Making a List and Checking It Twice: The Art of Choosing Colleges

As they round the corner of eleventh grade, juniors are firming up their list of colleges so they can figure out where to visit — and ultimately — where to apply.

It is not too early to create a college list.

In fact, I wouldn’t wait a minute longer.

To say that the college list is a crucial part of the application process would be an understatement. Like your American Express card, you can’t go anywhere without it!

But how do you make a college list?

The first thing you need to do is figure out what’s important to you.

There are 4,976 colleges in the United States. How do you know which ones are right for you?

You need to establish some criteria. And here is a list of questions that will help you do that:

  • Where do you want to be geographically? East Coast or West? Northern California?
  • How big a school are you looking for?
  • What are your areas of interest? What might you major in? You’ll want to find schools that are good in what you’re interested in.
  • Do you want to be in a school with sororities and fraternities or not?
  • What “feel” are you looking for — liberal, conservative, in-between?
  • Are you interested in Study Abroad programs?
  • Is diversity important to you?
  • Are you interested in internship opportunities?
  • Would you like to find schools that don’t focus on or even need to see SAT/ACT scores?
  • Public or Private?
  • Expensive or not?
  • How about how much help is available if you have a learning difference and run into trouble?

These are all essential questions to ask as you start making your list.

Used to be I carried a Fiske Guide around with me wherever I went. No more.

Now I just do what everyone else does: I Google it!

Recently, I had a student ask me about the schools that were particularly good in the middle of the country in nanotechnology. First I had to look up nanotechnology! I have a rough idea what this field entails, but I wanted to make sure my instincts were correct. Once I knew what I was looking for, I plugged the following into Google: Midwest Schools strong in nanotechnology. A whole list appeared before my eyes!

It’s not rocket science!

Once you’ve generated a list, you’ve got to do some footwork, some research, to see which schools really appeal to you. And once you’ve whittled that initial list down, it’s a good idea to visit, if you can.

These days I rely pretty heavily on CollegeBoard.Org. Click on Big Futures, then College Search and plug in the schools you are considering. This site lets you compare schools based on various criteria.

You can also look at the Colleges That Change Lives web site.

Or go to Unigo or College Prowler for student reviews and videos.

Or you can just Google: Online guides for choosing colleges!

Here’s a list of A+ schools for B students:

It’s never been easier to generate a college list, at least as a starting point from which to get advice or do more research. Once you’ve got that list, of course, the real work begins!

Feminism in Angela Manalang-Gloria’s “Querida”

The door is closed, the curtains drawn within
One room, a brilliant question mark of light…
Outside her gate an empty limousine
Waits in the brimming emptiness of night.

Angela Manalang-Gloria is a Filipina poet who wrote poems in English during the time before war. Her works were given less attention to during those times, which explains why her entry was ignored in the 1940 Commonwealth Literary Contests. Her collection of lyrical pieces exploring a woman’s private passions received less favor then, but has undergone revaluation in recent years.

The poem “Querida” consists of only four lines and was criticized before as “saying nothing but that inside there was a light; outside, there was a limousine. The poem describes a certain scenario. We could conclude that it is one of the nights when the mistress, or the “querida”, as what the title suggests, spends time with her lover, who is most probably a wealthy, married man. The theme of having an affair with a married man, or a married person for that matter, was a taboo topic before. As the years pass by, and the way people’s way of thinking change, this issue had been talked about with a more open and non-discriminating minds.

Querida, as mentioned, means “mistress” and a mistress is a woman who is having an affair with a married man. Of course, the term refers to the female gender. Some would even point out that if a woman has an affair, she is branded as a mistress, but when a man does the same sin, there is no known equivalent for the term.

This subject could raise interest to women, because it’s the branding of their gender that this poem talks about. I am also inclined to believe that when news of things such as having a relationship outside marriage surfaces, it will be talked about, regardless if the people talking are male or female. In the Philippine context, there is no denying that most of these people who would be talking about this issue would be mostly women.

There is no definite labeling for the voice of the persona describing the scene. It merely describes, but somehow we could say that the voice is suggesting what the title says – it suggests that this is one of the nights in a querida’s life. We cannot definitely say that the work is sympathetic to the female gender, because as stated, the voice of the persona describing the scene is merely describing and giving hints. The work could be sympathetic, but at the same time, some may say it’s even sarcastic. The clues and hints given could have a sympathetic feel, thinking that the persona’s purpose in telling this scene is for the readers to know what a querida goes through during these nights. On the other hand, it could also have this sarcasm, mocking the mistress in her deeds with a married man.

Although the poem is consisted of only four lines, the situation is pretty clear. It doesn’t sound like the persona wants to influence the way the readers think about mistresses, because again the persona is merely telling this certain scene.

The poem is full of images, one of them being the first line. A closed door and drawn curtains suggests secrecy. An affair is not openly announced to everyone anyway. Affairs are secretive, and the first line suggests the secrecy. The second line says that there is a questionable light in one of the rooms. Light is perceived as hope, but the persona deems it as a brilliant question mark. The hope being questionable is indeed doubtful. This could refer to the querida’s purpose or feelings about her being a mistress. Maybe she loves the man but the man is already married. Or maybe she benefits from the arrangement but despises it at the same time because she had no choice but to do it.

This poem is about a branded woman. A kind of discrimination which is predominant at the time this very poem was written. The poet was sort of like discriminated as well during her time, having her works ignored and all. But as they say, it takes a strong woman to speak her mind. Writing about “immoral” topics during those times opened an avenue to a broader perspective. Having this poem written by a female herself is indeed just because more than anyone else, a woman would understand another.

