As I usually do in my workshops, I talked to a group in Warsaw, Poland about how we should use color intentionally in our data visualization and that, in fact, the color choice itself can help us tell our story. I prepared a little activity around this issue, in which I asked them to generate a list of the words, phrases, feelings, memories, etc that come to mind when seeing this color:
Apart from “very yellow,” what words and phrases come to mind when you see this color? Do you have a positive or negative association to it?
You may be surprised to learn that auditors themselves don’t see the world in stark black and white, and we enjoy a dash of color just as much as the next person. Within reason, of course. (And for the record, our words are ‘sunflower,’ ‘sparky,’ and ‘neon sign.’) But what influence does color have on our perception, and how does that apply to our work?
Stephanie Evergreen explores the influence of colors on our psychological state, and ponders how they can best be used in data visualization. Read more here, or explore the psychology of color in more in-depth here.
Top level economic measures never tell the whole story. Knowing how many jobs have been added is important but it alone cannot tell you if job growth is enough to keep pace with population growth, or about the types of jobs being added and so forth. That is why a few years ago we introduced the Economic Recovery Scorecard which showed the progress made across nearly 40 different measures.
Josh Lehner at OEA examines Oregon’s post recession recovery, using indicators from the proportion of 18-34 year olds living at home, to bankruptcy filing stats and SNAP usage. Read more here.
Through media like visual art, fiction, and even food, artists have sought to transform static data points into vibrant and immersive experiences. In some cases, governments have commissioned these artists to produce pieces that promote resident engagement with data and other works that leverage data to bring residents into the physical city. In others, artists have independently produced data-inspired works that governments would do well to publicize and examine as potentially valuable sources of information. These works have given data another mouthpiece, made digital engagement an active experience, and provided governments with critical information on their data practices.
Importantly, art that uses data as a subject has a different goal than data visualization, which seeks to display data in a more digestible format to facilitate easier analysis. Art moves past first-order insights from data to establish an emotional connection with viewers and unlock personal, embedded meanings not accessible through quantitative analysis.
Chris Bousquet with Data-Smart City Solutions shares some vivid examples of how impersonal quantitative data can intersect with art to connect with the audience on both logical and emotional levels. Read more here.
The Oregon Secretary of State Audits Division releases an annual financial condition report for the previous fiscal year, which covers revenues and expenditures and reports on the State’s overall fiscal health. Enjoy our summary below, or read the full report here.
Auditors know how difficult it can be to muster facts to develop findings, workpaper by workpaper, and draft after draft, to get the language right. In contrast, someone can easily broadcast misinformation or, worse, distrust and skepticism about others’ information. Mark Twain had a good quote: “A lie can travel halfway around the world before the truth can get its shoes on.”
What should auditors do in these times of fewer reporters holding local government accountable, and less public confidence in facts?
Our very own auditing sage Gary Blackmer discusses the nature and necessity of trust as it pertains to government auditing. Read more here.
Periodically, we will highlight some of the methods used in a recently released audit. Every performance audit is unique and can require creative thinking and methodologies to answer our audit objective. Some of these methods could be replicated or present valuable lessons for future projects.
Disaggregating data can improve transparency and evaluation of programs. In a recent audit of Business Oregon, the audit team divided data about business finance and forgivable loans by different programs to estimate job growth and return on investment, as well as rural investments for each program.
Business Oregon reports jobs created for all of its programs combined, in one Key Performance Measure. The audit team saw their more detailed analysis as an approach that Business Oregon’s analysts could emulate and improve on, in order to foster greater transparency and improve understanding of the investments and outcomes of individual programs.
I recently sat down with Jon Bennett, a Performance Auditor, to learn about their analysis strategy and any lessons learned.
Jon’s team analyzed different business finance programs at Business Oregon and calculated net job growth for participating businesses over a four year period. They found that about two-thirds of businesses had net job growth. They also found that most of the awards went to businesses that paid wages below the county average, important since Business Oregon has a mission to create living wage jobs.
They also looked at investment by geography and found that most awards go to non-rural areas. This is important because rural areas contain 40% of Oregon’s population and were struggling to get out of the recession.
While it is valuable to look at the big picture, separating data into different programs and different measures can provide greater insights into the effectiveness of each program and how each program’s investments reflect the agency’s priorities.
Jon had a few different lessons learned, but the big take away is one I’ve experienced before – time management. Doing data analysis always seems to take longer than you expect it to. One of the time consuming aspects Jon faced was combining data from two different data sources. He thought it would be simple because he had a unique identifier, but it turns out that some of the businesses he was looking at had multiple locations and he had to look at the data more carefully.
Next time, Jon would also like to do a better job of planning how to document his work before he does it. As auditors, we always have our work checked for accuracy, which can be challenging if there is not a clear documentation trail. That is one of the benefits of using ACL, since it automatically creates a log. But sometimes other tools can be more useful. Jon interestingly switched between Excel, ACL, and STATA to use the tool that could do the task most efficiently in the way that he knew best.