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In the CSU Online Library, using the Business Source Ultimate database, search for and read the article titled “How Barbie Lost her Groove,” by Nash and Duvall (2005). Compose a persuasive response that includes the following elements:

  • Explain why Mattel’s managers were able to slowly change decision making over time and what kinds of cognitive errors contributed.
  • Explain and comment on any factors related to organizational culture and innovation within Mattel’s setting that might have influenced the company to move in a more positive direction.

Your response should be two pages in length, not including the title page or reference page. You are required to cite at least one article from the CSU Online Library (not including the referenced case study article). All sources used must be referenced; paraphrased and quoted material must have accompanying in-text citations in the proper APA format.

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How Barbie Lost Her Groove,” By Nash And Duvall (2005). Compose A Persuasive Response That Includes The Following Elements:
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Surprise is what business schools teach you to avoid. Mattel’s research .showed Barbie sales falling as girls sought a cooler doll. But Mattel misjudged how, and how fast, to move. Learn from Mattel’s mistakes in gathering— and acting o n – competitive intelligence.



MATTEL BASE CA. Headquarters: 333 Continental Blvd,, El Segundo, CA 90245 Phone:(310)252-2000 Business: Makes and markets toys, including Barbie, Hot Wheels and Fisher-Price products. Chief Executive Officer: Robert Eckert Financials in 2004: S5.1 biliion in sates; $573 million in profits; net profit margin of 11%, Challenge: To maintain Barbie’s place as the top-selling fashion doll in the world, and a cash cow for Mattel, amid an onslaught of doll challengers, BASELINE GOALS:

Generate 50% of sales outside the U,S,, up from 42% last year Cut overhead costs as a percentage of sales to between 17% and 18%, down from 20% last year. Increase operating margin as a percentage of sales to 20%, up from 14% last year. Continue to decrease reliance on Wal-Mart, Toys R Us and Target, which combined accounted for 46% of sales last year, down from 50% in 2002, in favor of smaller retaifers and online sales.

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No blonde hair, sugary smile or impossible figure, which for four decades had defined Mattel’s iconic Barbie doll. Girls who wanted attitude and ethnicity, not pert and pale, bought $20 million worth of Bratz dolls in the first six months they were out, and the doll line went on to win the People’s Choice Toy ofthe Year award from the Toy Industry Association.

MGA had hit a coveted demographic—girls age 6 to 12— dead-on.

And yet, Mattel was uncharacteristically sluggish in response. It would be a full 14 months before Mattel came out with a Barbie offshoot, the My Scene dolls, that featured the right mix of vivid makeup and edgy clothes that young girls now craved.

The gap was long enough for Bratz to get a platform- booted foot in the door and stay there. Unlike doll makers before it, MGA was able to seize, and keep, market share.

Woridwide sales of Bratz reached S700 million last vear —growing more than 45% over the previous 12 months, while Barbie has stagnated at the same S1.5 billion level since MGA introduced Bratz four years ago. Barbie’s share of the fashion doll market has shrunk from 75% in 2000 to roughly 6Q% today, says Sean McGowan, a financial analyst at Harris Nesbitt Gerard in New York.

Today, new rivals—Janay and Friends from Integrity Toys, Girls on the Go from Tolly Tots, and the Princess line from Disney—are are all crowding into the doll aisle.

“It’s a business that’s more up for grabs than ever before,” says Nancy Zwiers, who led worldwide marketing for Barbie for five years, “Now that Bratz has made inroads, it’s become

apparent to other companies that they can, too,” Mattel had the means to see it ail coming. Yet it was still

caught off guard. The toymaker has a world class corporate intelligence

system that consists of teams of research scientists who manipulate internal and third-party data with statistical analysis and business intelligence software,

Pre-Bratz, they studied point of sale numbers from Wal- Mart and other key retailers that showed zigzagging sales for Barbie, The company also had “psychographic” data about how girls of different ages play, drawn from Mattel’s private focus groups and observations at its own Child Test Center. That data suggested, for instance, that older girls— age 8 to 12, known to marketers as “tweens”—were losing interest in traditional Barbie, attracted instead to pop stars in heavy makeup and trendy clothes.

Identifying threats eariy is the goal of a good business intelligence program. But intelligence is only part of the equation, says George Day, a marketing professor at tbe University of Pennsylvania’s Wharton School who has studied several industry giants that have missed cues from the marketplace and subsequently suffered. You need sys- tems—human and technological—to interpret data, and then you need the wherewithal to act on it.

And that is where Mattel stumbled, according to con- sultants, such as Day, and several former Mattel managers, including Bruce Stein, who was chief operating officer and president of Mattel Worldwide from 1997 to 1999. ‘Iwo fac- tors blunted Mattel’s reaction, they say: internal challenges that distracted management, and the company’s disinclina-

tion to change its key product. Mattel declined requests for interviews, citing busy executive schedules.

Mattel did take tentative steps in 1999 and 2000 to address twccns’ changing tastes with dolls such as Diva Starz, but the moves didn’t click. Diva Starz’ bright facial features and hipper clothing, for instance, stopped short ofthe new provocative styles being blasted on TV and in magazines.