Who Was Eadric Streona?

In the days of Edmund Ironside, the name Eadric Streona keeps popping up at the most critical moments… and not in a happy way. It seems that this slippery Mercian Earl must have had incredible powers of persuasion, because he kept turning up no matter how often he changed sides. No one seemed to know whether he was working as a spy for Canute or as an advisor to Edmund, and no one seemed to understand why the Saxon King could trust him. Where did this man come from?

Streona was not the last name of Eadric of Mercia; rather, it was a nickname which roughly translates to “the Acquisitor”. He became Earl of Mercia in 1007, apparently as a result of murder, or rather, doing King Aethelred’s dirty work while acquiring the lands of tax defaulters. He married the king’s daughter Eadgyth in 1009, which made him brother-in-law to Edmund Ironside.

In 1015, Eadric procured the murder of Siferth and Morcar, two leading thegns in the Danelaw. We can assume that he did this for Aethelred, since the King confiscated their estates and ordered the arrest of Siferth’s widow. Following this episode, Edmund (not yet Ironside), in defiance of his father, carried off the widow and made her his wife. So Edmund became lord of the so-called Five Boroughs in the East Midlands, while Canute was hostile to the Danelaw at the time. Edmund and Eadric began raising troops to fight Canute, but since Edmund had just married the widow of the thegn Eadric had murdered, Streona was soon plotting to betray him. Within four months after Canute’s arrival in England, Eadric had sworn homage to the Danish chief along with forty Mercian ships.

In 1016, Aethelred the Unready died and Edmund the Aetheling was immediately elected King by the citizens of London. Unfortunately for him, Canute was elected King by the Witan in Southampton, thus causing a dilemma that wreaked havoc for the next seven months. London bravely withstood three sieges by Canute, and King Edmund did his best to draw the Danes away from the city. Eadric was present at every major battle, first on one side then the other.

His first infamy was at the Battle of Sherstone, fought on the border of Wessex and Mercia. Eadric sided with Canute, and on the second day he smote off the head of a warrior who looked like Edmund Ironside and held it up to the King’s army, shouting that the King was slain. The English wavered, about to take flight when Edmund tore off his own helmet, exclaimed that he lived and threw a spear at the traitor. Unfortunately, the spear missed Eadric and skewered someone next to him. The King’s army rallied but the day ended in a draw.

The Danes went back to their ships, but Eadric returned to his brother-in-law and swore fealty to him. No one knows why, but Edmund took the Mercian Earl back into his favor. The King levied a new army and closely pressed the Danes who were on the run, but Eadric was said to have contrived to detain Edmund long enough for the Danes to recover. Then, at the battle of Assandun, in charge of his own troops, Eadric suddenly turned tail and fled from the field, causing great slaughter.

For some reason, Eadric was still in King Edmund’s confidence, and after the defeat of Assandun managed to persuade the King to meet Canute in person. The two kings met on an island in the Severn and ultimately agreed to divide England between them, with the understanding that each King was the other’s heir. Poor Edmund did not survive the year; although no accusation of foul play was agreed upon by chroniclers, it was thought by many that Eadric quietly did away with Edmund Ironside.

As for Eadric Streona, Canute’s henchman had outlived his usefulness. Although he had retained his Earldom of Mercia, Eadric is said to have expected more rewards and upbraided Canute for his lack of appreciation. Some went so far as to state that Eadric claimed he killed Edmund for Canute, but I suspect this is poetic license. Regardless, it is certain that Canute had him killed at the Christmas Gemot. My favorite story is that he had Earl Eric cut off his head and throw it out the window into the Thames. How very appropriate!

Return of Earl Godwine, 1052

Earl Godwine may have had a humiliating experience finding himself exiled in the fall of 1051, but by many accounts his absence made the Saxons appreciate him like never before. King Edward the Confessor, ever more at home in Normandy than England, surrounded himself with Thegns and Prelates from his adopted land who proceeded to lord it over the Saxons as though they were a conquered people. Before the following winter was over, Godwine was encouraged by many requests for his return, and by summer he concluded that the time was right to reclaim his earldom.

Most likely he sent messages to Harold and Leofwine in Ireland, who finally set sail in nine borrowed ships loaded with mercenaries. Landing at Porlock in the Bristol channel for supplies, Harold met with fierce local resistance and a battle ensued that killed 30 Saxon Thegns and their troops. Harold plundered the immediate area then boarded again, rounding Land’s end and heading for Sandwich to meet up with his father.

Meanwhile, Godwine was headed toward Sandwich and was warned that the King had ordered a small fleet to be gathered against him. At the same time, one of those wicked Channel storms blew up, dispersed the Royal fleet and pushed Godwine back to Flanders. As it turned out, this was a lucky break for Godwine because the King was unable to reassemble his ships and crews, so the King’s undermanned fleet stayed in London while Godwine reunited with Harold and made his triumphant way up the Thames. Since Wessex was his own earldom, men flocked to his standard, and by the time he reached London at low tide and dropped anchor on the Southwark side, Godwine’s enthusiastic following had taken the spirit out of the King’s defenders. No one wanted a civil war just to support the overbearing Normans surrounding the King.

