How Restaurants Can Navigate Big Data Pitfalls

Big data continues to generate success for companies, highlighting its seemingly endless potential across a variety of industries. However, big data algorithms and analytics are increasingly the subject of trade secret litigation, as companies seek to protect the competitive advantage they have reaped from investing in big data utilization.

The earlier adopters in the restaurant industry have already enjoyed substantial returns on big data investment.

The rapid expansion of big data applications has drawn the attention of regulators, who seek to deploy existing statutory protections in this largely untested territory. Therefore, despite potential advantages, restaurant owners and employers must beware of big data applications that can expose them to discrimination and disparate wage-payment claims.

What is Big Data?

We begin with the fundamental question: what is “big data?” Big data is described as “extensive datasets – primarily in the characteristics of volume, velocity and/or variability – that require a scalable architecture for efficient storage, manipulation, and analysis.” For example, an online retailer may use your online purchase history to help predict what your next purchase will be and provide advertisements for products they predict you will buy. In the employment context, companies might use big data algorithms to find job applicants with a better chance of a positive job performance.

Big Data in the Restaurant Industry

A number of industries utilize big data, and certain industries have made significant inroads to exploit big data to make their companies more efficient and appealing to the individual consumer.

Despite the upsides associated with big data, the restaurant industry is notably falling behind in big data utilization. The Boston Consulting Group’s 2018 digital maturity survey found that of the top restaurant brands, “Four in five brands can access a wealth of data from multiple sources, but only one in five has in place a comprehensive big data strategy…”

Restaurant companies utilizing big data and analytics programs have reaped outsized rewards, including “five to 10 percent increases in revenue, 10 to 15 percent reductions in store-level operating costs, and 10 to 20 percent improvement in EBITDA.”

The Boston Consulting Group also outlines specific examples of big data success stories:

Domino’s built an algorithm to predict how long it will take to make and deliver a pizza, given the number and tenure of the staff in the restaurant, among other factors. This yields an accurate “promise time” to the customer and optimizes in-store labor.
Panera aggregates information about orders on all digital channels (apps, site, third-party) to help plan for in-store labor and product needs. It now receives 250,000 digital orders a day and has changed its store operating model to handle the volume…
Starbucks uses GeoAnalytics and analysis of past store openings to optimize its process of location selection for new stores.

The earlier adopters in the restaurant industry have already enjoyed substantial returns on big data investment. However, these returns do not come without risk – haphazard use of big data can lead to legal headaches.

Equal Pay Risks Presented by Big Data

Pay disparities can lead to claims under the Federal Equal Pay Act of 1963, which requires men and women receive equal pay for equal work, as well as discrimination claims under Title VII of the Civil Rights Act of 1964, which prevents employment discrimination on the basis of race, color, religion, sex or national origin. States have also enacted equal pay statutes with even tougher standards and penalties than similar federal laws.

However, these returns do not come without risk – haphazard use of big data can lead to legal headaches.

The Equal Employment Opportunity Commission (EEOC), the federal agency which administers and enforces civil rights laws against workplace discrimination, has signaled its intent to more closely scrutinize disparate wage data.

This means that employers with more than 100 employees are required to submit information concerning employee wage and hour data organized by job category, gender, race and ethnicity for calendar years 2017 and 2018.

The purpose of the EEOC’s data collection is to ensure employees are receiving equal pay for equal work. By having access to companies’ employee wage and hour data, the EEOC is in a better position to assess pay discrimination allegations. Naturally, the submission of this material to the EEOC could subject companies to scrutiny, particularly if wage and hour data evidences pay disparities among employees in different protected classes.

Proactive companies can help protect themselves from wage discrimination claims by applying big data analytics on this material internally to self-audit pay practices. By compiling employee wage and pay data, companies can recognize disparate wage red flags. Identifying potential wage disparities gives a company the opportunity to factor in neutral, job-related employee performance metrics, like job grades, service time and employees’ talent scores for past performance and future potential. Proper use of big data programs can analyze all of the above-mentioned factors to help companies explain the legitimate, job-related, rationale driving seemingly disparate wages.

Big Data Recruiting Risks

Using big data applications to assist in talent recruitment can also pose risks for companies. While algorithms can help employers target their recruiting efforts to find the ideal candidate for a specific position, if an employer is not careful, they could find themselves facing employment discrimination claims.

The American Civil Liberties Union’s (ACLU) filed a complaint against Facebook in September 2018 with the EEOC. The complaint, which alleged that Facebook implemented discriminatory employment advertising practices, provides a cautionary tale.

The EEOC’s Complaint Against Facebook

The ACLU’s complaint alleged that Facebook’s employment advertising algorithm unlawfully discriminated because of age and gender in violation of Title VII of the Civil Rights Act. Specifically, the complaint alleged that Facebook’s big data use purposely excluded women and older workers from receiving certain employment advertisements for employment in male-dominated fields. This targeted advertising purportedly excluded potential applicants in violation of Title VII. In March 2019, Facebook settled these claims for approximately $5 million.

In addition to the monetary settlement, Facebook also agreed to overhaul its targeted advertising system to withhold detailed demographic information, including gender, age and zip codes, from certain advertisers. These changes make it harder for advertisers to micro-target specific demographics, which, in turn, help prevent discriminatory advertising practices.

Understanding Facebook’s Alleged Misconduct

Although settlement means a court will not decide the merit of the claims, understanding Facebook’s alleged misconduct is no less important for restaurants looking to employ big data.

Until recently, Facebook maintained flexibility to offer companies expansive advertising options to micro-target specific demographics. Indeed, Facebook’s flexibility is the center of the controversy surrounding its advertising practices. By allowing employers to choose who sees their advertisements, Facebook’s advertising algorithms allegedly ran afoul of Title VII.

While Facebook denied the complaint’s allegations, restaurant owners looking to utilize big data algorithms should pay attention to the settlement terms.

Implications for Restaurants Using Big Data

Big data is here to stay, with almost unlimited potential for talent management, recruiting and operational assistance. Restaurants that fail to harness the power of big data may find themselves hopelessly behind their competitors.

Restaurants that fail to harness the power of big data may find themselves hopelessly behind their competitors.

The suggestions below provide a roadmap for restaurants on how to use big data as a shield before the EEOC, state regulators and plaintiffs using it as a sword in the next high-profile big data lawsuit.

Whether a restaurant has seamlessly implemented big data into their marketing and hiring strategies, or a company seeks to begin utilizing big data, the Facebook suit provides a clear warning: commercial big data practices create vulnerabilities for inadequately prepared companies.

A restaurant’s adoption of procedures designed to limit the disparate impact of consumer targeted advertisements will protect against lawsuits. This means not only adopting preventative measures to ensure compliance with federal and state anti-discrimination laws when launching certain marketing and employment practices, but also remaining diligent to ensure facially non-discriminatory conduct does not have a discriminatory impact.
Enacting express procedures for marketing and employment practices that use big data will help restaurants maintain a transparent company-wide policy that limits exposure to lawsuits and provides a neutral explanation for seemingly disparate findings in wage and employment data.

In conclusion, the competitive advantages other restaurants have derived from big data utilization should encourage and inspire similar big data usage. In doing so, proactive restaurants can use big data analytics and algorithms for greater profits while simultaneously protecting themselves from discrimination and disparate wage claims.