Mattel, says Jim Silver, an advisor to the Toy Industry Association, a trade group, didn’t act swiftly and forcetijlly enough to insulate its cash cow. The company, he says, “thought [Bratz] would come and go,” just another challenger without endurance. In 1991, for example, Mattel heat I lasbro’s blonde, busty Miss America doll by introducing its own American Beauty Queen Barhie. Likewise, Tyco Toys’ Little Mermaid doll initially skyrocketed but eventually drowned under a wave of mermaid Barbies from Mattel.

Now, Mattel finds itself fully engaged in a no-holds- barred attempt to outmarket Bratz, incite new doll mer- chandising trends and keep Barbie on her throne. Mattel says it won’t let up.

It can’t. Last year. Barbie, a perennial top seller, accounted for

30% of Mattel’s S5.1 billion in sales and an estimated 40% of its $573 million profit. In the past 30 years, the Barbie product line has produced approximately $24 billion in sales.

When Barhie is at risk, Mattel is at risk- “This is what happens when you get blindsided,”

Day says. The Mattel-MGA battle holds lessons for any company

trying to create an effective market intelligence system. Any company can develop accurate research and sophisticated technology to manipulate it. Stein points out: “The key is in how data is interpreted and, secondly, management’s will- ingness to respond to it.”

FEMALE INTUITION Well before the Bratz came hip-hop- ping along, Mattel, and the toy industry in general, had spotted a phenomenon called “age compression,” The most recentgcnerations ot children are outgrowing traditional toys sooner. Not so long ago, girls up to age 12 played with Barbies. By 2000, tween girls were a generation weaned on Britney Spears gyrating on M TV in a schoolgirl unifortn and crowned her their own pop icon.

For growing-up-in-a-hurry tastes. Barbie had become a haby toy; Mattel understood that older girls were losing interest in its flagship doll —and that even little girls 6 and 7 years old were influenced hy their hig sisters.

But starting in 2000, Mattel was focusing on a set of business challenges that included a transition at the top. Former Kraft Foods chief executive Robert Eckert arrived as its new chief executive, replacing Jill Barad, who as CEO had pushed Barbie into new venues such as CD-ROMs, dig- ital cameras and even NASCAR with a car-racing Barhie doll.

The company also was wrestling with the Barad-led acquisition of educational software maker The Learning Co., a deal blamed for Mattel’s S431 million loss in 2000.

Figuring out how to regain profitability topped Eckert’s to-do list.

“Mattel was vulnerable,” says Ronald Goodstein, asso- ciate professor of marketing at Georgetown University in Washington D.C, and a consultant for Mattel in the mid-

Robert Eckert Chairman and Chief Executive officer


Matthew Bousquette President Mattel Brands Bousquette is Barbie’s real- life Ken, ultimately responsi- ble for figuring out how to protect her against the Bratz attack, Bousquette has intro- duced a new line of My Scene Barbie American Idol dolls, signed tie-ins with teen star Lindsay Lohan, and cre- ated a new Barbie Live in Fairytopia stage show to regain Barbie’s glitz,

Thomas Debrowski Executive vice President, worldwide operations Debrowski IS responsible for reducing the time it takes to move a new Barbie doll, such as My Scene Lindsay Lohan, from the design stage to Wal- Mart’s shelves, Debrowski was a colleague of Eckert at Kraft Foods, where he worked for 20 years.

Bob Normile Senior Vice President and General counsel Normile is leading Mattel’s efforts to try to crush Bratz maker MGA Entertainment in the courts, in April, Mattel filed a suit against Carter Bryant, a former Mattel designer, argu- ing that he essentially stole the company’s intellectual property while still working at Mattel, Bryant’s lawyer denies that’s the case,


“” ‘̂’nh Fckroth Chief Information Officer New Century Financial Corp. Eckroth, Mattel’s former CIO, was new CEO Eckert’s first hire, joining the company in August 2000 from GE Medical Systems, where he was CIO. Eckroth dumped

Eckert joined Matte! in May 2000 after a 23-year career at Kraft Foods, where he rose to the chief executive’s position. He was charged with trying to rescue the company from a disastrous decision to purchase The Learning Co, in May 1999 for $3,5 bii- lion, and to reinvigorate the all-important Barbie brand. Former executives say Mattel had the com- petitive intelligence to know girls were looking for a doll with more atti- tude than Barbie, but Eckert and Mattel failed to react quickly, Eckert is still struggling to rekindle Barbie’s glow,

many of the company’s cus- tom-built applications in favor of packaged software, such as business intelligence tools from Cognos and Hyperion Software, The underlying goal was to speed the company’s decision-making processes. He left the company in June,

Bruce stein Co-Founder The Hatchery Stein was second-in-com- mand to former Mattel chief executive Jill Barad, until he left the company In a manage- ment shakeup in March 1999. Stein says there was reluc- tance within the company to mess with the Barbie fran- chise, and that may have pre- vented Mattel from creating a Bratz-like product of its own.

