The Maine Municipal Association represents and serves the interests of nearly every municipality in the state of Maine. Founded in 1936, MMA is one of 49 state municipal leagues that, together with the National League of Cities, is recognized at all governmental levels for providing valuable services and advocating for collective municipal interests. As part of these services, MMA has been conducting an annual Salary Survey for over 50 years, delivering valuable data to its members on the benefits and compensation being provided to the over 13,000 municipal officials and employees throughout the state of Maine.
Over the 30-year history of the salary survey, not much had changed. Each year, the survey would be mailed out to participants, responses would be collected and tabulated and the final 200-300 page report would be mailed out along with an Excel spreadsheet. While the data on the spreadsheet could be manipulated to an extent, the report itself was printed. From mailing, collection and compilation of survey data, to the dissemination of the final report and spreadsheet, the process was entirely manual. While many were comfortable with the status quo, the manual nature of the process was time-consuming and vulnerable to human-error. And with the study needing to support members ranging from small towns with as few as four employees to cities with hundreds of staff members, a one-size-fits-all-report was simply not enough.
“The Municipal Salary Survey had traditionally been conducted completely on paper. Questionnaire forms would be mailed out to, and returned by members, with their responses compiled by hand into an Excel spreadsheet,’” comments Carol Weigelt, Web Publishing Technician at MMA. “Results would ultimately be published in a long, printed report accompanied by the Excel spreadsheet.”
“It was a very tedious and time-consuming process which left us open to a high probability of error,” adds Maine Municipal Association Director of Communication and Educational Services, Eric Conrad. “When the individual who headed this project retired, we saw it as an opportunity to explore new processes.”
It was during this transition period that the MMA staff attended the demonstration of a benchmarking solution that Dynamic Benchmarking had created for another municipal association. MMA had not seen anything close in comparison in reviewing other benchmarking and survey solutions and contracted with Dynamic Benchmarking to upgrade its benchmarking process.
“We could tell right away that it would be a great process,” states Conrad. “The Dynamic Benchmarking team not only exhibited expertise in benchmarking, but also a willingness to learn about the ins and outs of our industry.”
“Compensation in municipalities can be quite complicated because of the variety of job functions each entity encompasses,” Conrad continues. “Add the numerous differences found in the operations of small town versus large city, and everything in between, and you have a wide range in the data being reported and the needs of each individual member. We were so pleased at how quickly Dynamic Benchmarking grasped these complexities and provided solutions that were ideal for our members.”
Dynamic Benchmarking’s background experience in working with municipal associations was an asset to the project, helping it run smoothly from start to finish. The new Municipal Salary Survey brought the entire data collection and reporting operation online, virtually eliminating paper from the process. While previously, members were provided with a printed report and an Excel spreadsheet, they can now create customized reports on the fly in a variety of formats using the data sets that are most relevant to their individual needs. This is especially relevant to MMA given the varied size of its members.
One method by which Dynamic Benchmarking is able to accommodate these varying groups is through the use of the Peer Cluster feature, which allows members to create a comparison group of peers by name rather than by characteristic. When these filters are activated, the users’ responses are compared to the aggregated responses of the peer group with results only displayed if the minimum data threshold requirements are met.
“The level of competency and attention to detail throughout the entire process and the application is amazing,” says Weigelt. “We would never be able to collect this data and have it searchable in the way it is now without Dynamic Benchmarking.”
Participation in the study has exceeded all expectations. Over 250 municipalities participated in the survey during the first year, far surpassing the association’s initial goal of 200, with twenty-five members completing the survey on the first day of data collection.
“We didn’t know how our members would react to a new format,” says Conrad. “We’re so pleased with their obvious willingness to participate without hesitation.”
MMA attributes initial success of the platform to a strong implementation plan that kept its members well informed and educated about the benefits of the new benchmarking platform.
“As we notified users of the new platform, we made sure to let them know that some data was already preloaded for them,” comments Weigelt. “Our members appreciated seeing that they were being given their form, not just a general one. They could see that we’d already done some of the work for them giving them incentive to add to it.”
Now that MMA is about to enter its third year of data collection, the Copy Prior Year Data feature is becoming even more important to spurring member participation in the salary survey.
“Probably one of the biggest contributors to year over year participation is the ability to simply update your data from the prior year,” adds Conrad. “Members are no longer starting from scratch each year. Most only need to go in and update their information annually without entering every piece of data. Now they only need to revise what’s changed from the prior year which saves lots of time and encourages participation year over year.”
As with many projects of this scale, MMA did come across instances when the platform did not meet everyone’s expectation, but even then, they were still impressed with the response from Dynamic Benchmarking.
“What’s probably impressed me the most is how the Dynamic Benchmarking team responded when we needed a change to the platform,” Conrad continues. “Several of our members expressed concerns that the reports weren’t printing correctly. When we mentioned it to Dynamic Benchmarking, it was resolved in only three days!”
“Absolutely,” agrees Weigelt. “We noticed that some members were entering annual salaries in the hourly rate field, skewing the overall data. Dynamic Benchmarking changed the settings in the field, so it would be flagged if the figure exceeded a certain number, prompting users to review the question and re-enter their answers.”
“Dynamic Benchmarking has truly changed how we’ve approached benchmarking,” continues Weigelt. “We’ve gone from the heavy lifting of fact checking and report compilation to more of a customer service organization – providing passwords, granting access and conducting simple tutorials on using the platform.”
“The company and its product are so flexible and easy to operate. Changes are made quickly and everyone is responsive. We can’t say enough good things about Dynamic Benchmarking.”
After the success of its Municipal Salary Survey, MMA returned to Dynamic Benchmarking in late 2018 with a new project, its annual Local Government Finance Survey. MMA, in conjunction with the U.S. Census Bureau, has been conducting this study since 2006. The data gathered through the survey is used to generate several reports including the U.S. Census Bureau State and Local Government Finance Report and the MMA Fiscal Survey Report. It is also one of the very few sources of comprehensive municipal revenue and expenditure data available to MMA members. Previously administered via a combination of paper and electronically submitted forms, MMA intends to increase participation as well as provide new and improved reporting options to its members by moving the survey to the Dynamic Benchmarking platform. Data collection for the study is slated to open in Spring 2019.