When the tide came in, Godwine’s party weighed anchor and traveled under London Bridge unopposed, making their way to where the King was waiting. Godwine sent messengers to Edward, asking him to return everything that had taken from him and restore his rights legally. Hoping to find a way out of this mess, Edward prevaricated, until Godwine’s followers became restive and the Earl had great difficulty keeping them under control.

Bishop Stigand and other negotiators decided that an exchange of hostages would help the situation, and this is probably when Godwine released his son Wulfnoth and grandson Hakon to Edward. It was agreed that the King and the Earl of Wessex would meet at a great Witan Gemot the following day and restore peace.

As soon as the Normans saw which way the wind was blowing, they decided to make a run for it. I have this vision of Norman soldiers bursting out of the city in every direction, among them Archbishop Robert, Godwine’s bitter enemy. He and his followers were said to have cut their way through the crowd and out by the east gate of London, leaving a trail of dead and wounded victims. Worst of all, it appears that they abducted Godwine’s son and grandson, which might be the explanation why their departure was so violent; perhaps the Earl’s men were trying to stop the kidnapping. Alas for poor Godwine, the hostages given in good faith ended up as pawns in Duke William’s hands, and Godwine would never see his youngest son again.

Regardless, the great gathering was held the following day outside the walls of London, where the people and the other Earls gathered to welcome the return of their hero. Godwine laid his axe at the King’s feet and declared his homage, and while the crowd cheered their acclaim he and Edward exchanged the kiss of peace. Godwine was restored all that had been taken from him, the charges were put aside, and amnesty was declared for any ills that had taken place the last three months. Archbishop Robert was deprived of his post and declared outlaw. And lastly, “Good law was decreed for all folk” (Anglo-Saxon Chronicle).

Alas, Godwine was not destined to enjoy his triumph for long. The events had taken their toll on his health and he soon fell seriously ill. Within the year he was dead; while feasting at the King’s table he was seized by a powerful convulsion and fell insensible, never to waken again.

Exile of Earl Godwine, 1051

By the middle of the eleventh century, Earl Godwine might have seemed pretty much at the height of his power. His daughter was married to King Edward, Godwine himself held the most important Earldom in England and his second son Harold was Earl of East Anglia. He had more strapping sons awaiting their turn for the next vacant earldoms.

But on closer inspection, things were not quite right. By 1051, it was apparent that Queen Edith was not likely to give birth to an heir, thus reducing her own and Godwine’s influence. Swegn, Godwine’s eldest son, had shamed the family by his outrageous behavior, then committed the heinous crime of murdering his own cousin. And to make matters worse, King Edward was surrounding himself with powerful Norman allies and churchmen, culminating in appointing Robert of Jumieges as Archbishop of Canterbury against Godwine’s and the local monks’ approved choice. Archbishop Robert immediately began poisoning Edward’s mind against Godwine, especially bringing up the old question about Alfred’s fate and Godwine’s alleged role in the tragedy concerning the King’s brother.

Things came to a head when Eustace, Count of Boulogne, visited King Edward in September, 1051. On his return trip, he and his men attempted to force the residents of Dover to give them lodging in their homes, just as they were used to in their native country. The stout Dover townsmen resisted, one was killed in his home, a Frenchman was killed in return, and the intruders mounted their steeds and plunged through the town, slashing and maiming whoever got in their way. The townspeople resisted, turning the incident into a full-fledged skirmish, and when all was done twenty English and nineteen Frenchmen lay dead on the streets.

Eustace turned around at full gallop and took his remaining men back to King Edward at Gloucester, demanding justice. Enraged, the King summoned Earl Godwine and insisted that he immediately chastise the offending town with fire and sword. This was putting the king above the law, and Godwine refused, insisting on a full trial. Then, having had his say, he retreated to his estate, leaving the King securely in the hands of the Normans. It didn’t take long before Godwine’s refusal to obey the King was construed as traitorous.

One thing led to another, and by the end of the month the tide was turning against Godwine. Edward summoned the other great earls of the land to support him against Godwine’s family; ultimately the King commanded Godwine and Harold to appear and answer charges. Godwine only agreed to do so if the King issued a safe-conduct. Edward refused.

Godwine knew there was no hope for his cause, at least for the moment. He had apparently been preparing for such an eventuality, because much of his treasure had already been loaded on a ship, and he quickly left the country along with most of his family. Their destination was Flanders, a common refuge for English exiles and home Count Baldwin, brother of Tostig’s new bride. On a different ship, Harold and his younger brother Leofwine took sail for Ireland, where they were well-received by Dermot, King of Dublin and Leinster.

Poor Queen Edith, caught between father and husband, was quickly trundled off to a convent and deprived of all her goods, real and personal. Did Edward think this was going to be permanent? Elated at his successful coup, apparently he wanted to make the most of it. But his freedom from Godwine was destined not to last.

Free Ways to Undelete iPhone Photos Easily

The iPhone has been a coveted gadget for several years. From stylish finesse to faster processing abilities and a great camera, the iPhone has it all. Losing photos on an iPhone accidentally or during an upgrade can be an extremely painful experience. After all, they are your favorite pictures and now this precious data is all gone. One of the most common reasons of such data loss is system updates. But don’t get disheartened by the grim situation because there are easy ways to retrieve this lost data. Yes! There are several options in the current breed of software programs that allow you to recover the lost photos on your iPhone. In fact, you can find paid as well as free software programs in this category.

Whilst we would never want any one of you to undergo the trauma of losing precious data like photos, videos, etc., it is always good to keep yourself updated with the latest options that can help you salvage such situations.