Ivy Ross Executive vice President, Product Design and Development Gap Inc. Ross, Mattel’s senior vice president of worldwide girls design until January 2004, is credited with helping Mattel establish an innovative prod- uct development process— an idea lab across from Mattel’s El Segundo, Calif,, headquarters. The lab creat- ed ello, a construction set aimed at the Barbie crowd,

Patricia Lewis Adjunct Professor, Kogod Schooi of Business Amehcan university Lewis has experienced the Mattel marketing machine from both sides—as director of marketing for Barbie in the 1980s, and as head of market- ing for Tyco’s Little Mermaid dolls. She saw early signals that some girls wanted an edgier Barbie, but back then the yearning wasn’t so seri- ous. Barbie continued to rule.

1990s about best practices in product branding. And the best time for a rival to strike with a new product, he adds, is when a company is iooldng inward.

But former COO Stein says that even if Mattel executives

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had focused on the intelligence that Barbie was vulnerable and sounded a red alert, the company’s instinct not to mess with the “hallowed ground” that was the highly profitable Barbie line would have muted the response.

Although Mattel was willing to add accessories and appendages—even a fish tail in 1992 to brush back Tyco’s Little Mermaid—remaking Barbie with heavy makeup and urban-chic outfits would have run up against years of policy not to break the moid. “The culture of protecting Barbie within Mattel is in their basic DNA,” Stein says.

Yet that reluctance to disturb Barbie—even with hard evidence of a market shift—coupled with the internal dis- tractions, left the product line, and by extension Mattel itself, exposed.

In any industry that experiences tectonic shifts, it’s rare to see companies react to the early warning signs, even though they’re generally visible, says Wharton professor Day, who has studied missteps at Mattel, Monsanto and other industry giants. Long-running success makes managers at large companies near-sighted, he says. Focused on a mainstay product, they tend to ignore fresh information that diverges from their accepted norm in three basic areas: marketplace trends, the interests of target consumers, and threats from competitors. For example:

• Monsanto, a leader in plant biotechnology, failed to recognize a shift in marketplace mind-set in the late 1990s. Genetically modified crops like canola and variations of corn and soy- beans were promoted as healthier than natural versions because of built-in benefits such as reduced saturated fat. Farmers liked them tor their biocngincered protection against pests. But when a British scientist said in 1998 that genetically modified potatoes lowered the immune system responses of rats, other medical authorities chimed in with concerns about altered crops —and there soon followed a firestorm of protests and European government edicts against so-called “Frankenfoods.” Investors panicked. Monsanto’s stock price lost 20% through 1999. The then- S9.1 billion Monsanto was pushed into a merger with Pharmacia Corp., largely for the value of its pharmaceutical products.

• Blockbuster, the ubiquitous S6 biliion movie-rentai ctiain, watched as Nctflix, an online movie-rental company, grabbed 2.6 million customers in six years by eliminating late fees and offering convenient service through the mail.

Cornered, Blockbuster in January decided to drop its late fees—worth at least $400 million in revenue. Still, Blockbuster said in financial documents that it had no choice other than “to eliminate the most prevalent cus-

tomer complaints … and combat our com- petitors’ use of this concept.”

• Microsoft, despite having a track record of spot- ting and eliminating up-and-coming competitors, such as WordPerfect and Novell, didn’t see Netscape Communications coming with its Web browser in 1994, It took Microsoft 10 months to release its own browser— and even then, it was built on a product licensed from another company. Microsoft eventually clobbered Netscape, but the upstart’s early, unexpected success forced

~— Microsoft to revamp its core products, incorpo- rating Internet features into every one of them.

The list goes on, but Mattel didn’t have to be on it.

BARBIE LETS DOWN HER GUARD Since its inception in 1945, Mattel has been collecting market intelligence in some form. While systems and procedures have been upgraded, refined and enhanced, the basics have remained the same.

Mattel’s market research department mixes and analyzes data that comes fi”om the company’s own financial and inven- tory systems, plus outside trend and demographic informa- tion from at least five market research firms, including ACNielsen; anecdotal research from focus groups; statistics trom large consumer surveys; studies of children’s play pat- terns; and sales figures from Wal-Mart and other giants.

Mattel also continuously collects aggregate sales at hun- dreds of smaller retailers from market researcher NPD Group, which gathers monthly sales figures on Mattel’s 107 product lines from store owners across the U.S. and Canada.

Mattel seeds its Oracle and IBM DB2 databases with data on units sold, models, prices and dates, and analyzes past and present sales patterns by brand, geography and other categories —all to help forecast the fiiturc.

Analysts at Mattel can run database queries to spot sales trends and conduct profit-and-loss studies by product. Marketing managers like to measure the effectiveness ofTV

commercials by looking at store-level sales data before

and after an ad campaign begins, says Jennifer

Caveza, a former marketing brand manager for Mattel’s Fisher-Price division.

The numbers also arc analyzed in light of observational data from outside researchers and Mattel’s own scientists, including “mall intercept” interviews with girls and anec- dotes about the competition collected from Mattei’s field sales agents, who chat up buyers at the big retail chains.

Employees up and down the Mattel hierarchy are expected to coiiect and discuss inteiligence, using e-mailed updates, text reports filed at private Web sites, and monthly meetings among brand marketers, market researchers, sales managers and product designers.

