September/October 2016

Diallo Telli Brown is an administrator of an alternative private day school and urban education advocate, author, and speaker.

I don’t watch many movies. I tend to think of movies as frivolous, a 100-plus minute escape from reality, conditioning some minds to expect odd and improbable outcomes to future challenges. But I recently watched Bennett Miller’s and Brad Pitt’s 2011 film, Moneyball, based on the nonfiction book Moneyball: The Art of Winning an Unfair Game by Michael Lewis.

Moneyball is a noteworthy take on the effects of analytics in Major League Baseball (MLB). The film introduces an ex-MLB player turned general manager named William Bean and features a depiction of Paul DePodesta, then a recent economics graduate of Harvard University. Together this pair used data-crunching analytics to repair the decimated roster of the Oakland Athletics — after three superstars’ contracts expired — and solve the ballclub’s small-market finance problems.

After digesting the movie and pouring over research on analytics, I am convinced that, if the matter is approached systematically and specific to the setting, school boards and their districts can duplicate the process of success that analytics brings to many different industries.

Analytics in a peanut shell

According to Tom Davenport of the Harvard Business Review, these five essentials are the very basics of analytics:

  • Identifying and Framing the Analytical Problem
  • Working with Quantitative People
  • Understanding Different Types of Data and Their Implications
  • Understanding Different Types of Analytics and Their Implications
  • Exploring Internal and External Uses of Analytics

While I won’t delve into all five, two stand out: “Identifying and Framing the Analytical Problem” and “Exploring Internal and External Uses of Analytics.” Respectively these two essentials are the starting pitcher and middle reliever, and they relate to how school boards can manage their relationships with school buildings.

Analytics begins with an identified and particular problem. For the sake of educational discussion, let’s use truancy as the identified agitator. The truancy problem is shared across several departments, has internal and external factors, and is not contained to a single school building. The district is made aware of the problem and those at the both the building and district level begin to determine what type of data is available to them internally, as well as what other sources may avail themselves before the end of the ninth inning. The internal data set or the “small data” that district has at its fingertips (for example through PowerSchool, Infinite Campus, Blackboard, or Skyward) has useful analytical tools that contribute to seeing the problem of truancy and aiming to diminish it.

But what about “big data” — data sets outside a school’s server? Perhaps there are conditions in a particular neighborhood that prevent a student from attending school routinely. Maybe there is a medical outbreak running unchecked but unreported in a certain community or area of town? Perhaps there is a lack of childcare, affecting the district’s PreK and kindergarten programs. Maybe the increasing talk of a charter school lottery or school voucher program is creating reservations in parents’ minds about consistent school attendance.

Regardless of the contributing factors, these data sets may not be located on the district’s server but are correlating factors in considering, and winning, the issue of truancy. Analytics uses both big and small data sets to identify the problem and provide solutions in order to further the academic success of the district.

Who’s on first?

Oakland ’s general manager duo of Bean and DePodesta eventually proved their system worked by winning the American League West title with one more win than the previous season, minus the three superstars the organization could no longer afford to pay. In this analogy, if the school board is the general manager, then the administrators are the coaches, and members of the district’s information technology staff are the players. All are involved in making schools better via analytics.

No one player is of superstar significance. Instead, there is a meticulous way of managing the district in order to gain consecutive wins towards the identified problems in need of solutions. Usually, the district office is responsible for pulling data reports at building-level or district-level requests. Instead of reacting, IT staff should become proactive in running daily and weekly data sets against the norms of the district, state, and other districts they want to emulate.

A problem lies in IT staff knowing their data too well, and as such not articulating what it means in mutually beneficial ways. This leaves the administrators to decipher more by instinct than by analytics. In baseball, there is a situation called a “pickle.” It occurs when a runner is between two bases and needs to safely return to one base (that is not occupied by a teammate) before being tagged by an opposing player with the ball. This accurately describes an administrator when data is requested, but either not accurately articulated or the implications are not completely understood. More consideration of how data can be used both intellectually as well as instinctively is the   process of analytics, which lead the Oakland As to a 20-game winning streak, a modern-era Major League Baseball record.

Building the fan base

It’s been said that a school should not be run like a business. I agree. However, a school district should be run like a business, if you consider its customer to be the school building. In turn, the school needs to put out a great product — well-educated students who will become productive citizens. These students are viewed as Ws — they are wins to the community and families they serve. When the school regularly produces student growth and success, fans are created from near and far. When fans or stakeholders are pleased with the product, and as a result, support is established in the community, a better financial picture for the district is foreseeable.

To explain, I need to change-up the analogy. Now, school boards are the team owners with administration being the GMs. Operational efficiency in education has to evolve into the school board’s understanding of the school building as a customer instead of an internal partner. Purposes of a school board include safeguarding finances and providing equity in learning for the district’s customer (the school building) and the customer’s customer (the students).

By providing safe and secure opportunities to infuse analytics and providing an intermediary who can interpret the data in a common language so that it can be used to manage problems within the school building, boards can focus more on prevalent issues.

One such prevalent issue would be a referendum. Wishful thinking suggests that, someday, selling a referendum will be a non-issue, because the district has used big data and small data analytics to solve its issues, in turn producing students Ws, which develops demand from families relocating into the district, which results in more tax dollars and state funding.

The closer

The 2002 Oakland As season resulted in more than a 20-game winning streak and AL West championship. It also opened the evaluating eyes of industries across the world to how analytics can be an asset to just about any situation. Analytics promotes a deeper understanding of how problems can be solved implementing the use of big and small data sets. The question becomes, why have school districts not completely embraced that notion? In baseball, there is a player called a closing pitcher – the closer. His job is to enter the game in the late innings, and shut down the opposing team’s hitters. His priority is to not allow the runs that would cause his team to be tied or to lose. His analytics are to recognize the problem (getting the last remaining batters out). His data set is the type of pitch he is capable of commanding versus the type of pitch the batter is expecting.

Remember the truancy problem? By the use of analytics, we can acquire a realistic assessment of the problem. We can determine how many students from past years who have like addresses have experienced truancy issues. We can develop correlations between discipline and social/emotional issues associated with truancy. We can gather data on parent involvement, or lack of.

From there, this problem, or any problem becomes a quest for regularization, which can lead to closing the distance between intellect and instinct; both of which are needed to improve how school boards manage school issues for consistent Ws.