Here is a brief overview of these options:

EaseUS MobiSaver

This is one of the world’s first recovery software programs that came to the rescue of people looking for free ways to retrieve the photos deleted or lost on the iPhone. Simply plug-in the iPhone to the computer, run the software and you can recover lost data like pictures, songs, videos, etc.

Use the itunes back up files

If you have consistently built a back-up for your iPhone through itunes, data recovery becomes easy especially if you have lost it to the process of updating the system. Usually, the itune back-up recovery is the most preferred option by iPhone users.

iSkysoft iPhone data recovery

Another software program in the category of unpaid options that can be used to recover lost pictures on the iPhone, this is an excellent choice for people who don’t believe in taking itunes back-up. The free download version of this software is available on leading websites and so looking for one should not be much of an issue.

The free iPhone recovery software programs are extremely easy to use and implement thereby helping customers avoid the tension of losing pictures and similar important data to unexpected situations. In fact, using these software programs saves time when it comes to retrieving crucial data.

So, the next time you encounter a situation where you have lost the photo and related data on your iPhone, don’t get hassled. All you need to remember is to invest a little effort and choose the right recovery program to retrieve the data.

Aggravation in the Grocery Store: Modeling the Checkout Line

Almost everyone has waited – likely impatiently – in a grocery store checkout line. The aggravation rivals another modern irritation – being stuck in traffic. And just like understanding traffic might ease the annoyance (see the reference box for two prior articles on traffic congestion), understanding the dynamics of cashier lines at grocery store might also give some mental relief.

So let’s explore.

The Need for More Cashiers

As we wait in line, we often wonder why the store doesn’t add more cashiers. The store must be trying to save money, at our expense and on our time.

However, our reaction doesn’t quite hit the mark. More cashiers will not fundamentally solve the waiting problem, nor does having less cashiers fundamentally save the store money. Why might the apparently obvious approach of adding cashiers not work? It might not work because the fundamental problem stems from the TIMING of the cashiers.

Let’s do some simple modeling to understand this. After that, we will add sophistication, and model more complex situations.

Simple Modeling: An Early Morning Scenario

Imagine a grocery store early on a Saturday. As the store opens, a small cadre of early risers enters. In this (relatively simple) situation, what waits might these shoppers experience?

Let’s put some numbers to the scenario, to enable calculations. We want the scenario simple enough to grasp it intuitively but still representative enough to mimic reality. Let’s use these assumptions.

  • 30 Shoppers
  • 15 items purchased per shopper
  • A per item checkout time of three seconds (i.e. scanning, bagging, etc.)
  • A added per shopper checkout time of 45 seconds (i.e. payment, etc.)
  • Three cashiers on duty

As the store opens, the shoppers surge in and after a few minutes the first of the 30 shopper arrivers at the cashiers. From that point, we will assume a shopper arrives at the checkout lines every 30 seconds.

Will these shoppers need to wait? How long? How many of them?

Let’s step through events to find out. When the first shopper arrives at the checkout line, that shopper will go without waiting to one of the three cashiers (i.e. all three are available). The second shopper arriving at the checkout line will see one cashier busy (with the first customer), but will see two cashiers with no line and go without waiting to one of them. Similarly, the third arriving shopper will see two cashiers busy, but the third cashier with no line and go there.

Now the fourth shopper arrives. To which line do they go? Well, we are now 90 seconds after the first shopper’s arrival (three shoppers later times the 30 second arrival interval). Will the cashier checking out the first shopper be available in time? Certainly. Checkout requires 90 seconds – 15 times 3 seconds, or 45 seconds, for the items plus 45 seconds more per shopper. So the first cashier has completed checkout for the first shopper when the fourth shopper arrives at checkout.

So the fourth shopper goes to the first cashier, without waiting. This sequence will continue, for example the second cashier will finish with the second shopper just as the fifth shopper arrives at the checkout line. Thus no shopper will experience a wait.

We can reach the same conclusion – no waits – another way, through a ratio. Specifically, with constant arrival intervals and service times, we divide the service time (the 90 seconds) by the servers (the three cashiers) and compare the result to the arrival interval. In this case, that ratio equals or exceeds the arrival interval (i.e. 90/3 is >= 30) indicating the servers can handle the load without delays.

Now overall, when all shoppers are checked out, the three cashiers will have handled 30 customers and 450 grocery items, and have spent 45 minutes checking out customers, i.e. 90 seconds per customer times 30 customers.

No shopper will have experienced any wait. The last shopper will arrive at the checkout lines after 15 minutes, i.e. 30 shoppers times the 30 second arrival rate, and finish 90 seconds later.

The Impact of Timing

We stressed that TIMING stands as the key variable, so let’s alter the scenario to demonstrate that. We will now assume the shoppers arrive at the cashier lines every 15 seconds.

Will the shoppers encounter waits? Let’s step through events. Just as with the 30 second arrival rate, the first three shoppers get served without delay, by the three cashiers. The fourth shopper, however, arrives 45 seconds after the first shopper. (Remember we have a shopper arriving at checkout every 15 seconds). Unlike the first scenario, where the first cashier was just completing servicing the first shopper, the first cashier has handled only 45 seconds of the 90 seconds required.

Thus, the fourth shopper now waits 45 seconds for the first cashier to complete the first shopper. In a similar fashion, the fifth shopper (going to the second cashier) and the sixth shopper (going to the third cashier) will also experience 45 second waits.

