What Are Government Workers Saying About Advanced Analytics?

Strategy   |   Andy MacIsaac   |   Mar 25, 2021

Editor’s Note: This is a two-part series featuring insights from the Alteryx Government Data Summit. Part one highlighted key takeaways from speakers at the event. Here, part two dives into survey results from 140 participants at the event on their use of advanced analytics.

As part of the rollout of the Alteryx Government Data Summit, the Government Business Council (GBC) polled a random sample of 140 federal, state, and local government employees regarding the status of data analytics within their agencies. The poll consisted of three questions to help understand challenges to utilizing and optimizing analytics in the workplace.

#1) How confident are you in your ability to apply data analytics to your line of work?

The poll indicated that only 40% responders were either very confident or extremely confident. This means that 60% of those polled are, at best, moderately confident in their ability to apply data analytics.

In this data-connected world, establishing a data-centric workforce is no longer optional. As GBC’s survey results show, government workers are not always confident in applying analytics to their work, whether it be from knowledge gaps, outdated tools, or inaccessible data. As new cloud and Big Data applications join legacy technology, data from all sources must be analyzed.

Meeting this challenge head-on requires a stronger and more unified self-service analytics capability to build agile, trusted data sets that are infused with actionable geospatial, predictive, and machine learning intelligence.

#2) Identify your top challenge in applying advanced analytics?

According to survey respondents, accessing accurate data is the biggest challenge to applying advanced analytics. Lack of statistical knowledge and reliance on outdated data tools like spreadsheets came in second and third, respectively.

These responses indicate that many government agencies are still impeded by resource-intensive processes in the preparation of data for analysis. Other top responses indicate that tools like spreadsheets do not scale or create an opportunity to upskill resources to higher levels of analytics capabilities. With all the talk about digital transformation, the issues raised by the responders showcase there are real impediments to progress in this area.

What agencies need to do is collectively address the ability to democratize data, automate key processes across the analytics lifecycle, and focus on upskilling all level of data workers with an agile, unified platform that augments their ability to apply advanced analytics, including predictive modeling, geospatial analysis, and Machine Learning. At Alteryx we call this capability Analytic Process Automation.

#3) What type of analytics would be most useful for your agency?

48% of the responses indicated that assisted predictive analytics would be most useful, while text mining and geospatial analytics rounded out the other responses.

For the most part, the ability to deploy predictive analytics, text mining, and geospatial analytics within government agencies has been in place for years. If this is the case, why do many government data workers see these advanced analytics capabilities as gaps? One of the reasons is that to deploy these capabilities, users are faced with using a complex array of point products that are costly, not integrated, and may require specialized skills to leverage.

With Alteryx, these impediments to deploying and scaling advanced analytics are overcome and your vital data resources are provided with an ability to upskill and unleash domain expertise to create more valuable levels of actionable insight.

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