Olympic Skiing & Decimal Precision

By Christine Carragee
March 3, 2014

If you followed the Olympics, you might know that two gold medals were awarded in the Women’s downhill ski event.  The precision level of the timing equipment at the Olympics enables officials to discern if Tina Maze of Slovenia or Dominique Gisin of Switzerland was actually a fraction of a second faster than the other, but in their sport finish times are not reported at that level of precision.

“They kind of feel like hundredths is enough. The difference between one hundredth in that ski race, if you were one hundredth behind the winners, it’s about eight to 10 inches on the race course. So those two women were probably within a half of inch of each other one way or the other if they were racing side-by-side.”  Two Golds in One Event?

As in sports, in the business world there are opportunities to make calls about the level of decimal precision appropriate for various calculations and performance measurements.  In a scientific environment you would call the number of places after a decimal point (or comma for our European readers) “Significant Figures”.  I like this term because it puts the decision around decimal precision in the context of significance – what really matters to you, and why?

If you’re focusing on dashboards, and reporting on historical transaction data, you can weigh factors such as Visual Simplicity and the Implied Confidence Level of an estimate in the presentation of your data.  On the one hand, you want to present the data in the cleanest, simplest format possible which would argue for fewer decimal places.  On the other hand, you want to retain the descriptive power of the measures for ranking, sorting and decision making.

If instead, your focus is on projecting results in the future, say you’re using analysis workbook in Price Manager, the applicable maxim to remember is “it’s better to be directionally correct, than precisely wrong”. It may be best to display your measures rounded to the nearest thousand because viewers won’t immediately see the caveats and uncertainties you had to adjust for in your calculation.  By presenting large numbers with multiple decimals points, you are implying a level of certainty in your projection that isn’t inherent in a rounded figure.

When using data as the basis to build out complex calculations, it’s often important to store more significant figures behind the scenes, than you may choose to display.  Otherwise as calculations become more complex, you may have rounding or truncation that causes your financials not to tie back to other records.  You certainly don’t want to cause confusion, distract your audience, or undermine their confidence in the data source because rounding errors can burn up Quality Assurance hours.

At the end of many Vendavo Profit Analyzer implementation projects, you have the opportunity to polish the look of the dashboards and reports by setting the display precision of each measure.  This is, of course, a second tier concern, after the data itself has been validated to ensure it is comprehensive and as accurate as possible, but it is something you can continue to refine using the self-service configuration tools.

decimal precision screenshot

If you’re interested in learning how to change decimal precision in the application, take one of the Vendavo University courses on Profit Analyzer Self-Service Reporting.  For reading materials on standards for displaying business data, I recommend that you check out Stephen Few’s books or for a more artsy perspective Edward Tufte’s “Visual Display of Quantitative Information” is good too.

  • Decimal Precision , Implied Confidence Level , Olympics , Price Realization , Significant Figures , Visual Simplicity

    Christine Carragee

    Christine has a diverse background in pricing analysis and implementation across industries. As a pricing practitioner, she has worked in both B2B and B2C environments and collaborated across functional areas to improve margin performance. Applying her passion for data analysis, Christine has helped Vendavo customers to anticipate their data and reporting needs during requirements gathering in anticipation of the on-going the value realization process. Another component of her work has focused on corporate education and training; ensuring strong project ROI through user adoption and increased pricing understanding.