Even the part-timers Mattel hires in the busy fall season to drive trom store to store to set up merchandise and ensure


that stores are giving Mattel its negotiated shelf space file daily reports to headquarters on what they find, via a secured Weh site. CKO Eckert himself visits toy stores to eyehall inventory levels of competing products.

Meanwhile, senior consumer research analysts with MBA degrees conduct focus groups and interviews with girls, and then speak as the “voice of the consumer” in presentations to senior managers in the consumer research department. Senior associates in the company’s corporate strategic plan- ning group —positions that require not just MBAs but Ivy League MBAs —assess competitors to determine whether to try to beat them or buy them out. These senior associates, according to job descriptions at Mattel’s Web site, also track market shifts in toy categories such as fashion dolls, baby dolls and ride-on vehicles to improve brand sales and profits, and regularly prepare material for Eckert, chief financial officer Kevin Farr and senior vice presidents.

One source of valuable hands-on information is visits by Mattel researchers to children’s homes (with parents’ OK, of course) to observe and understand play patterns.

For example, if researchers see Barbie dolls displayed on a shelf above a girl’s dresser, even if the girls like them, it’s an indication they don’t play with them regularly. They may even be forgotten, says Zwiers, the former Barbie marketing exec- utive, who founded Funosophy, a toy-brand consulting firm in Long Beach, Calif, after leaving Mattel in 1999.

It’s more encouraging to see dolls lying on a pillow on the bed, which indicates they are loved and held. Similarly, dolls seen on the floor next to a box of doll clothes indicates active play Seeing what else is in the room also tells a story Mattel doesn’t want to fmd Barbie on the closet fioor and Sasha and Yasmin Bratz on the pillow,

“Having girls teli you in their own words what they have on their bed and why, and what they have stuffed away in

c/^tMig£iiC£ O u t r^mi lival firms aren’t the only force that can take your company lart.

movements, societal pressures, economic shifts and technotogy breakthroughs can sneak up to derail even a longtime market dominator, according to George Day, a marketing profes- sor at the University of Pennsylvania’s Wharton School,

companies that have ruled their markets for years are espe- cially at risk for overlooking “peripheral” forces that change the familiar landscape, says Day, who co-wrote a forthcoming Haivard Business Review article, “Scanning the Periphery,”

For example, Anheuser-Busch, SABMiller Brewing and Molson Coors initially missed the growing popularity of microbrews. In 1984, beer drinkers sucked up small-batch beers from Samuel Adams in Boston, Pyramid Breweries in Seattle and dozens of others in between. The big brewers didn’t realize that 1980s narcissism was a societal trend that would touch their business: Beer drinkers in the all-about-me decade wanted a beverage as distinctive as they thought they were.

When the number of microbreweries jumped from fewer than 50 in 1980 to 764 by 1996, the mass producers had to respond. They bought stakes in small brewers or acquired them outright, Anheuser-Busch, for example, paid $18 million in 1994 for 25% of Redhook. Independent brewers continue to appear, with an esti- mated 1,400 in business today

Toyota and Honda, on the other hand, skillfully considered how U,S, environmental politics would touch them. The Japanese automakers picked up on consumers’ increasing interest in fuel-efficient hybrid cars, even before the Iraq war. Because they pushed ahead building their Toyota Prius and Honda Insight gas-electric cars, which get 60 miles per gallon, they were ready when car buyers en masse wanted hybrids. General Motors and Ford, meanwhile, continued making gas-gulping sport-utility vehicles, in May, Standard & Poor’s said sinking SUV sales helped convince it to downgrade the bonds of GM and Ford to “junk” status.

As Day explains, “scanning the periphery” for growing threats means actively looking for bad news—such as early backlash

against once-popular SUVs on Web sites such as idontcare- aboutair.com—and then bringing it back to managers who may not want to hear it.

One way to pick up on this intelligence is to designate an executive to “collect the paranoia,” he advises. That person must be senior enough to be able to see the impact of controversial information and appraise it properly At chipmaker Intel Corp,, it was Andy Grove, “It takes a particular kind of curious leadership and processes and systems to be able to make sense of streams of incoming data,” he says. In the 1980s, Grove heard and saw that Japanese chip companies were swarming into memory chips and decided to shift Intel into computer microprocessors, where it eventually ruled the market.

Day also suggests that companies mount scouting parties of two or three people from different departments to focus on one question. An example: “What’s the worst thing that could happen to our new product line this year?” Draw up a list, then go out and look for signs of those things happening. And then, after envisioning the worst, fantasize about the best.

For example, in the 1970s, Day says, scientists at AT&T’s Bell Labs pretended the phone system was wrecked and that they had to build a new one. What wild features and functions would they put into it? Voice mail and voice-activated commands, among many ideas, according to Day, Although the then-industry giant didn’t know how to add them into its phone system imme- diately, those concepts became ideal design points for future projects. Today, we take them for granted.

Another technique: Look at the same data in new ways. Rather than market share, a consumer products company might delve into “wallet share,” Mattel’s Barbie may still be the No, 1 fashion doti in terms of worldwide market share. But wallet share showed that girls are spending increasing amounts of money on music CDs, hip-hugging jeans and karaoke sets—indicating that Barbie’s traditional customers are no longer dreaming about princesses, but about becoming stars on Amehcan Idol. That intelligence could be exploited to develop new products like American Idol Barbie, which Mattel did this year. —K.S,N, AND M,D.


