The Brain Behind The Big, Bad Burger And Other Tales Of
Business Intelligence
Business intelligence systems have, for the most part, been dreary
failures. But not in the restaurant industry. There, the payoffs have been
significant. So what have you been doing wrong? And what are they doing right?
Restaurant chains such as Hardee's, Wendy's, Ruby Tuesday, T.G.I. Friday's and
others are heavy users of business intelligence software. They use BI to make
strategic decisions, such as what new products to add to their menus, which
dishes to remove and which underperforming stores to close. They also use BI for
tactical matters like renegotiating contracts with food suppliers and
identifying opportunities to improve inefficient processes. For example, in June
2003, Wendy's decided to accept credit cards in its restaurants based on
information it got from its BI systems, which include IBM DB2 OLAP software, IBM
and Compaq servers, databases from Hyperion and Oracle, Cognos Powerplay tools,
and software from Crystal Decisions and Arcplan. Because of that decision,
Wendy's restaurants have boosted sales; customers who use a credit card spend an
average of 35% more per order than those who use cash, according to Wendy's
executive vice president and CIO John Deane.
It's been called "the fast food equivalent of a snuff film" by one health and
nutrition advocacy group. Jay Leno made cracks about it on The Tonight Show.
Even The New York Times devoted an editorial to its excesses.
The Monster Thickburger, the latest piece de resistance from burger joint
Hardee's, consists of:
Two charbroiled certified Angus beef patties, each weighing in at a third of a
pound
Three slices of American cheese
Four crispy strips of bacon
It's topped with a dollop of mayonnaise that oozes from a toasted buttery sesame
seed bun.
The Monster Thickburger tips the scales at a whopping 1,420 calories and an
artery-clogging 107 grams of fat. It quite possibly is the most fattening
mass-produced burger on the planet, and it's selling like gangbusters, according
to Jeff Chasney, CIO and executive vice president of strategic planning at CKE
Restaurants, the company that owns and operates Hardee's.
You'd think that CKE would have thought twice about rolling out such an
over-the-top concoction in the midst of a national obsession with the growing
epidemic of obesity. But CKE was able to introduce the Monster Thickburger
nationwide on Nov. 15, 2004, with such confidence (if not impudence) that the
public would receive it with open mouths because of the insights the company
obtained from its business intelligence (BI) system. BI refers to a variety of
software applications that analyze an organization's raw data and extract useful
insights from it. BI as a discipline is made up of many related activities,
including data mining, online analytical processing, querying and reporting.
CKE used its BI system, known ironically inside the company as CPR (CKE
Performance Reporting), to monitor the performance of its big, bad burger in
test markets. Specifically, CKE used BI to see if the hamburger was actually
contributing to increases in sales at restaurants or if it was just
cannibalizing sales of other, lesser burgers. The company wanted to evaluate
whether the increases in sales from the burger were worth the cost to produce
it. CKE used its BI software to study a variety of factors--such as menu mixes,
the cost to produce a Monster Thickburger, average unit volumes for the
Thickburger compared with other burgers, gross profits and total sales for each
of the test stores, and the contribution that each menu item (including the
Monster Thickburger) made to total sales. Because the Monster Thickburger
exceeded expectations in test markets, the company decided to roll it out
nationwide and to devote around $7 million in advertising to promoting it. CPR
gave CKE the confidence it needed to introduce such a burger and to know that
the advertising dollars behind it wouldn't be a waste.
And, in fact, it's been a resounding success; sales of the burger bomb continued
to exceed expectations in December 2004. Sales at Hardee's stores that have been
open at least a year were up 5.8 percent for December, and "the Monster
Thickburger was directly responsible for a good deal of that increase," says
Brad Haley, Hardee's executive vice president of marketing.
Smart Food
Restaurant chains such as Hardee's, Wendy's, Ruby Tuesday, T.G.I. Friday's and
others are heavy users of BI software. Many of the big chains have been using BI
for the past 10 years, according to Chris Hartmann, managing director of
technology strategies at HVS International, a restaurant and hospitality
consultancy. They use BI to make strategic decisions, such as what new products
to add to their menus, which dishes to remove and which underperforming stores
to close. They also use BI for tactical matters like renegotiating contracts
with food suppliers and identifying opportunities to improve inefficient
processes.
