By Patrick White 2014-10-03 06:18:12
Take off your blinders, pull your head out of the sand and overcome fears set years ago in algebra class. You simply can’t manage what you don’t measure. “The Sexiest Job of the 21st Century.” That’s how a recent Harvard Business Review article described the relatively new profession of “data scientist.” In the past, these bar graph-obsessed numbercrunchers were more likely to be called “nerds.” Now, data scientists are the cool kids, and they’re driving just about every key decision made at Fortune-500 companies, social media startups, political campaigns and professional sports teams. Heck, even movie star Brad Pitt successfully pursued the role of baseball data analytics guru Billy Beane and went on to earn an Oscar® nomination for his “Moneyball” performance. What explains the zero-to-hero transformation? Businesses large and small have realized how important data is to attracting and keeping customers, making key marketing and management decisions and, ultimately, to realizing a successful bottom line. Data, by definition, refers to “facts or information used usually to calculate, analyze or plan something.” That doesn’t sound sexy, but consider that the ongoing success of such corporate superstars as Google, Facebook and Amazon depends on the principle of mining and extracting customer data to discover what people are searching for, thinking about and buying. Ponder the fact that every commercial you see on television has been carefully scripted according to data about the income, family demographics, hobbies and desires of the most-likely viewers during that time and on that channel. It’s no wonder that spreadsheets and pie charts have become a lot more relevant and their study has become that much more vibrant and attractive. The average school nutrition operation might not have a team of data scientists on staff the way Silicon Valley tech firms and corporate retail giants do, but that doesn’t mean data isn’t available—and essential. “Data drives pretty much every decision we make,” says Kathleen Glindmeier, SNS, director of nutrition and wellness with Paradise Valley Unified School District in Phoenix. “We do all kinds of data collection: meal counts, labor hours, inventories and so on. All of that has to be quantitated, and then based on that, we make decisions.” Glindmeier says that when she analyzes data, she’s simply keeping an eye out to identify trends that may have a long-term impact. For example, last year the district’s food costs rose 5.8%. Further investigation revealed that while some of the increase was attributed to a general surge in all food costs, a percentage could be tracked specifically to the new regulations regarding increased produce portions. “For most districts, food costs are at least 40% of your overall costs, so this is an important area to study,” she notes. “For example, if the cost of beef goes up nationally, we may have to make a decision that we can’t afford to serve beef as often, or that we have to raise our lunch price, or that we have to look for other ways to tweak the menus to bring down food costs.” Without tracking and analyzing this data and looking for such trends, it’s impossible to understand why certain things are happening and determine how to respond, Glindmeier emphasizes. The business world has adopted a catch phrase that neatly sums up the value of this effort: “You can’t manage what you don’t measure.” Data, Where Art Thou? If you don’t have a team of sexy data scientists to generate reams of facts and figures for you, where does it come from? “We all have computer systems. So we all have data that’s available to us at our fingertips,” asserts Beverly Girard, PhD, RD, SNS, director of food and nutrition services, Sarasota County (Fla.) Schools. For example, Sarasota’s school nutrition operation, like many others across the country, uses a productivity standard called meals-per-labor-hour to set staffing levels throughout the district and at individual sites. “We don’t staff our schools or make hiring decisions until we look at our productivity standard,” says Girard, who regards this as probably the most consistently applied type of data in the school nutrition business. “If I have a manager tell me that they need an additional employee, I say, ‘Please show me either the [increased] meals you have already earned or [that] you anticipate you will earn. When you meet that number, then I’ll add a staff member. But until you meet that number, I can’t add a staff member.’” This particular example demonstrates the important difference between just randomly reviewing raw numbers and actually analyzing data, she notes. For instance, if one school has a high total payroll, it might not be an indication of an over-staffing problem, but rather that the employees at that site are more experienced or longer-tenured and thus are earning a higher wage. Using a meals-perlabor- hour formula levels the playing field to compare one school to another on a productivity basis. The value of examining this data isn’t just that it prevents over-staffing, adds Girard. If a school isn’t meeting the productivity standard, it could indicate that additional training is required or that another problem exists that should be investigated. For example, lower productivity at one school might reveal that outdated equipment needs to be replaced or inefficient production systems are being used that should be revised. Data doesn’t always contain the answer, but sometimes it tells you what questions to ask. Area Manager Javier Vasquez oversees meal applications and IT for Orange County (Fla.) Public Schools’ Food and Nutrition Services administration. He agrees that data plays a huge role in how their school meals program is operated. For example, “feeder pattern” data has helped to identify schools that don’t have the expected percentage of free/reducedpriced applications on file that is indicated by other demographic data. In part, that discovery has been made by tracking student populations as they