THE MISSISSIPPI LEGISLATURE

The Joint Committee on

Performance Evaluation and Expenditure Review

Report # 589

Improving the Efficiency of Mississippi’s School Districts: Phase Two

Executive Summary

Introduction

In this review, PEER conducted a comprehensive efficiency review of selected school districts in Mississippi.1  PEER sought to identify best practices exhibited by districts with both low support expenditures and high academic performance in order to determine what actions or efforts these districts have implemented that could be implemented by other districts with reasonable expectation of similar results.

PEER established a sample of fourteen districts2  based on a methodology that utilized relative measures of efficiency and academic performance3  applicable only to the purposes of this review. For a detailed description of the methodology utilized to select the districts, see Appendix A on page 85 of the report.

PEER’s Theory in Phase Two of Improving Efficiency in Mississippi School Districts

School districts should apply a disciplined approach of identifying their needs so that cost savings can be effectively redirected into an area that will improve the district’s efficiency and academic performance. Also, the Legislature’s current effort to revitalize performance budgeting requires increased accountability for the efficient and effective use of public resources, including the expenditure of tax dollars by the state’s public school districts.

PEER sought to identify efficiency drivers and metrics utilized by the selected districts with the purpose of compiling a list of best practices that could be shared with other districts to yield efficiency improvements. PEER had proposed that by selecting districts that exhibited low support expenditures and high academic performance, as well as those districts that exhibited high support expenditures and low academic performance, distinct practices and procedures could be identified in order to establish drivers and metrics deemed as more efficient.

By using an interview protocol based on school district efficiency review processes in other states, PEER targeted nine functional areas in the fourteen selected districts: district leadership and organization, financial management, human resources, purchasing and warehousing, educational service delivery, transportation, facilities, food service, and information technology. Three major themes were exhibited within the selected school districts.

• Regardless of whether the district was more efficient or less efficient (as defined by PEER in this report), no distinct efficiency drivers were identified that could be implemented as best practices.
• Within each functional area, multiple instances of decisions had been made with a focus on academic performance without consideration of efficiency.
• While efficiency decisions and procedures were mentioned at various levels, often these efficiency decisions were made by district leadership in a manner that was not accountable, based on available data and transparency of the decisionmaking process.

Because PEER could not identify specific efficiency drivers within the selected school districts as initially theorized, PEER proposes that all districts work toward a disciplined approach that is both efficient and accountable through a data-driven decisionmaking process.

A Data-Driven Decisionmaking Model for School Districts

Data-driven decisionmaking is a dynamic, disciplined process of utilizing data to make well-informed decisions on how to target resources in meeting needs and educational goals. The Data Driven Decision Making (DDDM) model is derived from the Total Quality Management (TQM)4  model, which states that organizational improvement can be achieved through directed review and analysis of data to set and benchmark goals (i. e., to set measurable objectives by which progress toward goals can be measured). A DDDM model for school districts would seek to establish a process wherein data is used to formulate education policy and to measure the effectiveness of those policies with the end goal of targeting resources to those educational goals, objectives, and programs that show the most impact and return on investment.5

In order to utilize the DDDM model successfully, districts should gather data, convert this data into information through analysis, produce actionable knowledge by coupling this information with statewide and district priorities for public education, and arrive at district goals, objectives, and program decisions based on the information provided by the preceding steps. To construct, administer, and maintain an effective DDDM system successfully, districts must collect, report, and utilize reliable data and operate in a school culture that is receptive to such. Further, districts should be aware and take steps not to overwhelm themselves with data and know that the use of this data will be for the betterment of the district and not for alternative purposes.

Observations Within the Selected School Districts

While PEER could not identify specific best practices based on observations within the fourteen selected districts, PEER did note efficiency elements that could be incorporated into a data-driven decisionmaking process, as well as deficiency areas in need of a disciplined approach to making decisions.

• District leadership and financial management--District leadership and organization affect the operation of all functions. Efficiency decisions are a reflection of a district’s leadership and financial management. As noted previously, these decisions should be based on data, should be documented (for future reference or for third-party review), should be critical parts of the district’s planning process, and should be made in a disciplined manner in order to achieve the desired balance of efficiency and quality as determined by the district’s needs.
• Human resources--The selected districts rarely had a disciplined approach for data collection and formal application of data related to human resources issues. For example, PEER could not find evidence that service contracts were the most efficient or economical decision when utilized by the selected districts.
• Purchasing and warehousing--The selected districts often reported that they sought the best price when purchasing goods (e. g., by state purchase list or by competitive bid against the state purchase list as a benchmark). However, PEER observed that some critical information relating to district purchases and inventories is not being utilized to its fullest extent. For example, some districts collect and report equipment items in their inventory, but they do not utilize this inventory to forecast potential future needs or expenditures.
• Educational service delivery--Of the fourteen districts sampled, those districts rated as A or B6  spent an average of $6,672 per student for educational service delivery, while the districts rated as C, D, or F spent an average of $9,539 per student for educational service delivery.
• Facilities--All of the selected districts collect and track data regarding facilities to some degree (e. g., square footage, age of buildings, custodial staffing). However, it was not readily apparent for most of the selected districts how this data was utilized.
• Transportation--All of the selected districts maintained some form of fleet inventory, but most of the decisions regarding bus maintenance and replacement appeared to be driven by the availability of funding from year to year rather than by a formal schedule. Also, while the selected districts often reported that they sought the best price when purchasing fuel (e. g., through Fuelman or by competitive bid), districts had no comparative data that could distinguish the more efficient method. Finally, while multiple districts reported that they had access to a routing and scheduling software program, this program did not interface with the districts’ student information database.
• Food service--Food service is the only functional area in school districts with a separate source of revenue. It should be financially independent from the district by reducing costs associated with personnel, inventory, and equipment and facilities.
• Information technology--The selected districts collected a large amount of data regarding information technology costs or needs, but often this data was not compiled and analyzed in a way that would take into account the true cost of ownership for information technology equipment, was not developed into formal equipment replacement schedules, nor did the data enable the district’s leadership to establish an accurate picture of the information technology needs within the district.

