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Vera Bradley, a fashion accessory and handbag retailer, faces the challenge of accurately predicting consumer interest and optimal pricing for new products. The company constantly introduces new products, making educated guesses on customer interest and pricing. Pricing too low risks losing margin, while pricing too high may result in unsold items. The uncertainty in consumer preferences, especially in the fashion industry, adds to the complexity. The goal is to offer the right product assortment at the right time, price, and place to optimize sales and product performance.

Dick’s Sporting Goods faced the challenge of differentiating its product offerings to attract consumers away from competitors. The retailer aimed to make both its private labels and branded merchandise appealing to shoppers. However, the industry average for new product success rate is below 40%, making it difficult for Dick’s to build a selection that would stand out. This challenge was exacerbated by Amazon’s growing product range and dominance in the sporting goods market, with Amazon launching its own activewear private labels and achieving significant sales growth in sports and outdoor categories.

A brand/retailer was concerned about the impact of tariffs on their margins. They wanted to understand in which retail channels they could increase prices on specific programs/items without receiving price resistance from customers. The challenge was to identify which items could bear the price increase and which could not, in order to optimize their pricing strategy and maintain profitability.

In today’s competitive hiring environment, identifying and attracting the most qualified candidates is challenging even for top tech companies. Facebook has faced difficulties in finding data scientists with the right expertise and skills. Traditional hiring methods, such as resumes and interviews, often fall short in revealing the true capabilities of candidates. To address this, Facebook began running Kaggle competitions in 2012 as part of its data science recruiting strategy. These competitions are designed to attract a diverse pool of data scientists and test their skills in real-world scenarios.

Many companies are cautious about releasing data online due to customer privacy and competitive industry concerns. This is particularly true for industries dealing with sensitive information, such as health insurance. Deloitte Australia faced this challenge when they wanted to offer expanded analytic services to their client, HCF, a health insurance provider. The sensitive nature of health claims data made privacy an ongoing concern, even though the data was anonymized. Deloitte needed a way to leverage advanced data analytics without compromising data privacy or intellectual property (IP).

The universe is filled with 'dark matter'—invisible, heavy matter that distorts light as it travels from distant galaxies. To create an accurate map of the universe, scientists must account for the way dark matter distorts our images of space. NASA, the British Royal Astronomical Society, and the European Space Agency sponsored the Mapping Dark Matter research competition to solve this problem. Participants were given 100,000 galaxy images, blurred to simulate the effects of dark matter. They had three months to create models to find the real shapes of galaxies; their results were scored for accuracy against known measurements.

The Heritage Provider Network (HPN) identified a significant challenge in the U.S. healthcare system: more than 71 million people are hospitalized annually, leading to at least $30 billion in avoidable costs. To address this, HPN launched the Heritage Health Prize, aiming to develop new algorithms that could predict and prevent unnecessary hospitalizations. The competition sought to revolutionize preventative medicine by enabling care providers to intervene before emergencies occur. Participants were given anonymized claims and provider data to predict hospitalizations for the next year. Despite the complexity of anonymizing sensitive patient data, which often results in a tradeoff between data anonymization and predictive accuracy, the competition aimed to push the boundaries of what is possible with existing healthcare data.

Flight dynamics change quickly. From weather to gate conflicts, efficiently adapting to changing flight conditions can save millions of dollars in annual fuel costs, as well as reducing carbon emissions. Flight Quest tackled this real-time big data analysis challenge. In Flight Quest I, participants were given multi-source flight and weather data and asked to predict precise runway and gate arrival times for domestic flights in the United States. The winners produced a 40% accuracy improvement over industry standards—equivalent to saving 5 minutes at the gate per flight (an annual savings of $6.2 million for a mid-sized airline). Flight Quest II was even more challenging: Participants optimized flights in real time. The second phase included significantly more complex weather data—rain, wind, barometric pressure, ice, and more—as well as crew and passenger counts, airport traffic, and no-fly-zones. The winning solution was evaluated in a flight simulator and found to be a 12% efficiency and cost improvement over real flights.

The Merck Molecular Activity Challenge aimed to improve medicine discovery techniques, specifically QSAR models, by leveraging the data science community on Kaggle. Participants were provided with 15 data sets containing chemical structure information for thousands of molecules. The challenge was to predict the activity levels between molecules and targets, ensuring that candidate molecules were active toward intended targets and inactive toward targets that might cause side effects. Each data set had unique characteristics and was measured in different units, creating 15 distinct prediction tasks. The competition saw intense participation with over 2900 entries in just 60 days.

Education experts agree that essay writing is better than multiple choice tests for measuring essential skills like critical thinking, communication, and collaboration. However, because essays are more expensive and time consuming to grade, most standardized tests are still multiple-choice. In Kaggle’s Automated Student Assessment Prize (ASAP), the Hewlett Foundation challenged participants to build data science tools to help teachers and public education departments to grade essays consistently, quickly, and affordably—without sacrificing quality.