move from, say, the elementary to the high school level. “We know that high school is the age when many [kids and families] don’t fill out or submit applications; we found that, in most cases, the high schools were 10 to 20% below where they should be,” Vasquez explains. That information has helped direct where efforts are needed to try and boost meal application submissions. Tracking trend data also has made the actual processing of applications more efficient throughout the district. For example, it helped staff to recognize that lists from the state of “direct certified” (pre-approved) students didn’t always include the names of siblings who also were eligible for free or reduced-priced meals. By adding data fields such as guardian name, address and telephone number, Vassquez was able to use the department’s database to identify children living in the same household who also should be considered direct-certified. In a district of 180,000 students, this effort yielded 4,000 additional names and greatly reduced the amount of staff time required to send, follow up on and process those applications—not to mention eliminating the need for many parents to complete the paperwork. It also offered the potential for greater reimbursements to the operation’s bottom line—and, of course, more meals to more students without the means to pay for them. Thanks to other data gleaned from the district, state and even the U.S. Census, Vasquez and his colleagues have taken this applications project a step further. Now, addresses for students in schools that haven’t reached their expected free/reduced-price eligibility level can be plugged into a Google Maps application to identify areas where pockets of higherincome students might be surrounded by lower-income students in the same community. This can identify families who could be contacted individually to ascertain why they haven’t completed an application, provide assistance and catch applications that may have been declined because of easy-to-correct errors. “We now have the ability to really dive deeply into the data,” notes Vasquez. It’s the same data-driven approach that might be used by a car dealer to target customers. Vasquez admits that being an IT expert gives him an advantage when it comes to accessing and understanding data that is compiled electronically. “Sometimes it may take some tech expertise to really do that,” he acknowledges. In a smaller district that doesn’t have dedicated IT professionals within the school nutrition department, it may be possible to reach out to staff in other district departments for assistance. You may be surprised by how many data-savvy colleagues are available to be resources to you; it’s just a matter of explaining the school nutrition intricacies of the situation to them, Vasquez advises. “Try to get them involved and engaged in what you’re doing,” he urges. He came to his position as a dedicated IT professional, but reports that once he started to fully understand the school nutrition operation, he was able to provide helpful assistance. Having hard data and a willingness to apply it are only the first steps in making data-driven decisions. You need steps and a timeline to conduct that analysis and then apply the results—and then to assess the effectiveness of the data-driven action. “You need the structure to help you make good decisions, and you always need the assessment piece afterward,” notes Girard. One common way of using data to set goals and evaluate performance is through the use of key performance indicators (KPIs). When working on a specific initiative, a KPI would set a quantitative bar at the very start in order to measure success or failure at the end. Driven By Data Are you intrigued to start diving deeper into your data? As you look around your office, you realize there’s probably a ton of valuable information contained in two years’ worth of binder-clipped financial statements and a file box full of average daily participation meal counts at each serving site, but it’s a pretty daunting task to try to sort it all out. Unless you put that data into an easy-to-understand, quickly accessible format, the value is likely to remain lost under a thick layer of dust. One way that data can be made relevant on a daily basis is through the use of a data dashboard. “We started using a dashboard [approach] four years ago,” explains Sandra Ford, SNS, director of food and nutrition services for Manatee County (Fla.) Schools and an SNA past president. This visual compilation of data is “sort of like the dashboard on your car, where you have a bunch of gauges to help you drive. [It’s] a series of graphs and numbers and information in front of us that helps us operate the program.” A data dashboard can be built using any criteria that will provide a useful snapshot of your school nutrition operation. Each month, Ford collects and records data details related to average daily revenue, per-meal costs for both labor and food, breakfast and lunch participation rates, reimbursements, revenue from the online payment system, meal applications and any other figures that she wants to track for comparison with prior months and years. Most of these numbers are important for making financial and management decisions; some, such as the number of applications processed, double as “feel-good” data, notes Ford, explaining, “It lets the staff see how much they’ve done and feel good about how hard they’ve worked.” Each year, she updates the criteria that she wants to display on her dashboard based on the departmental goals that she’s set with her supervisor and with her own management team. Once the categories are set, they remain in place for the whole year. According to Ford, there may be software that facilitates the construction of a data dashboard, but she simply uses a Microsoft Word document. The content is more important than the technology involved, she emphasizes. Ford shares her data dashboard every month with her managers, as well as with other senior district-level staff, as a way to showcase