Opportunities for Data-Driven Decisionmaking

PEER proposes that districts move to a disciplined approach of a data-driven decisionmaking process implemented through outsourcing, shared services, strategic human resources management, and strategic facilities and equipment management.

• Outsourcing--By utilizing performance-based contracting and make-versus-buy analysis techniques, districts could improve the efficiency of their outsourced contracts and increase the return on investment of such contracts.
• Shared services--Shared service arrangements could allow districts to pool both resources and expertise regarding a particular issue in order to maximize purchasing power and available resources to be mobilized in combating the issue.
• Strategic human resource management--School districts’ human resources personnel should keep vigil not only on developments affecting the future of the district, but also should monitor and reexamine the work done and the need for all district personnel.
• Strategic facility and equipment management--Districts should develop a comprehensive strategy to maintain and update/replace district infrastructure such as buildings, buses, and computers.

Also, the Mississippi Department of Education (MDE) should work with the districts and with legislative staff to identify the performance metrics that should be collected and reported for each administrative and support program in the districts’ program inventories. Administrative and support programs and measures should be uniform from district to district, which would facilitate unit cost comparisons. Once these programs and associated performance metrics have been identified, MDE should establish a mechanism for capturing the data in a central database that is integrated with district expenditure data in order to facilitate data analysis. Further, once the program-based school district data collection and analysis system is fully operational, MDE should work with the districts to develop a data dashboard that reports efficiency metrics for each district in a format that is complementary to the No Child Left Behind district report cards for academic accountability.

Conclusions

Because PEER observed that the fourteen selected school districts did exhibit some elements that could be considered components of a larger efficiency and accountability framework, PEER proposes that Mississippi’s school districts adopt a disciplined approach to examine, review, and guide their decisionmaking process and improve efficiency, such as the Data Driven Decisionmaking (DDDM) model. Pages 57 through 60 of the report provide an example of application of the data-driven decisionmaking process to a school district’s decision of whether to continue contracting out janitorial services.

While several possible models exist regarding how to implement and organize DDDM, four key elements are universal to any model:

• a district must gather raw data tailored to tracking the outcome of a specific goal;
• this data must be distilled into a usable form to produce information offering insight into the goal;
• this information must be coupled with the priorities of the district and the relative merits of the goals; and,
• all of this information should be weighed by the district to establish, refine, and reexamine the goals of the district.

Based on PEER’s observations within the selected districts, many data sets are already being tracked and reported by the districts that could be utilized in data-driven decisionmaking. The ultimate goal is for the schools and districts to improve their decisionmaking through ongoing analysis of data (including making unit cost comparisons where valid and reliable) and implementation of improvements based on knowledge gained through analysis.

1 On November 12, 2013, PEER issued Report #578, Identifying Options for Improving the Efficiency of Mississippi’s School Districts: Phase One. That report proposed a Phase Two that would include a comprehensive efficiency review of selected school districts with the goal of identifying best practices.

2 PEER’s sample included the Aberdeen, Amite County, DeSoto County, Enterprise, George County, Hattiesburg, Itawamba County, Jefferson County, Jones County, Lamar County, Moss Point, Okolona, Rankin County, and Tunica County school districts.

3 To determine measures of efficiency and academic performance, PEER utilized data provided by the Mississippi Department of Education for the 2012-2013 school year.

4 Total Quality Management, Organizational, Learning, and Continuous Improvement (TQM) are management technique models practiced by private industry and manufacturing to increase efficiencies in the quality and delivery of goods by emphasizing that organizational improvement can be achieved through directed review and analysis of data to set and benchmark goals.

5 The RAND Corporation is a nonprofit, nonpartisan research organization that was initially founded in 1948. While RAND researches multiple policy areas, its research on pre-K, K-12, and higher education covers issues such as assessment and accountability, choice-based and standards-based school reform, vocational training, and the value of arts education and policy in sustaining communities and promoting a well-rounded community. In 2006, RAND Education issued a report entitled Making Sense of Data-Driven Decision Making in Education, from which PEER drew this model applied specifically to education.

6 PEER utilized academic performance ratings of districts developed by the Mississippi Department of Education for the 2012-2013 school year.

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