Mattel uses a wide range of business intelligence tools and services to understand and guide the Barbie franchise. APPLICATION Financial management

PRODUCT SUPPLIER Oracle Pinancials Oracle

Financial planning

Human resources


PeopleSoft Human Capital Management


Supply chain and demand management


Manugistics Supply Chain and Demand Management

Ariba Procurement


Transportation management

Business intelligence

Market intelligence

Consumer spending research

Store saies data

Kewtll-Ship Enterprise

Impromptu and PoweiPlay, SPSS 13, SAS Assist and SAS insight

Retail Measurement, AdReievance, HomeScan

ConsumerTracker, Custom Analytics


Kewill Systems

Cognos, SPSS, SAS Institute


Scarborough Research

Information Resources

Product strategy research

Spectracom Research


Corporate strategic planning

Learning Map Root Learning

Databases DB2, Oracle 9i. SQL Server

IBM, Oracle, Microsoft



their toy box and why, can be so much more revealing than asking a lot of canned questions,” she says.

Mattel can record such observations in content analysis software, like Nvivo from QSR International of Australia, which scans for keywords, analyzes their context and weights them for importance. For example, each toy identified in an intet^-iew can become a data point, as can the order in which a girl names her favorites. Analyze enough of those inter- views, and a toy company can see what girls think of its own and its competitors’ products.

Alattel recently has added to its mix business-analysis prod- ucts from Hyperion Software, Business Objects and otbers. Analysts use these products to answer questions about a data set, such as “How many Cali Girl Barbies did we sell in the first nine months of last year, and how does that compare to the sales level we’re ramping so far this year?” ‘ITie products also can be used to produce executive “dashboards” that distill current data on sales, profitability, operating costs and other metrics to produce color-coded reports and alerts for senior managers.

Finally, Mattel casts a wide net to understand the overall marketplace, so it can determine how societal trends, such as i2-year-olds downloading music, might affect Barbie sales. (Say, should Mattel approach Apple Computer about an iPod cross-licensing deal?)

Mattel works with ACNielsen to track TV viewing habits but also consumption of other media. For example, ACNielsen monitors magazine readership statistics and Internet traffic to better understand what girls do when they’re not buying toys. Its NetRatings Internet analysis service functions a bit like its TV ratings service. Families volunteer to have their online activities tracked and recorded. When a member of a Nielsen family sits down at the computer, a screen displays the names of members of the household. If 8-year-oId Ariana clicks on her name, NetRatings, with parental permission, tracks wher- ever she goes online using software installed on the machine.

“We’ll tell them, ‘Here are the most popular shows for 8 year-old girls, here’s where they’re going online, here’s what they’re reading and here’s where you should spend your advertising dollars,'” says Corey Jeffery, a senior analyst at Nielsen/NetRatings.

In response to the popularity of the American Idol TV show and Web site among older girls, Mattel launched American Idol Barbie in January.

The company also uses software tools from Cognos, SAS Institute and SPSS to mix and match internal findings with outside market or economic statistics.

Using Cognos analytic tools, for example, Mattel can track the income level of families that buy traditional Barbie prod- ucts or newer My Scene dolls by triangulating point-of-sale data from different stores, such as Sears or Target or KR Toys, with L.S. Census data on household incomes by ZIP code. It can also determine, say, whether Internet traffic by geo- graphical region is a leading or lagging indicator of sales for Barbie. If click counts at Barbie.com’s American Idol section soar in California in September, but show no similar spikes in Florida, Mattel has a strong indication of where it needs American Idol products on shelves and where to punch up marketing before the holiday shopping season.

Wtth statistics tools from SAS and SPSS, Mattel’s consumer research managers use regression analysis—modeling what-if scenarios by figuring out the relationships among variables such as disposable income, retail locations, weekly sales trends, price fluctuations for the soft plastic of which Barbie is made in Indonesian factories — to get a sense of fiiture trends. One kind of question: “IfWal-Mart will allow My Scene dolls 12 feet more shelf space in half of its 3,000 stores and we run a $3-ofif con- sumer coupon in Nickelodeon magazine, how many points of market share could we steal back from Bratz next quarter?”

The combined intelligence —numerical, observational and aggregated information, from both outside research firms and Mattel itself—helps Mattel’s strategic planning group fill in what Mattel Brands president Matthew Bousquette calls a “pyramid” of products aimed at girls of different ages and tastes. Fairytopia Barbies, for instance, include dolls dressed as fairies with light-up wings for little girls, and $1, bottles of eau de toilette created by perfumer partner Puig Beauty and Fashion Group, for older girls.

To get a feel for the future, Mattel designers create sketches and foam-core prototypes to show to prospective customers of different ages. Researchers then pose a simply

BRATZ ATTACK: BARBIE’S GLOW IS FADING BESIDE HIP NEW COMPETITOR Barbie’s position as the queen of the doll market was thought unassailable, but then young giris 8 to 12 years old started to change. They wanted edgier fashion dolls, and MGA hit the mark with Its Brau line. Mattel was slow to respond, and now Bratz threatens Barbie’s reign.

