Advancements in data analysis technology can help school districts and local governments identify and thwart financial crises.
Transparency in government is an oft-used catch phrase that’s defined differently from one person to the next. States regulate what data must be provided to the public and sometimes how that data is displayed, but for the most part it is a free for all that results in communities posting fancy charts that average people — both residents and employees — have little time and inclination to understand. Reading lines on a chart or graph is one thing, but walking away with an understanding of the full picture and what it means down the road is another.
Too often local governments settle for representation of the facts as they are within a vacuum and leave out what those facts mean in the big picture. It’s understandable; local governments often lack the resources to provide more insight into the data they display. Doing so would require hours of work by finance and communications professionals tasked with compiling data, comparing it to regional trends and determining the best way to communicate the complicated information it reveals. With the number of public sector professionals in a steep decline, presenting complicated data sets in meaningful ways can be a herculean task for underfunded and/or understaffed public entities.
The public relies on their government to provide essential services and maintain accountability – closing up shop or taking a buyout isn’t an option – and local governments must evolve to work with the resources available to them to meet the demands of the public. One of the resources best suited to aid local governments both now and in the future, is intelligent technology.
The Talking Database by Munetrix is a program akin to artificial intelligence for public sector information, which utilizes the latest technology in machine learning.
The Status of Machine-Learning Systems
A leading industry analyst on agile technology transformation recently wrote a semi-controversial article “Is IBM Watson a ‘Joke?” for Forbes. The author, Jason Bloomberg, details the status of artificial technology and machine learning in contrast to the famous IBM technology. In the article, he credits IBM with wowing the world with Watson’s 2011 Jeopardy! win, but criticizes the lack of improved platforms the company has released since that time.Save time analyzing expansive data sets with Munetrix.
“VC-funded startups are now running circles around Watson’s weaknesses,” Bloomberg writes. “Watson requires many months of laborious training, as experts must feed vast quantities of well-organized data into the platform for it to be able to draw any useful conclusions. And then it can only draw conclusions based upon the body of data, or ‘corpus’ (corpora) that it has been trained on.”
Bloomberg goes on to detail additional flaws, adding that Watson is incapable of making connections between different corpora, and thus unable to glean insight outside of each individual data set it is provided.
Ernest Son, a chief data scientist for Booz Allen Hamilton, described the flaws in Watson and similar AI in contrast to human functioning, “Human intelligence outperforms machine-learning applications in complex decision making routinely required during the course of care, because machines do not yet possess mature capabilities for perceiving, reasoning, or explaining.”
Artificial intelligence might still lack the functionality for complex reasoning, but the sophistication of intelligent technology is constantly evolving, and both industry behemoths and little-known VC start-ups are making considerable advancements in machine-learning processes.
Harnessing the Power of Subject Matter Experts
Recognizing the challenges of replicating human decision making, Munetrix has harnessed the power of subject matter experts into text generated analysis of complicated data sets. The Munetrix program allows industry experts to speak to you about your specific data through the click of a mouse.
A great example is the staffing level analysis report previously prepared manually by former Michigan School Business Officials Executive Director, Ric Peterson.
Quantum technology makes it possible for super computers to learn new information at unprecedented speed. Image by Varsha Y.S. on Wikimedia Commons.
The staffing level analysis is a detailed report that incorporates complex and wide-range data. Prior to working with Munetrix, it took Peterson hours to prepare the report and once it was completed, it required about a 30-minute explanation of its analysis.
When utilizing Munetrix technologies, Peterson found that once the information was entered, The Talking Database automatically generated charts to represent every school district and public school in the State and provided a machine generated paragraph to narrate the results in an easy-to-comprehend format.
The Talking Database not only dramatically reduced the time Peterson spent building the staffing level analysis and the time he spent explaining it, but also made it possible for colleagues to access individual data sets on their own without one-on-one assistance or explanation from him.
Here’s an example of the text generated by The Talking Database:
[su_quote style=”modern-light”] If [Your District] kept the same Pupil to Staff ratio in 2017 that it had in 2010 (9.0 to 1), it would suggest 353 staff members: -33 less than the 386 it actually employed and/or contracted. If it had the same pupil to staff ratio as the Peer Group, it would suggest 334 staff members: -51 less than the 386 it actually employed and/or contracted.[/su_quote]
Munetrix technologies are helping school districts and local governments across the State reduce the cost of manpower, increase insight into how they are doing in real time, improve comparisons to similar entities and locate potential problems down the road.
Further examples of intelligent technology available in Munetrix applications include:
Legislative Algorithms:
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- Alert users when public safety drills are not compliant with legislated requirements
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- Alert users when transparency documents are not compliant with state-legislated requirements
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Artificial Intelligence Narratives (AIN) are used to:
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- Analyze data and give observations unique to each district or municipality and situation
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- Analyze data for each school district and municipality to put their data in perspective with statewide trends
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Embedded Workflow Manager that sends courtesy email reminders for:
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- Upcoming payments for Long-term Debt issues stored in the Debt Manager™ app
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- Upcoming scheduled public safety drills from our Emergency Preparedness Manager app
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- Upcoming tasks scheduled by our users in the ProjecTracker™ workflow app
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Custom Reports and Administrative Review apps allow administrators to:
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- Build a comprehensive collection of charts and reports with AIN to provide stakeholders with a broad understanding of their municipality or school district
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- Provide quick charts and reports to explain common analysis like comparing approved budgets to amended budgets
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- Provide teachers with comprehensive academic achievement analysis of their incoming students
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Charts and graphs are not enough on their own. When they are easy-to-understand, they usually only show a part of the big picture, but if they have too much information, they become complicated and difficult for average citizens and the public to understand. By harnessing years of experience from subject matter experts and merging that with machine generated text, Munetrix has provided our users with a significantly more powerful solution, one that tells the underlying story, with no bias or politics – The Talking Database.
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