What wait will the seventh shopper experience? That shopper arrives 90 seconds after the first shopper, i.e. six shoppers later times the 15 second arrival interval. The first cashier, however, has just completed the first shopper, and will spend 90 seconds servicing the fourth customer. The seventh shopper thus waits 90 seconds.

This sequential lengthening of the wait times continues. By the last shopper, the waiting time grows to 405 seconds, almost seven minutes. Across all thirty shoppers, the total waiting time sums to 100 minutes, over an hour and a half of shopper time wasted waiting.

Now let’s compare the overall metrics of our two scenarios. With both a 30 second and a 15 second arrival interval, the cashiers check out the same number of customers (30) and items (450). The cashiers spend the same combined time checking out customers (45 minutes). The last shopper is finished checkout at about 16 minutes (a spreadsheet can be used to calculate this).

However, with the 15 second arrival time, extensive delays ensued.

What changed between the scenarios? The TIMING. Customers arrived with a different timing.

Notice no wage cost saving occurs by incurring the delays. In both scenarios, the grocery store pays for 45 minutes of cashier time.

Notice no extra revenue accrues. In both scenarios, shoppers purchase 450 items.

Thus, the financial position of the store remains unchanged in these two scenarios. The store experienced the same costs and revenues whether or not delays occurred.

Matching the Load

But still, what about adding more cashiers? Wouldn’t store costs go up if more cashiers were added in the second scenario?

Let’s do that then, let’s adjust the availability of the cashiers to match the timing of the customers. Given a 90 second checkout time, and an arrival rate at the cashier line of a shopper every 15 seconds, how many cashiers do we need?

We saw how to calculate that above, i.e. the checkout time divided by the number of cashiers must equal or exceed the arrival rate. With a checkout time of 90 seconds, we need six cashiers, so that our ratio of checkout time over servers equal or exceeds the 15 second arrival time.

So the store schedules the three extra cashiers – that eliminates any waits. Now, doesn’t that indicate that waiting timing does depend on the number of cashiers? And doesn’t that indicate that the store saves money by having fewer cashiers and imposing waiting time on the shoppers?

Not fundamentally. How much time in aggregate will the six cashiers require to checkout the shoppers, at the arrival rate of a shopper every 15 seconds? Exactly the same as before with three cashiers, they will require a combined 45 minutes. Regardless of the number of cashiers, and the arrival rate of customers, the aggregate time cashiers require for checkout depends on the number of items and customers.

In our scenario, with 30 shoppers at 15 items each, we could have one, two, three, four, five or six cashiers on duty, and the aggregate time spent by the cashiers for checkout would be 45 minutes. With one cashier, that cashier would take 45 minutes checking out shoppers; with two, each would spend 22.5 minutes for a combined total of 45 minutes; with three, 15 minutes, again for a combined total of 45 minutes; with four, each would spend 11.8 minutes; with five, 9 minutes; and with six, 7.5 minutes.

Very simply, a given shopper load translates to the same cashier time requirement to service that load, regardless of the number of cashiers (up to the point of matching the arrival rate). Having more cashiers reduces shopper delays, and reduces the length of time each cashier spends, but not the total combined checkout time.

What About Idle Time?

Very nice. But you might claim a certain sleight of hand has occurred here. Certainly, the amount of time actually checking out customers depends on the number of customers and the number of items, regardless of waiting lines and the number of cashiers.

But AFTER checking out all the arriving customers, what do we do with extra cashiers. Adding cashiers to eliminate delays does not increase aggregate cashier time actually servicing customers, but what about the idle time after servicing customers. In our early morning scenario, if we add three extra cashiers to handle the 15 second arrival rate, we have six idle cashiers after seven and a half minutes.

What do we do with them? After all, idle time costs money.


We redeploy them.

Grocery stores face many tasks in addition to checking out customers. Associates are needed to stock shelves, staff the customer service desk, place and remove sales tags, reshelve customer returns and abandons, check inventory, coral shopping carts, manage the container return machines, and on and on. At a management level, supervisors must do scheduling, provide oversight, record incoming goods receipts, and so on.

So at any given instant, a store almost certainly faces non-checkout tasks. And at any given instant, some, even a great number, of the non-checkout tasks are not time critical. Their completion can be staggered. Thus, during slack periods, cashiers can be redeployed to these other tasks, and during peak periods, cashiers can be brought back up front (or wherever the cash registers are) to check out customers.

Providing extra cashiers for peak loads thus does not of necessity require having extra cashiers standing by idly. Extra cashiers can become available through their redeployment to and from other grocery store tasks.

Very nice. That is simple to say, but difficult to do.

But not impossible. Management could take these or similar steps, to build a cadre of employees to shift in and out of cashier duty:

  • Hire/select a set of employees able and motivated to task shift
  • Train them for multiple jobs
  • Clear them, as needed, to handle cash and financial transactions
  • Work through any union classification or work rules
  • Overcome any stigma or preconceptions about the status of cashiering
  • Build an overall store culture that accepts task shifting
  • Adjust task and employee schedules to maximize task shifting flexibility

These are nettlesome steps for the store management, likely unpleasant and burdensome. But none of these steps – except possibly union rules – presents a hurdle outside the scope and skill one could expect of management at the individual grocery store level.

Missing the Surge

Assume then, that to a lesser or greater extent, the store can move employees to cashier positions to match shopper arrivals at checkout. As noted, store managers can accomplish locally. And actually I would say some, many, stores already do so, though some more successfully and consistently than others, and some of course abysmally.