BASELINE: Overall U.S. toy sales (does not include video games)



BASELINE: Mattel Girls Category (includes Barbie, My Scene, Cabbage Patcb Dolls pllo and Polly Pocket)




worded but critical question, says Patricia Lewis, former director of marketing for Barbie in the mid-1980s and, later, an executive at several competing toy companies.

“We would ask girls. Are you ready for this type of doll?'” she recalls.

The answers reveal what girls view as a step beyond them in maturity—and what they may reach for as they grow, she says. Asking mothers the same thing gives a glimpse of the support or resistance Mattel might encounter with new dolls. “You do need to keep the moms in consideration,” she notes.

MATTEL GIVES IT SYSTEMS A MAKEOVER Gathering and crunching all this data takes processing power. Mattel has acknowledged in conference calls with financial analysts that the hardware and software to support its overall technology strategy needed help in the late 1990s and early 2000s.

Mattel’s former chief information officer Joseph Eckroth, who left in June to become CIO at real-estate investment company New Century Financial Corp., has said that when he arrived in 2000, he found that Mattel’s information sys- tems were a decade old. There were 200 “fragmented” enter- prise systems in manufacturing, inventory management and transportation that didn’t easily share data. About 80% of them were custom built, which was “a limiting factor on our employees’ productivity and operating efficiency,” Eckroth told financial analysts during an April 2002 conference call. Dianne Douglas, formerly head of investor relations, has been named Mattel’s new CIO.

A company that runs dozens of older applications built by in-house programmers can find its technology staff spending most of its time maintaining the software and creating interfaces between any new software and the older applications.

Corporate intelligence amounts to under- standing your customers, sensing the compe- tition’s next moves and knowing yourself. A lack of reliable, timely data from a company’s own accounting, supply chain and other core applications impedes the fiow of information to decision-makers.

Eckroth explained during the analyst call how the inefficient technology had hurt Mattel’s ability to compete: “[By] the time an event has occurred—let’s say a change in demand for a specific product—and the information is made available to the people who need to react to it, it is often too late to take action to effectively minimize a risk or maximize an opportunity.”

Early in 2002, Eckroth and Eckert launched an overhaul of Mattel’s information systems. They wanted to make the technology department more efficient with off-the-shelf applications that needed less “manual intervention” by devel- opers and support staff.

They also wanted to use technology to make the com- pany as a whole more efficient. Focal points included replacing 2,000 old personal computers; upgrading the dis- jointed, customized enterprise software; and installing a data warehouse for better decision-making.

“Every year we are incurring millions of dollars in lost opportunities,” Eckroth said in 2002, “whether it’s … to manage inventories better, reduce our cycle times, improve

our customer service or eliminate non-value-added work, all because our systems infrastructure is not up to date.”

Eckroth steered Mattel toward packaged software. That included buying Hyperion products, including Essbase, for financial and research analysis in early 2002; Mattell also stan- dardized on Oracle financial applications and databases in late 2002, and deployed Computer Associates’ ERWin data-mod- eling tool. In 2003 and 2004, Mattel focused on rolling out Oracle Einancials so its offices worldwide could see and report unified budget and other financial data. Consistent data makes forecasting more accurate, which in turn feeds better data into internal intelligence reports.

But Mattel’s mistake related to Bratz wasn’t so much that it wasn’t getting data; the information was processed and delivered. What mattered was the company’s ineffective response, says Ben Gilad, a competitive intelligence expert and author oiEarly Warning., which outlines corporate intel- ligence problems, including Mattel’s. Mattel, he says in an interview, “completely missed on the early signals and it caused them to lose the edge.”

In the period from 2000 to 2002 when MGA bore down, financial data from Mattel’s accounting systems indicated sales dips for Barbie. Mattel does not give dollar figures for U.S. Barbie sales, but disclosed that domestic sales of the doll line dropped 12% in 2001 and another 2% in 2002. Ultimately, US. Barbie sales would fall 15% in 2003 and 15% last year. In those four years, according to industry estimates, US. Barbie sales dropped $500 million.

At the same time, the company had to deal with the fallout from the $3.5 billion acquisition of The Learning Co.


Even former CEO Barad’s impressive achievement of taking Barbie from a $200 million brand when she started man- aging the doll line in 1982, to Si.8 billion in 1997 —the year she became chief executive—wasn’t enough to salvage her job. She resigned in February 2000 under pressure from the board, ending her i8-year career at Mattel.

After three months with no permanent leader, the com- pany tapped the more conservative Eckert, a newcomer to the toy business, to fix the mess at Mattel. On top of it all. Toys R Us—which, with Wal-Mart, accounted for 40% of Mattel’s sales in 2000—was pulling product orders as it struggled to stay alive.

“Mattel was in a desperate time when I came on,” CIO Eckroth told an audience at an Oracle customer meeting in 2003. “Bob needed to get the company back on track.”

