CAPTURE APRIL 2016 Q2 ISSUE 02 | Page 16

THE TRANSFORMATION OF TRANSPARENCY

16 CAPTURE. COSTTREE 2016 Q2 ISSUE

Back when the Internet made funny noises, expectations of data availability and transparency were quite different. Governments are quickly catching up to other industries, and they want to do more, they want to do it better, and they want to share it with those that they do it all for. Up until recently, the standard toolbox has included only local applications. Local applications run in isolated environments with a small group of system users. The outputs from these models were not displayed in a way the general public could understand. On top of that, the public had no means of accessing information that was pertinent to them.

Data visualization was in its infancy. The isolated nature of these applications prevented many large-scale metrics from being generated. Without comparables to give the data context, this information was only impactful to subject-matter experts. Even when it was shared, the layman was able to glean very little from it. Since it was perceived as essentially meaningless to a broad audience, there was no push for sharing, and there were few workable platforms to share it with.

Let’s look at one of the most ubiquitous of these tools: Excel. Isolated Excel models do not meet society’s ever-rising bar. When data is computed in Excel, the justifiability of the data becomes difficult. When performing complex calculations with many inputs, such as a fee for a city’s permit application, the preparer must update a very complex model.

Let’s say that the permit application fee in this

THEN: LOCAL APPLICATIONS

city is $225. The process involves input from six city employees in separate departments and the cost of each employee plus associated indirect costs must be factored into the permit fee.

Every year when the Excel model is updated to prepare a new permit fee, the preparer risks breaking it and delivering invalid data. With every modification and manipulation, the preparer’s confidence in the results lessens. They become increasingly hesitant to share the results with a large audience.

The Excel model also makes the preparer less inclined to share the results because of the difficulty of explaining the underlying creation method when questioned about it. When working with complex models in Excel, the user becomes intimately familiar with it but explaining and walking someone through it is almost impossible if the audience is not a subject-matter expert and willing to dedicate a large amount of time. The preparer’s motivations line up against pushing data transparency when working with an Excel model. This complex justification process also exposes the audience of the permit fee to the complexity of the calculations and risk of error.

Even if the preparer is motivated to share the data, people do not want to see a spreadsheet. The numbers may be accurate and show the correct permit fee, but they are not a meaningful way to convey information. After generating the rates, the preparer must try to prepare the data in an accessible way using Excel then find a way to share that information with a self-selecting audience.