Fans of Star Trek might recall the recurring plot lines about The Neutral Zone. The bad guys crossing it, or an innocent needing assistance requiring the bold Captain (Kirk, Picard, et al) to cross into the Neutral Zone. The irony of it all . . . there was NOTHING neutral about The Neutral Zone.
We have this same artificial neutrality in many places. Journalism. Criminal Justice. The Internet. But nowhere is it more frequently preached than business metrics. From stock market valuation to individual performance reviews there is a recurring theme of data purity.
Facts are Facts. Don’t blame me – It’s the data. I don’t make the rules. We followed the process. It’s proven science.
All of these things assume that information has the ability to be intrinsically correct. Proven science is a great analogy to the misconception about data. Electron microscopes provide a completely different “correctness” than the naked eye. How we choose to look at and measure data has a direct bearing on the result.
The first question to ask of any data is – who is measuring it, and why? How the data was captured makes a big difference in the result, and the intent of the researcher determines how it was captured.
Great example – towing weights. Many of my fellow RVers will be familiar with the sometimes significant difference between advertised weight and actual weight. Additional options, fluids, battery, spare tire, and tools can cause variation. On the tow vehicle things are just as sketchy. Tow limit measured without anyone in the truck – incompatibility between tow limit and gross vehicle weight. Why is this? Engineers capable of designing trucks and RVs should be capable of using highway scales, right?
The purpose of each measurement causes these challenges. There is a desire on the RV manufacturer to produce ‘towable’ products. Light, fuel efficient, manageable. They tend to strip out anything possible in their equation. Truck manufacturers want to emphasize their power. They tend to skew high. Of course we can pull that. But when designing – they look at specifications across the RV industry to determine customer need. If the actual average RV weight doesn’t correspond to the published data, then the design requirements of the trucks are based on a fallacy. See where understanding the purpose of the data matters?
Why does this matter to an individual? You are purchasing these vehicles. You’re buying food with calories and nutrition measured with similar bias. . .such as unrealistic serving sizes. If you’re running a small business you have raw materials and production costs that may suffer from these factors as well . . .and that’s where a business analyst can help. Not to change your successful processes, but to help you make informed decisions about your customers and your costs.
For additional information about our services, or to suggest topics please comment below, or contact us.
The entirety of this site is protected by copyright © 2016 Bright Beach Consulting LLC