To stop the bleeding from The Learning Co., Eckert signed an unusual deal. He gave The Learning Co. to Gores Technology Group, a turnaround firm in Los Angeles, in


THE OBSTACLE Former Mattel executives agree that the company had competitive intelligence pointing to a desire among 8-to-12-year”Old girls for a bolder, hipper Barbie—but Mattel failed to act. Ultimate responsibility for protecting a company’s crown jewel lies in the hands of the chief executive officer. But information-techtiology managers can take steps to ensure their chief executives get the right competitive intelligence, at tiie right time, with the tools they need to interpret it correctly.

THE RESPONSE Make sure your competitive intelligence system is strong enough to pinpoint potential threats. Good com- petitive inteiiigence systems will help companies become aware of threats that may not even exist yet. That involves having technology to identify and analyze current trends and predict future consumer patterns, such as the desire of every 8-year-old girl to be the next American Idol, Services from companies like Scarborough Research measure the lifestyles, shopping patterns, media behaviors and demo- graphics of consumers to spot such trends at early stages.

Constantly evaluate your system to ensure it’s as strong as it can be. The field of competitive intelligence is changing rapidly, particularly as the Intemet plays an increasing role in consumers’ shopping patterns. Firms like VNU (which includes ACNielsen) can now triangulate store

purchases against television viewing, magazine readership and Internet browsing, and recommend where companies need to focus their advertising dollars. Technology managers need to make sure they’re not missing out on a new Insight that their competitors may be exploiting.

Establish an early warning system. Not only do execu- tives need to knovtf what’s happening In their markets, but they need to know it early enough to act, Ben Gilad, a com- petitive intelligence consultant, says smart organizations set up formal groups v f̂ith representatives throughout their business units and ask them to pore over competitive data and gather field reports. Those bodies report directly to the CEO, There are any number of tools the groups can use to instantly communicate perceived threats—from e-mails, to instant messaging, to intranet and blog postings.

Be ready to justify the cost of upgrades. Today’s com- petitive intelligence systems can be expensive. For instance, ACNielsen gathers data on millions of retail pur- chases, but its customer contracts run an average of about $3.5 million. If a chief executive balks at those types of fees, provide examples of how other companies suffered after they were surprised by an up-and-coming competitor, A company like Netflix might not exist today if Blockbuster Video had done away with late fees several years earlier. And a company like Mattel might not be worrying about a bunch of Bratz, —M,D.

exchange tor “future consideration.” Mattel would get a share of any profits Gores could coax from a revitalized Learning Co,, or part of the proceeds if, as eventually hap- pened. Gores sold it, Mattel got $21.3 million —a sHver of what it paid. But Htkert had freed Mattel from the drag of (rinding a money-losing software firm,

Eckert also forged a financial realignment plan in late 2000, to save $200 million over the period from 2001 through 2003, Mattel closed factories in Kentucky and Mexico along with some international offices, and lopped 2,570 people from its 27,000 workforce.

Amid Mattel’s upheaval, Bratz’ mojo grew, Zwiers, the former Barbie marketing leader, says her

alma mater needed to work harder to figure out where to take Barbie,

“Leadership at the very top of Mattel had changed,” she notes, “There was not the same understanding of the level of ferocity needed to cut someone off immediately and not let them gain a foothold.”

Former Barbie marketing director Lewis says Mattel intelligence had picked up wisps of age compression from internal surveys and external lifestyle studies even when she was there in the mid-i9Sos.

Mattel did bring out dolls wearing flashier clothes, such as its Diva Starz line. But with no competitor yet capitalizing on those concepts —and Barbie’s sales still growing—Mattel didn’t push this new direction.

“Mattel did not have an incentive to turn the fashion- doll aesthetic upside down,” Zwiers says, “Only someone trying to unseat Barbie could do that.”

When Bratz arrived next to Diva Starz on toy-store shelves, the Mattel dolls’ rounded heads and muted makeup looked immature. Diva Starz are still available but have been repositioned for “transitional” girls age 6 to 8, rather than tweens.

In addition to the My Scene dolls, in June 2003 Mattel tried to further dilute the market for trendy dolls, adding an even edgier line called Flavas. But the dolls, meant to evoke the hip-hop music scene, incensed some parents who felt Mattel had turned Barbie into a tart. By early 2004, Eckert killed the product. “Every year we have products that work well and products that don’t and simply said, Elavas was one of those that didn’t work well,” he told financial analysts in a Eebniary 2003 conference call.

Mattel acknowledges that today few segments of its Barbie product line are doing well—mostly those intended for girls under age ?, Other Barbie versions, including those competing against Bratz, “need more work,” Eckert acknowl- edged in an April conference call with financial analysts. He vowed to continue “rebuilding relevance with girls.”

The lesson? A giant that rules its market can’t get com- fortable, says Day ofthe Wharton School. Instead, he says, it should create crisis internally, to teach itself how to respond when trouble does appear.

If Mattel, as part of its intelligence operation, had set up an internal “attack team” to strategize about how it would compete with itself, he says, it would have known to move faster when MGA first launched Bratz. “Ask yourself what have been your blind spots in the past and what’s happening there now,” he says (see sidebar, p. 45). 49

GOTCHA! ANALYZING TEXT MINING TOOLS Human analysts, not computers, bear most of the responsibility for spotting competitive threats, trends and opportuni- ties. Technologists can arm them with “text mining” software that analyzes news stories, patent filings, customer-service notes and the like to find mentions of a company and its products and activities. The tools try to determine whether a company is seen in a negative or positive light, and to spot themes that might provide insight into what customers want the company to do next

PROBLEM: The goal of discovering unexpected patterns through text mining can be elusive.

