a joke".   As for the big data side of ordering food goes I can see it's usefulness if you've got demographics and you have some insight into orders that tend not to be picked up or the delivery driver ends up being pranked or stiffed on payment I could see having a talk with the person placing the order before actually filling it or sending a driver out.

Re: False positives...
  • 12/7/2012 12:50:48 PM
NO RATINGS

@Matt, John Barnes warns us about those dang outliers in his blog from earlier this week! Don't You Regress With Your Regressions  

Caio! Seebachers
  • 12/7/2012 12:44:45 PM
NO RATINGS

@Noreen, my question is, had you ever ordered from the "love you not" pizzeria? Seems to me if three speciality pies were an unusual order that would have stuck in her mind -- like, "Oh, it's them again." What poor customer service. I know our local favorite wouldn't flinch if we called and ordered three times as many pies as that (not only do I have a large family but I come from a large family so entertaining requires big orders).

False positives...
  • 12/7/2012 11:05:18 AM
NO RATINGS

It seems to me that in the examples of the pizzas and ham, it was people who decided to kick out an order because it looked bogus.  Analytics can do this too, because every model has false positives, and both analytics and people are sensitive to what appear to be outliers.

I live in an area where Sheetz and Wawa, two convenience store/gas station companies, have turned to kiosk-based food ordering systems to drive revenue.  So far as I have been able to tell (I'll admit I've never tested it too far), if an order is placed, it gets filled.  I can imagine some teenagers (or adults who behave as children), have thought it would be funny to go in, tap in a bunch of orders, then walk out of the store and abandon the food. Every business must deal to some extent with the frustrating balancing act of filling orders that aren't real vs. orders that don't look real but are and need to be filled.

INFORMATION RESOURCES
ANALYTICS IN ACTION
CARTERTOONS
VIEW ALL +
QUICK POLL
VIEW ALL +