her team’s accomplishments. She even posts it on the department’s website. “It’s something you can use not only for comparing and looking for problem areas, but it’s also a tool for marketing what you do,” Ford advises. In addition to the department-wide dashboard, Ford’s team also maintains data dashboards for each individual school in the district. This provides comparative data that she and her supervisors can use to help site managers solve problems and set goals for achievement. Not only can they review the performance trends from month to month or year to year at their own site, but they can measure against other sites with similar enrollments or operations, such as all middle schools. Indeed, the dashboard approach has been a great teaching tool, Ford avers. “By putting food cost data on there, for example, and showing food cost fluctuations from month to month, it has allowed us to engage managers in a conversation: ‘What do you think happened this month? Why is the number different than last month? Was it last month’s number that was off, or is it this month’s?’” It’s creating a less-threatening environment; simply having a conversation over the numbers together, she asserts. It also provides an opportunity for managers to see the bigger picture, beyond the day-to-day challenges of getting the meals to the students. Ford agrees that the real value of data isn’t looking for one number that answers all questions, but rather in following patterns over time. For example, the school-level dashboards track employee overtime costs. A spike might be explained by a special event or some other specific situation, but a trend is more telling, indicating to Ford that she should investigate further. The visual display of such patterns offers the same function as a warning light on a car dashboard. Initially, Manatee’s school nutrition team used its dashboard simply as a tracking tool. Now, goal setting and achievement measurements will be tied to the data. For example, a site will be required to fall within a certain range of the district average in order to be considered a success. “We hope, down the road, to tie it to [employee] performance evaluations,” reports Ford. She encourages any school or district inspired to look into applying the dashboard approach to start small, with just a few data areas to monitor and compare, and then expand both the categories and the application of the results over time. Persuasive Power Having good data is perhaps the most powerful evidence when making a case for change—for a higher budget, bigger staff, new initiative and so on. For example, during the first few days of this school year, Sarasota County’s Beverly Girard didn’t have to worry about convincing a skeptical IT staff when a computer snafu was suspected in hampering student registration for meals. “If I had just said, ‘This is what my managers are saying,’ that would be one thing,” she recounts. “But instead I was able to pull up data showing registration numbers from the first days of the 2013 school year. I was able to show that we were serving more students from our production records, but there were nearly 2,000 fewer students registered.” When you’re able to quickly access and use that kind of data, everyone starts paying attention. “They 100% take your position more seriously—then, it’s not just somebody whining,” notes Girard. “Data helps you maintain credibility and even look like an expert.” Similarly, at the end of last school year in Paradise Valley, Kathleen Glindmeier took advantage of the internship program she offers to collect data and analyze the district’s breakfast-in-the-classroom (BIC) program. In addition to prompting protocol changes for the school nutrition operation, the data was presented to each of the principals involved, so they could see, for example, how individual classrooms were performing with BIC, and how their school compared with others in the district in regard to food waste and other criteria. This also helped to spotlight classrooms where more training was needed. “Principals want to do the right thing, and when they saw this data in front of them, they wanted to make it better,” says Glindmeier. “I could have just told them in a meeting that something was a problem, but when they could see the data in front of them, and they’re looking at how they rank compared with other schools offering the [alternate breakfast service] program, they could really see where they needed to improve.” Using a data-driven approach certainly can help new directors and managers, as well as those trying to turn around a problematic operation or fend off uninformed critics. But it’s a tactic that works for even the most seasoned operator. After nearly 30 years in child nutrition, Beverly Girard admits that there can be a temptation to simply make decisions based on experience and a good gut feeling. “However,” she emphasizes, “when I combine my intuition and experience with hard data, I’ve found that I always make better decisions.” Patrick White is a freelance writer in Middlesex, Vt., and a former assistant editor of this magazine. Illustrations by iunewind/istockphoto.com. SNAPSHOT • Whether you are a district director or a cafeteria manager, data should drive virtually every decision you make for your operation. • A willingness to apply data is only a first step; you also need a system to assess the actions that result. • Compile data in one place, creating a “dashboard” to provide a visual representation as you track different measurement categories. BONUS WEB CONTENT To use data to its greatest potential in school nutrition programs, you need to preach its virtues to your entire team. Check this month’s exclusive online bonus content for expert reflections on how to do this, plus some simple data collection strategies and a list of resources that can help you dig out even more data to guide you in taking your operation to the next level. Visit www.schoolnutrition.org/snmagazinebonuscontent.
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