Anderson Seafoods' e-commerce offering was met with rave reviews and instant repeat customers, yet it also attracted unwelcome attention from fraudsters targeting the new site with fraudulent orders. Manual order reviews, frequent phone calls to merchant services, and efforts to prevent chargebacks added a minimum of a half hour of back-office work to each transaction. Time-consuming validations, costly chargebacks, and lost product concerns were wasting valuable man-hours and taking the focus off growing the business. As demand for their online store grew and the 2011 holiday season loomed ahead, Anderson Seafoods knew they needed to take a proactive stand in the fight against retail fraud.

Halyard Health, a division of the consumer product Halyard Health Corporation, offers a wide range of innovative clinical solutions. The associate director for Global Strategic Marketing at Halyard Health was responsible for increasing the sales and market share of a pain management medical device to meet revenue goals for the year. The client’s team had been using the traditional approach to target and segment physicians by means of internal sales data and territory insight accumulated by a seasoned sales force. The client decided to explore alternatives that could help the team meet its year-end revenue goals. According to the client, “We needed a reliable data set that would give us physician- and organization-level insight that we were lacking from our traditional targeting and segmenting methods.” The goal was clear: identify physicians who were performing a specific procedure that would benefit from using the Halyard Health medical device. Once identified, the team would then understand which of these physicians provided the greatest potential based on procedure volume. After evaluating several vendors, LexisNexis® was chosen because “LexisNexis® could provide accurate physician- and organization-level information and deliver it in a format that met our needs,” said the client. The client was interested in understanding his particular market and maximizing sales force efforts and results. However, like many in the medical device industry, Halyard Health lacked the technology and resources to objectively identify physicians, quantify the potential opportunity, and determine the best locations for sales calls. They relied on internal sales data and rep knowledge for targeting – which wasn’t complete and lacked a holistic view of the physician. In addition, they had limited sales representative resources in which to cover the entire nation. The client needed to align sales reps with the high-value physicians and their practice locations if he was to meet year-end revenue goals.

The company initially engaged LexisNexis® to uncover new ways in which to grow its business. MarketView is based on billions of data points, matched and integrated from physician-level claims data and the Provider MasterFile™. It brings together multiple and disparate datasets and delivers insight into volume, splitting and referral network activities. This approach enables users to focus on high-value targets and accurately assesses and quantifies opportunities for more strategic targeting. The company faced a significant challenge before deciding to go with LexisNexis®. An executive in the manufacturer’s Global Strategic Marketing department was responsible for reaching a seemingly unattainable goal: increasing sales and market share of a pain-management medical device. After scrutinizing available data and services, the executive believed MarketView could help better segment and target physicians, provide the sales team with insights unavailable from internal data, and reduce reliance on 'tribal knowledge' from current and previous reps.

Consortium needed a master file to match reliably against the Provider Data Repository and third parties, as well as determine market penetration among all practicing providers. Consortium set out to find an outside source to overcome these challenges. They tested data samples and manually validated the information to determine which vendor provided the most complete and accurate view of providers across the U.S.

Insurance industry studies indicate that 10 percent or more of property/casualty insurance claims are fraudulent, according to the National Insurance Crime Bureau (NICB), and fraud is the second most costly white-collar crime in America behind tax evasion. Added up, the NICB notes, insurance fraud costs Americans billions of dollars each year. For nearly a decade, Erie has managed its share of fraudulent claims with the help of the automated LexisNexis® FraudFocus™ platform, which uses predictive modeling and other tools to analyze claims information for patterns of fraud probability. In fact, Erie was a pioneer in implementing LexisNexis FraudFocus, being one of the first users of its unique predictive modeling technology in the insurance claims market. The result was a long-standing relationship in which the two companies have worked closely together as the fraud detection platform has evolved – most recently to include public records.

Special Agent Chris Woehr, assigned to the economic crimes squad, learned about a baby abduction from a local hospital's maternity ward. The police responded quickly, locking down the hospital and establishing a perimeter, but believed the suspect had already left. They had a description of the car, including the age, make, model, and a partial license plate number. The Sanford Police Dept. issued a 'BOLO' alert for the vehicle. Agent Woehr approached Robin Sparkman, an analyst at FDLE, with the vehicle information. She entered the information into the dFACTS system, developed with the LexisNexis® Advanced Investigative Solution platform. Using the Wild Card search feature, she received a list of five vehicles, four of which were in central Florida. One vehicle was registered to a female in the city where the abduction took place. FDLE used an additional source to get a description of the woman and matched it with the suspect in less than 10 minutes. The information was relayed back to the investigators, who matched the driver's license photo of the suspect with surveillance footage from the hospital. A police unit in Lake Mary spotted the car and conducted a traffic stop, finding the infant boy unharmed in the suspect's car.

To meet the rising threat of health care fraud, Lovelace sought a robust solution to maximize its detection abilities.