Another aspect of timing, however, still remains an issue. When do we bring up extra cashiers?

Let’s return to our Saturday morning scenario, specifically the first scenario with 30 second shopper arrival rates at the checkout lines. Let’s assume that past experience indicates two cashiers can handle the early morning load, so we deploy the third cashier to another task.

However, the past experience has misled the store this morning – the load requires three cashiers. Do the shoppers experience waits? How long?

The answer depends on the response time. If we pull the third cashier up to a checkout register within a minute or two, essentially no waits ensue. If we place the third cashier in service with any longer a lag, delays build. With the help of a spreadsheet, we find the following average (across all 30 shoppers) and maximum (for any one shopper) delays for different lags in bringing up the third cashier.

  • 5 minute lag – average delay of 60 seconds, and maximum of 90 seconds
  • 10 minute lag – average delay 130 seconds, and maximum 180 seconds
  • 15 minute lag – average delay 180 seconds, and maximum 275 seconds
  • 20 minute lag – average delay 205 seconds, and maximum 390 seconds

If the arrival rate jumps to a shopper every 15 seconds with only two clerks, the delays spiral almost out of control. A small 5 minute lag in pulling the third cashier forward to a register imposes an average delay of 280 seconds, and one unlucky customer waits 500 seconds.

Thus quick and accurate response to shopper load must accompany an ability to redeploy employees as cashiers to handle that load.

Predicting the Load

Our Saturday scenario showed that waiting lines can build, dramatically, in minutes. For success then, we need a method to monitor, even predict, shopper load on a similar scale, i.e. minute-by-minute.

Historic data will help. Such data would assist in setting the general number of cashier-capable employees to be scheduled to work. So for example history may indicate the store rarely, if ever, needs more than four cashiers Tuesday night, while up to ten are needed on a Saturday afternoon.

But beyond that, beyond giving guidance on how many cashier-capable employees to call into work, history provides no help. History lacks sufficient specificity to guide the minute-by-minute decisions on splitting the cashier-capable cadre between cashiering verses non-cashiering tasks.

A store could make, or attempt to make, that split by watching the waiting lines at the cashiers. That would seem simple enough, and would work, partially. In fact, well-managed stores do that now – when lines get long, extra cashiers, if available, are put on the registers.

But once lines form, the battle can be lost. Reducing lines requires not only adding enough cashiers to handle the ongoing surge in customer load, but enough to also work down the prior surge that created the backlog of shoppers now in line. It may not be possible to open cashier lines in sufficient number and with sufficient speed to do that.

Stores need more than just reactive information on current cashier lines; they need forward-looking information to predict future cashier lines. How can stores get such information? Well, at any point, the future load on cashiers consists of the present shoppers in the store. So the information needed is right there. Stores can get a good handle on future load by counting shoppers as they enter, and monitoring their numbers as they shop and check out. Cameras, RFID (radio frequency) tags in shopper carts, electric eyes, cash register data, either individually or in tandem could collect such real time data.

Cost and complexity do become an issue. While building a flexible employee force might fall within the scope and ability of the local grocery manager, real time data collection and forecasting most likely would not. Hardware (cameras, electric eyes, etc.) must first be installed, and then integrated into software that, continuously, compiles and converts the data streams into a forecast of cashier demand.

Such a system may not rival building rocket ships, but the necessary equipment and software can’t be purchased at Home Depot or Best Buy. This doesn’t say real time data systems aren’t available. A quick web search for “Shopper Counter Systems” shows major firms that stand ready to implement shopper tracking. But the grocery chain national office would most likely need to take the lead.

Full Scale Simulations

Our discussion has postulated that three techniques – employee redeployment, rapid response and load forecasting – will shorten waiting times, ease customer aggravation and, importantly, still use employee time efficiently.

Will that theory work in real life? It did in our Saturday morning example, but while instructive, that example was admittedly a bit simplistic. Will our techniques work in a more robust simulation, one closer to real life? Let’s find out, by expanding our modeling parameters as follows:

  • Two hour time period (compared to15 minutes for the Saturday scenario)
  • Eleven cashier positions (up from three)
  • Two of the eleven cashiers serving express (up from no express)
  • Three self service lines adding to the 11 cashier positions (up from none)
  • Variable # of items purchased (compared to the same for each shopper)
  • Maximum of 50 items (up from 15)
  • Random arrival times (compared to a constant)
  • Shopper arrival rates up one every 4 seconds (up from every 15 seconds)

With our model now expanded, we stand ready to play store supervisor. Can we keep lines short but not waste cashier time?

Let’s use our first scenario as a baseline. No load forecasting will be used; we want the baseline to provide a comparison point to see the impact of such forecasting. Similarly, we will pick a middle ground for cashier deployment rules, again to allow comparison to more extreme rules. Our baseline will thus be as follows:

  • Don’t use/deploy load forecasting
  • Pull in extra cashiers when lines grow to longer than two minutes
  • Redeploy a cashier to another task if lines are less than a minute
  • Don’t pull back a redeployed cashier in less than ten minutes

These rules recognize start up time. When a redeployed cashier moves between tasks, a transition time exists, first just walking through the store to the new task, but also setting up for the new task. So employees needs to stay on a new task long enough to get through startup time to a point of actually getting something done.

Note also our scenarios do not assume everybody can do cashiering. Twenty different employees might be scheduled at a given time. But the deli counter attendants likely have no slack, and a few employees likely could not effectively manage switching tasks continually. Thus, in our scenarios, a set cadre of employees, eleven, represents the universe for cashiering and redeployment.