Because restaurant chains are so operations-driven, and because BI is so central
to helping them run their businesses, they are among the elite group of
companies across all industries that are actually getting real value from these
systems. Want proof?
Carlson Restaurants Worldwide, the privately held company that operates T.G.I.
Friday's and Pick Up Stix restaurants, saved $200,000 in 2003 by renegotiating
contracts with food suppliers based on discrepancies between contract prices and
the prices suppliers were actually charging restaurants. Carlson's BI system,
which at the time was from Cognos, had identified these discrepancies.
Ruby Tuesday's profits and revenue have grown by at least 20 percent each year
as a result of the improvements the chain has made to its menu and operations
based on insights provided by its BI infrastructure, which consists of an Oracle
data warehouse, analytical tools from Cognos and Hyperion, and reporting tools
from Microsoft.
CPR helped CKE, which was on the brink of bankruptcy five years ago, increase
sales at restaurants open more than a year, narrow its overall losses and even
turn a profit in 2003. A homegrown proprietary system, CPR consists of a
Microsoft SQL server database and uses Microsoft development tools to parse and
display analytical information.
In June 2003, Wendy's decided to accept credit cards in its restaurants based on
information it got from its BI systems, which include IBM DB2 OLAP software, IBM
and Compaq servers, databases from Hyperion and Oracle, Cognos Powerplay tools,
and software from Crystal Decisions and Arcplan. Because of that decision,
Wendy's restaurants have boosted sales; customers who use a credit card spend an
average of 35 percent more per order than those who use cash, according to
Wendy's executive vice president and CIO John Deane.
These restaurant chains' successes are unusual considering the indigestion
companies in other industries have gotten from their BI initiatives. "Most BI
implementations fall below the midpoint on the scale of success," says Ted
Friedman, an analyst with Gartner. Restaurant chains use BI effectively and
realize value from it for a variety of reasons, and other industries would do
well to pay more attention to restaurant chains, according to Hartmann. Because
their industry is so competitive, they have to be agile, so their cultures are
accustomed to rapid change. Also, their BI initiatives are closely aligned with
their business strategies, and the insights that their BI systems produce
contribute to improving operations and the bottom line. Finally, they've found
ways to address three of the biggest barriers to BI success: having to winnow
through voluminous amounts of irrelevant data, poor data quality and user
resistance.
"If you're just presenting information that's neat and nice but doesn't evoke a
decision or impart important knowledge, then it's noise," says CKE's Chasney.
"You have to focus on what are the really important things going on in your
business," he says.
At Ruby Tuesday--as at most restaurants and, indeed, in most companies--sales,
products and service are the most important levers in its business. So, in
August 2003, when the chain's BI system identified a restaurant in Knoxville,
Tenn., that was underperforming, it used the very same system to drill down into
that store's specific problems in an effort to help the company determine what
corrective actions to take.
The company's BI software indicated that customers were waiting longer than
normal for tables and for their orders once they were seated. It was a recipe
for customer dissatisfaction, and of course poor sales. Management at corporate
headquarters wanted to know what specifically was wrong. Was the restaurant not
adequately staffed? Was the problem with the kitchen staff, a server, an
assistant manager, a general manager--or with something beyond the company's
control, like the location?
Managers used BI tools to study food costs. High food costs might have indicated
inadequately trained cooks who were ruining a lot of food before getting dishes
right, which would have contributed to increased wait times. But food costs were
normal.
Managers then assessed the time it took for a table to change hands from one
patron to the next, using the BI system to calculate the time between when a
waitstaffer opened a check on the point of sale to the time the customer paid
the tab. Nick Ibrahim, senior vice president and CIO of Ruby Tuesday, says the
average time it takes a restaurant to turn over a table from one customer to the
next is 45 minutes. So if the company sees in its BI system that it takes 55 to
60 minutes to close a check at a particular restaurant, people aren't getting
their food as fast as they should. (The problem is rarely a matter of diners
lingering over their meals, especially if it's taking the waitstaff at every
table 55 minutes to close the check.) Management concluded based on this
information and by visiting the restaurant that the long wait times were a
result of increased demand. The area had been through an economic boom, and the
restaurant was running at full capacity. The company made changes to the layout
of the kitchen, the placement of food and the location of cooks so that everyone
had easy access to the food and equipment they needed to produce dishes faster,
to move more customers through the restaurant and ultimately to increase sales.