Target Medical, Inc. faced a significant challenge when it was disqualified from the DMEPOS Competitive Bidding Program due to a clerical error. This disqualification forced the company to drastically reduce its reliance on the Medicare program and seek ways to diversify its business. As a small business with two locations and 35 employees, Target Medical utilized traditional sales methods but lacked the ability to identify key physician targets, quantify potential opportunities, and create a sales strategy achievable by a limited sales force. The company needed a solution to transform its approach from reaching out blindly to focusing on referral sources that actually prescribe the products they sell.

To maintain viability and grow, the health system sought to identify additional outpatient opportunities. To do this, it needed a clear picture of market activity to determine potential and degrees of risk.

Lise Charmel Lingerie, known for its high-quality French embroidery and innovative textiles, faced challenges in controlling costs and fabric consumption. The intricate details of embroidered and lace bands required precise placement to minimize waste. The company sought a way to estimate lace and fabric consumption more accurately and easily to maintain quality while keeping costs reasonable.

La Moda, a major player in Brazil's fashion industry, experienced rapid growth after shifting from childrenswear to women's apparel. By 2012, the company had grown 50 times its original size, producing over a million pieces annually. However, this rapid expansion led to operational inefficiencies, particularly in the cutting room. The company needed to update its processes to keep up with increased demand while maintaining high quality and cost-effectiveness. The challenge was to streamline production, reduce waste, and ensure quick turnaround times to stay competitive in the fast-paced fashion market.

Miti wanted to gain control over hide consumption, reduce operational costs, and ensure the quality of cut pieces by incorporating leather cutting into the in-house production process. Previously, Miti designed and assembled products in-house and subcontracted the leather cutting. However, outsourcing leather cutting resulted in a loss of control over quality and material consumption which, given the high quality of the hides, was very costly. These issues spurred Miti’s management team to consider overhauling its production processes to include leather cutting.

Tachi-S Mexico faced significant challenges in their cutting room, including low efficiency, high fabric consumption, and quality issues. These problems hindered their ability to meet the growing demand from car makers opening plants in Mexico. The company was looking to improve production capacity, reduce operational costs, and minimize quality defects to capitalize on the expected growth. They initially considered acquiring new cutting equipment but were advised by Lectra experts to perform in-depth analyses of their current production processes to identify areas for improvement.

Maggy London faced significant challenges with manual marker placement for their engineered prints. The manual process was slow, tedious, and lacked the precision needed to accurately estimate material consumption and stay within margins. This inefficiency was particularly problematic given the company's production of five seasons of nine lines each year, both for private label and in-house brands. The manual method involved designers scuttling pieces on a table to find the best position for their designs, which was not only time-consuming but also impractical. Despite 40 years of marker-making experience, the uncertainty of the manual process was a significant issue, especially in an industry with an unforgiving margin of error. The need for a more efficient and precise method became critical as the company aimed to grow and meet the demands of private labels and retailers who are very savvy about cost and time to market.

Gruppo Mastrotto’s automotive business unit needed to enhance its manufacturing flexibility to meet evolving customer requirements brought about by rapidly changing consumer expectations. The tannery sought to optimize workflow and processes at its high-intensity automotive manufacturing plants, located on three different continents. The company faced the challenge of handling a high number of engineering changes associated with program changeovers, which required quick and seamless pattern development directly from digital files to eliminate costly retooling that could take several months.

ASTRO Apparel needed to update its design and product development capabilities to maintain its ISO-certified quality standards amidst increasingly complex production requirements. The company, which produces 1.5 million garments annually, including school wear and menswear, distributes its products through over 1000 stores in the US. To manage this complexity and maintain its competitive edge, ASTRO required intelligent technology solutions. The company has been a Lectra customer for 30 years and constantly seeks to improve production efficiency and accelerate time-to-market.

Having built a reputation for the fastest and most reliable lead times in the industry, Quality Furniture constantly seeks to pinpoint areas for additional time and cost savings. In particular, the company wanted to bring more products to market faster—both for designs based on client briefs as well as their own original ideas. Seeing the opportunity to cut time and costs from tasks like manual pattern making, drafting with pen and paper, estimating resource usage, and testing prototypes, Quality Furniture sought to implement a CAD solution. They immediately saw that Lectra could handle all their needs—something no other solution could.

The global challenge for TAL was to hold their dominant place in a competitive market by constantly innovating. This meant increasing pre-production efficiency by harmonizing orders, with the benefit of saving on fabric consumption and maximizing human efficiency.

Mario Levi needed to transform its production processes in order to meet market demands for production flexibility and faster time to market. The productivity levels of their die press system were not sufficient to keep pace with the increase in demand. The die press system required constant monitoring, leading to longer processes and delays in fulfilling orders. The team was looking for a solution to boost productivity, improve material use, and accelerate time to market while being flexible enough to handle growing demand from an expanding market.

ECA, a Belgian automotive supplier, faced the challenge of increasing their yield of leather cut parts while reducing labor. The surge in demand for leather interiors in vehicles made it critical for ECA to meet changing consumer preferences quickly. The traditional die cutting process was labor-intensive and inflexible, requiring different cutting knives for each car model. This process also incurred high OEM tooling costs and long start-up times, making it difficult for ECA to remain competitive in a rapidly evolving supply chain.