Given the rules and provisos above let’s run a simulation. To keep some brevity in the discussion, we must skip the details – these details comprise a large but manageable Excel file that tracks customers, cashiers, and load second-by-second. Overall, the simulation models 531 shoppers arriving in waves at the cashiers across two hours, with cashiers coming forward, or being redeployed to non-cashier tasks, depending on the customer load and deployment rules.

Running our baseline simulation gives the following:

  • Average waiting time (across the 531 shoppers) of 87 seconds
  • Average waiting time in the peak 20 minutes (144 shoppers) of 159 seconds
  • 74 employee transitions, i.e. moving to or from cashiering
  • 114 idle minutes

For a perspective, the 87 second average waiting time compares reasonably to the 120 seconds required on average to checkout a shopper, i.e. the wait is less than the checkout. The 114 idle minutes is only 9% of the total employee time across the two hours.

The 74 transitions, though, represents a good bit of churning back and forth. We maybe be able to sell our employees on being flexible, but 74 transitions in two hours may stretch their tolerance.

Similarly, the 159 second wait during peak will definitely stretch shopper patience. During the peak 20 minutes, a shopper will pull up to a line, every line, to see a customer with up to 50 items being checked out, and another customer with a possibly equally full basket waiting.

Can we do better? Possibly. To find out, we will use a different trade-off in our rules. We will lower the shopper wait threshold for bringing added cashiers forward (pull cashiers forward at just 50 second line waits, down from two minutes) but increase the minimum redeployment time for pulling employees back to cashiering (15 minutes, up from just 10).

This, unfortunately, fails. While pulling cashiers forward with a lower waiting line threshold might seem as if it would reduce shopper waits, the 15 minute minimum for pulling a prior cashier back constrains us. We simply can not get enough cashiers forward fast enough. The result? All the metrics get worse, i.e. longer waits, more transitions, more idle time.

Let’s then flip to an opposite set of rules. We will let lines grow to 4 minutes. But we will pull employees forward to be cashiers immediately when lines hit that wait threshold, regardless of how long, or short, a time has elapsed since that employee was just a cashier.

We again see little improvement. In fact, average wait increases to 150 seconds, and the peak period average wait to 188 seconds.

We remain concerned, also, at the abruptness of pulling employees forward. Employees on alternate tasks (say putting back returns, or stocking shelves) would find themselves pulled forward unexpectedly, with no warming, right in the middle of whatever they were doing.

We could try a “double” extreme scenario. That would combine the short 50 second wait time for pulling forward, with immediate pull forward when lines reach that wait time. But we won’t. Chaos would reign. Employees would revolve back and forth between cashiering and other tasks so frequently they would wonder if we are thinking straight.

Thus, we will now consider load forecasting. As store supervisor, we have concerns over the cost and effort to implement. But we relent, if just to see what the modeling will say.

For modeling, we will project that the forecasting system can give us a five minute forward look at average waiting time. We thus add that into our rule, i.e. if the current wait, or the projected future waiting time, exceeds 50 seconds, we will pull cashiers forward.

We keep the 15 minute minimum for redeployment, i.e. if a cashier goes out to do an alternate task, they do not come forward to cashier for at least 15 minutes. We judge this crucial – the forecasting system must let us have some sanity and stability to our pulling employees in and out of the cashier position.

The result? Thankfully good. Adding in forecasting provides moderate, and in cases, strong improvement. Compared with our baseline scenario, we see the following:

  • Average waiting time of 37 seconds (vs. 87)
  • A waiting time in the peak 20 minutes of 89 seconds (vs. 159)
  • 47 employee transitions, i.e. moving to or from cashiering (vs. 74)
  • However, 298 idle minutes (vs. 114)

Forecasting gives sizeable reductions in waits, reduces transitions noticeably, and allows a solid 15 minutes of uninterrupted redeployment time.

Costs and Revenue

But idle time increases. And idle time costs money. With forecasting, idle time increased by three hours (298 minus 114 is 184 minutes) over our baseline scenario. With a loaded cost of $33/hour, this idle time translates to $100 in wage costs in the two hours. That represents a greater than 10% increase in cashier wage costs.

By comparison, however, this $100 dollar cost, and 184 minutes of extra idle time, saves over 400 hours of customer wait time (about 50 seconds a customer times the 531 customers in the two hours). Quick division shows that cost equates to just 25 cents an hour saved.

Will quicker lines bring added revenue, to cover this cost? I would argue certainly. Given the large waiting line reductions, we can market the quicker lines and (given we consistently achieve such quicker lines) most likely garner extra business.

Now, admittedly, any added revenue must cover not only the idle time, but the implementation of the forecasting system.

However, added data could bring unexpected benefits. Our modeling focused on periods in which the stored experienced high and chaotic demand, and highlighted techniques for handling such high and highly variable demand without dramatic increases in costs.

But stores at time do not have such chaotic or heavy demand. Just like we have seen long lines, we also know times (and try to go to the store at those times), where no or few lines exist. A forecasting system, along with an employee force trained and motivated for flexible redeployment, could reduce idle time in such slack periods.

Such savings could be significant, possibly astounding. And we could extend the load forecasting to the deli counter, or bakery, or service counter.

A load forecasting system, if sufficiently precise, could produce revenue gains and cost savings that pay for the system.

Bottom Line

What do we have then?