The changes increased the rate at which tables were turned by 10 percent, which
in turn decreased wait times for customers.
Insights Are the Meat; Data Is the Relish
The problem with so many BI tools, says Chasney, is that they're no different
from the standard corporate reporting tools that have been around for years,
which churn out old data like curdled butter and don't provide information that
executives can chew on. If companies really want to get value from BI, he says,
they need a system that provides them with insights, not just mountains of data.
"There's nothing worse, in my opinion, than a business intelligence system that
reports changes on a weekly basis," he says, because those systems don't provide
any context as to what factors are influencing those changes. Without that
context, you don't know whether the data is good or bad; it's just useless.
When charting a course for BI, Chasney advises companies to first analyze the
way they make decisions and to consider the information that executives need to
facilitate more confident and more rapid decision making, as well as how they'd
like that information presented to them (for example, as a report, a chart,
online, hard copy). Discussions of decision making will drive what information
companies need to collect, analyze and publish in their BI systems.
When Chasney started building CPR in 2000, he asked the company's CEO and the
chief operating officers of CKE's three restaurant chains--Hardee's, Carl's Jr.
and La Salsa Fresh Mexican Grill--what information is most important in their
efforts to run the company. The CEO wanted to know what caused changes in sales.
The COOs wanted something that would indicate business opportunities they could
pursue as well as clear indicators as to which restaurants were underperforming.
The discussions taught Chasney that BI systems need to focus on a company's most
important performance indicators-- including sales and cost of sales;
exceptions, such as those areas of the business that are outperforming or
underperforming other segments; and historical and forward-looking business
trends--if they're to provide the company with any value.
Good BI systems also need to give context. It's not enough that they report
sales were X yesterday and Y a year ago that same day, says Chasney. They need
to explain what factors influencing the business caused sales to be X one day
and Y on the same date the previous year. CPR uses econometric models, which the
company reviews and refines each month, to provide context and to explain
performance. The econometric models take into consideration 44 factors,
including the weather, holidays, coupon activity, discounting, free giveaways
and new products. If the CEO wants to find out why sales were down on any given
day at Hardee's, all he has to do is click the "explain" button on his computer
screen, and the model performs its magic. The CEO will see, for example, that 5
percent of the 8 percent decrease was due to torrential rain in the Northeast
and 2 percent was due to free giveaways.
"If your business intelligence system is not going to improve your decision
making and find problem areas to correct and new directions to take, nobody's
going to bother to look at it," says Chasney.
Start with the Freshest Ingredients
The key to getting accurate insights from BI systems is standard data. "Data
quality remains a very overlooked issue in business intelligence, but a massive
one," says Gartner's Friedman. "I continue to see failures due to a lack of
attention to data quality." Data is the most fundamental component of any BI
endeavor. It's the building blocks for insight. Companies have to get their data
stores and data warehouses in good working order before they can begin
extracting and acting on insights. If not, they'll be operating based on flawed
information.
Ruby Tuesday's Ibrahim advises companies to develop plans that outline what
they're going to do with data once they get it, practices for preventing
redundant data and methods for organizing it in a way that makes sense to the
business. For instance, Ruby Tuesday organizes its data around three
categories--sales, labor and food costs--that happen to be the key drivers of
its business. Those three categories are tracked in an Oracle database and put
into separate table spaces for ease of reporting and processing, Ibrahim says.
That way, information on what products are selling does not get mixed up with
information on labor and vice versa.
Knowing that the key to using information to improve decision making is ensuring
that the transactional data collected at the point of sale is consistent and
accurate, Ibrahim standardized all of the company's restaurants (700 at the
time), including those run by franchisees, on a common technology platform in
2001. He also moved the company onto a Microsoft SQL server and
open-architecture databases from Oracle and Sybase, which makes it easier for
business analysts to get to the data they need. The open architecture lets
analysts run specific queries against databases when they're looking to find
out, say, how many margaritas the company sold on Cinco de Mayo, rather than
having to sift through mountains of data to get the answer.