RESOLUTiotsi Take the time to properly define what you’re looking for. Text mining aims to identify specific entities, such as people or customers, related facts and attributes, and events such as product launches or compa- ny acquisitions. But doing it effectively often requires a substantial investment in defining synonymous terms, such as scientific versus trade names for a given drug, or estab- lishing relationships between products and companies or between parent companies and their subsidiaries or acqui- sitions {the startup that’s suddenly relevant because it’s been bought by your biggest competitor).

The “machine learning” capabilities of text mining soft- ware can accelerate this process by guessing at relation- ships—for example, by using computational linguistics to identify the relationship between a company and an action it has taken, sucfi as acquiring another firm.

PROBLEM: Some forms of text mining, such as “sen- timent mining,” which focuses on identifying positive or negative comments posted online about your company or its products, don’t work equally well.

RESOLUTtON: Know the limits of the tools you choose to use. Sentiment mining vendors such as intelliseek, with its BrandPulse suite and B!ogPulse product, provide a way of continuously monitoring the online buzz about your com- pany and its products. If you’re Apple Computer, it’s likely that a significant slice of your customer base is buzzing

about the latest Mac or iPod product. But what if you’re Mattel? Are there enough young girls keeping blogs for BlogPufse to discover meaningful trends in attitudes toward Barbie?

PROBLEM: The analysis often produces too much information for users to easily digest.

RESOLUTION: Provide analysts with a toolkit that contain both visualization software, such as mapping packages, and spreadsheet-like displays. For example, MicroPatent’s Aureka ThemeScape, an analysis tool for patent data, will display the intersections between, say, a new chemical and its applications as if they were elements in a topographic map. Mountain peaks represent clusters of similar applica- tions; isolated applications appear as islands.

PROBLEM: computer analysis does not equal insight.

RESOLUTION: Don’t just read the data, study it and talk about it. Leaders have a tendency to do what worked for them in the past, ignoring changes that render that strategy obsolete, according to competitive intelligence expert Ben Gilad, author of the book Business Blindspots. “Blind spots are immune to any text mining or visualization tool on the market,” he says. Gilad advises firms that want to avoid this pitfall to establish an early warning system where executives and analysts meet twice a year to discuss what he terms “faint signals” of customer dissatisfaction and competitive threats, -DAVID F. CARR


BARBIE FIGHTS BACK Mattel is fighting back against -fiBratz not only cheek-to-jowl on store shelves, but in court.

Several Mattel veterans now work at MGA and are involved in legal battles. Mattel is suing product designer Carter Bryant, a former Mattel doll designer, for allegedly spilling confidential information and taking Mattel ideas with him to MGA.Also included in the suit are lo unnamed MGA employees accused of helping Bryant breach fiduciary, loyalty and confidentiality duties to Mattel.

Bryant has denied all charges and is countersuing Mattel for allegedly forcing him to sign an overly broad employ- ment agreement when he started work there. Bryant says, for example, that the contract prohibited him from revealing routine information such as the identities of Mattel employees and their skills and knowledge.

In April, MGA sued Mattel, accusing it of acts of unfair competition and intellectual property infringement related to the resemblance between My Scene and Bratz dolls. All cases are pending in US. District Court in Los Angeles.

Meanwhile, Mattel has swamped toy stores with new doll products — Barbies that look like the stars on American Idol and 19 year-old movie actress Lindsay Lohan (J-krh’e: Fully Loaded), as well as Fashion Fever Barbie dolls endorsed by Hilary Duff, who stars In Disney’s popular Lizzie McGuire TV show about

middle school girls. In June, Mattel announced Barbie would hit the road, with an actress touring next year in a live show hased on Barbie’s Fairytopia incarnation, which sells well among girls 3 to 5. The My Scene dolls have many new acces- sories, including a limousine with hot tub. ‘lTiis fall. My Scene Goes HoUywood, a direct-to video animated movie, is due out.

Still, retailers typically give My Scene less shelf space than Bratz. At albys R Us in Calgary, Alberta, for example, My Scene claimed 36 feet to Bratz’ 52 feet. Tbe disparity was greater at a Wai Mart in Peekskill, N.Y., where My Scene got 16 feet to Bratz’ 60 feet. Barbie had more real estate than cither doll line at both locations, but Barbie sales still languish. Retailers measure sales and profits per square and linear foot, and gen- erally give more space to products that generate higher margins.

Mattel’s financial picture is better than when Eckert arrived in 2000, yet five years later he still struggles with Barbie. Last month, Mattel reported that Barbie sales dropped 4% world- wide for the second quarter. “We still have a lot of work to do on Barbie,” he said last month. He noted that he has tried to make Mattel less reliant on any single brand, but that Barbie continues to be “an important, sizable business for us.”

Meanwhile, in its latest annual report, Mattel vows its No. I goal is “invigoration ofthe Barbie brand.”

Yasmin,Jade, Sasha and Cloe don’t look worried. <

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