We started with a question of why don’t grocery stores have more cashiers. After stepping through some considerations and modeling (well actually a good number of considerations and a good bit of modeling), we found techniques for shortening waits.

Along the way, a principle emerged – creating long waiting lines does not reduce the actual combined time cashiers require to checkout a set group of shoppers. Regardless of waiting times for the shoppers, the cashier time actually spent checking out shoppers depends on the number of shoppers and items.

Waiting lines emerge from an imperfect matching of that cashier time with the arrival of shoppers.

And that was where our techniques entered. Our techniques – employee redeployment, rapid response and load forecasting – aimed to move around the cashier availability to match shopper arrival, without generating side effects, i.e. idle time, chaotic employee deployment, costs.

So next time you wait, imagine, if you are so inclined, what could be done. While what could be done might not be done, thinking about might make the time go faster.

Using Demographic Questions For In-Depth Data Analysis

Demographic questions help to determine factors that could influence a respondent’s choice of answers, which means that gathering this information from your survey audience is a great way for you to be able to split your respondents into certain groups and see how your groups vary with their answers.

For example, you could split your respondents into groups according to their geo-location and see how people from different locations compare to one another. This would be particularly valuable information if the goal of your survey was to determine where you might open a new store, for instance.

Here are some examples of demographic questions and how you can use them to assist in your survey questions:

1. What is your age?

One of the most used demographic questions asked in surveys is about age. The age of your respondents can sometimes greatly alter the way that they answer your questions. For example, if you were to ask about a recent computer game that has been released, you are likely to get very different responses from respondents over 65 years than you would from your 18 – 24 years old respondents.

If you have a few demographic questions to ask, asking for a respondents age can also be a good way to ease people into answering this somewhat personal questions as it is an easy question to answer.

2. What is your ethnicity?

Ethnicity questions can provide an interesting contrast when it comes to comparing the answers of respondents from different racial or cultural backgrounds. For example, if you are asking questions regarding stereotypes in the media, you may get different opinions from a White/Caucasian person than you would from a Latino respondent.

Asking a person to identify their ethnicity in a survey can be a slightly precarious question, therefore we recommend that you always allow a respondent to choose a “prefer not to say’ option for these types of questions.

3. What is your marital status?

Questions regarding the marital status of your audience can be useful as it can give you an insight into how the household is made up. For example, if you are asking about a respondent’s ideal night out, someone who is married or in a domestic partnership may have different opinions on topics than a single person.

4. What is your highest level of education?

The level of education of a respondent may affect the answers that they give to certain questions. Someone who has had vocational training may have different opinions on topics than those who have a Masters degree, for example.

5. What is your current employment status?

Employment status can give a good contrast of opinions from differing demographic groups, especially when it comes to financial questions later on in the survey or opinions on social statuses. An unemployed person looking for work may have particularly differing views on job prospects than someone who is in full-time employment.

It is important to remember that demographic questions are inherently personal and sensitive to certain extents, so they should be treated as such. Allow the customer to skip the questions or have the option to choose not to say to reduce the risk of your respondent abandoning your survey.

There are many other demographic questions that you can ask in your surveys to help you to group your respondents for analysis. Other demographic questions could be income, number of children, geo-location, weight and gender, to name a few.

The Other Things Your Children Learn In Preschool

It isn’t mandatory to send your child to preschool. In fact, if you’re a stay at home parent, you may not feel the need to pay for care outside of the home. But the truth of the matter is that preschool isn’t just about paying professionals to watch your children for you. There are a multitude of additional benefits that come with attending an early development children’s program.

Improved Communication and Socialization Skills

A childcare center regularly gives children the opportunity to communicate and socialize with other children of their age. The skills learned through personal interaction will be very helpful when they enter kindergarten. You’ll find that these skills can even help your communication at home.

Learning to Work Well with Authority

Obeying the orders of a parent is substantially different than obeying the instruction of a teacher. A teacher is initially foreign to a young child, having not been involved in the majority of their development thus far. Your child will be forced to interact with numerous authority figures throughout their school years and beyond. Getting them started in preschool will help them get used to the idea of instruction, regulation, and discipline as a means of consequence.

A Head Start in Learning

Many of the things learned in these programs are essentially small seeds-initial exposures-to concepts that will be expanded upon in their later school years. Math and problem solving skills will be planted in your child’s schematization of the world, allowing them to adjust and adapt in reaction to obstacles and later conceptualize imaginary scenarios as a means to answering abstract questions. This will give them a head start in the classroom, and make the transition into school life much easier.

Creativity Encouragement

Numerous artistic activities, along with interactive games are implemented throughout the day, fostering your child’s creativity and ingenuity. You will notice signs of increased activity in the home, whether it be in the narratives of their imaginary play, or in their answers to questions. In addition to standard drawing and coloring, you child can be exposed to:

* Role Playing
* Acting
* Puppeteer work
* Clay creation

Be prepared to engage in these activities at home, having the necessary craft supplies to continue the learning beyond the school day.

Learning to Share

Something young children are notorious for is the inability to share, whether it be with toys, treats, seats or other things. Early exposure to other children will help your child understand the transaction of sharing and the joys of group play. Preschool is a safe, controlled environment where the beginning forms of empathy sprout.

Make sure to schedule an initial meeting with potential facilities before making any commitments. This will give you an opportunity to see the grounds, amenities, and teaching practices that are used. It will also give you a chance to meet each teacher, and to have your questions and concerns directly addressed.