Unfortunately, few companies have the luxury of replacing disparate technology
with common systems across all of their units. Wendy's is a case in point. While
all 1,500 of the company-owned restaurants use the same technology,
approximately 5,000 franchises don't. The sales data that franchises send to
corporate headquarters looks different from the data that company-owned stores
submit because franchise data is reported on a weekly basis at an aggregate
level. By contrast, more granular transactional data collected directly from the
point-of-sale systems of company-owned stores is sent to corporate headquarters
on a daily basis. As a result of those differences, Wendy's corporate doesn't
have the highest possible level of visibility into its franchise operations.
Wendy's Deane acknowledges that this less-than-ideal environment for BI creates
problems for the company when it needs to compare aggregated sales information
from franchises with transactional data from company-owned stores--it's a
hamburgers to cheeseburgers comparison. He says the company needs to
increasingly make these comparisons as it looks to expand the pool of stores it
uses for product testing and as it attempts to improve supply chain integration.
To compensate for their suboptimal data collection environment, Deane is using
an XML standard to collect more detailed information from franchisees who
operate a large number of stores. (For smaller franchises, Wendy's uses a
Web-based data collection system.) He also uses heuristics, or rules of thumb,
based on activity at company-owned stores to extrapolate meaning from the
aggregate data that franchises provide. For example, if a franchise- owned store
does $30,000 worth of business in a week, Wendy's corporate can make assumptions
as to how that $30,000 would break down into sales of french fries, baked
potatoes, hamburgers, chicken sandwiches and the like based on sales from
company-owned stores in similar markets with similar aggregate sales histories.
Proxies such as these may not be perfect, but they are a practical workaround
and can be modified as needed to accommodate further integration with other
systems, like the point of sale. Wendy's has no plans to get its franchises on
standard technology because it sees its franchisees as entrepreneurs capable of
making their own decisions about their operations, including choice of
technology.
Because Wendy's is starting to understand the importance of having standard data
to fuel business initiatives such as supply chain integration, the company was
able to replace the phone lines and unstable modems that stores were using to
transmit data to headquarters with a satellite connection in September 2002. The
new, stable network helped improve the amount and quality of data that
headquarters collects from both franchise- and company-owned stores. Where in
the past Wendy's would miss information from as many as 40 stores out of 1,200
due to unstable modems, it now gets consistent information from 1,483 out of
1,488 stores every night.
Why Force-Feeding Won't Work
Like so many technology projects, BI won't yield returns if users feel
threatened by, or are skeptical of, the technology and refuse to use it as a
result. And when it comes to something like BI, which, when implemented
strategically ought to fundamentally change how companies operate and how people
make decisions, CIOs need to be extra attentive to users' feelings.
When Wendy's began using its BI system to generate sales forecasts for stores,
operators were skeptical. They didn't think technology could possibly take into
consideration how local factors- -such as weather, events and traffic
patterns--affect their sales. Deane recognized that it's tough for people to
quit relying on their experience and gut, so he listened to operators' concerns.
Instead of forcing them to accept the forecasts, which he knew to be extremely
accurate, he told them they could modify the forecasts from the BI system so
long as they explained why and provided they later compared actual sales with
what they forecasted and what the system predicted. The operators who modified
the forecasts realized that the technology was often more accurate than they
were. When they saw that they could improve their operations by better staffing
their restaurants and more accurately ordering food to meet forecasted demand,
they increasingly embraced BI. In effect, Deane let the users come to the trough
on their own terms.
One might argue that Wendy's could have gotten better results more quickly had
it forced store managers to use the forecasts. However, if it had, it would have
run the risk of facing mutiny from the operators. And had store operators fought
the forecasts, that would have disrupted operations much more than the delay the
company experienced by letting operators modify the forecasts. Deane says being
sensitive to users' concerns was more important, even at the expense of slowing
down the rate of return.
"Trying to convince 1,500 store managers to automatically accept a new tool that
is going to have an impact on their ability to perform in their store is no
trivial matter. You have to be very, very careful how you deal with the change
management and the acceptance side of an implementation," says Deane. And if you
do it right, you can realize an ROI of 430 percent over a five-year period,
according to IDC (a sister company to CIO's publisher). Adds Deane, "Of all the
projects that one attempts to do as a CIO, business intelligence, if well
managed (and it's not always well managed) contributes far, far more than it
costs."
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