Let’s Discuss Data
In the hi-tech industry of today, and in every brand, large corporation or small family office, people are obsessed with data. We collect it, we store it, we analyze it, and we quote it as statistics. There is a huge movement towards more efficient data collection and comprehensive data searching, towards tools that analyze data and tools that create facts based on the data we have collected.
Good access to this data creates a level playing field where every part of a business can use the data to help drive better decisions. Good use of data is better for consumers and for businesses. Companies that own a lot of data, such as Google or Facebook, are thought of as superpowers and rewarded by investment.
W. Edward Deming, data scientist and one of the founding fathers of data collection used to say, “Without data you’re just another person with an opinion.” (and as opinions go, it was James L. Barksdale who summed it up nicely: “If we have data, let’s look at data. If all we have are opinions, let’s go with mine.”). Data is knowledge, and we all know that knowledge is power. Having knowledge is an important part of making a decision. The more a business knows about its customers, or procedures, or end products, the better informed they can be when making future decisions.
However, while data is indeed a key factor in understanding behaviors which can lead to better decision making, it is also very limited.
Data tells us only what’s on the surface. Data tells us how a group of people are behaving right now, or what they did 6 months ago. It is dry information that alone, is not helpful or particularly informative. The number 31 reoccurring in a database is not useful knowledge until we know if it is a date, an age, a price or the number of units sold in a day.
Very often, one piece of data alone does not tell the whole story. Data needs to be understood and contextualized in order for it to have meaning. Each piece of information that a business has must be put in context of time, season, place, politics and hundreds of other factors in order for it to become meaningful. For example, if I tell you that three million Nordmann fir trees were sold in the UK last year — that sounds like an interesting fact. But if I tell you that all of those trees were sold in the three weeks before Christmas, the context turns that fact into meaningful knowledge that can help drive business practice.
You need to know how to read the data. Albert Einstein said: “Any fool can know; the point is to understand.” Owning the data is only useful if you know how to interpret that data correctly. A great example was posted by Nick Tomashot, CFO at LazyDays.
“During WWII, the Navy tried to determine where they needed to armor their aircraft to ensure they came back home. They ran an analysis of where planes had been shot up, and came up with this.
Obviously, the places that needed to be up-armored are the wingtips, the central body, and the elevators. That’s where the planes were all getting shot up. Abraham Wald, a statistician, disagreed. He thought they should better armor the nose area, engines, and mid-body. Which was crazy, of course. That’s not where the planes were getting shot. Except Mr. Wald realized what the others didn’t. The planes were getting shot there too, but they weren’t making it home. What the Navy thought it had done was analyze where aircraft were suffering the most damage. What they had actually done was analyze where aircraft could suffer the most damage without catastrophic failure. All of the places that weren’t hit? Those planes had been shot there and crashed. They weren’t looking at the whole sample set, only the survivors.”
You can dig deeper into this example here.
Data may tell us what people want, but often — that is not helpful information. Steve Jobs said, “It’s really hard to design products by focus groups. A lot of times, people don’t know what they want until you show it to them.” A great example of this is the evolution of the mobile phone. If you asked people in 2004 what they wanted in a phone, they would have said they wanted it smaller, or the famous quote by Henry Ford “If I had asked people what they wanted, they would have said faster horses.” (regardless of whether he ever actually said that or not).
Too much data means it is often hard to find the gold nugget among all the chaff. According to techjury’s big data statistics of 2019, internet users generate about 2.5 quintillion bytes of data each day and it would take 181 million years to download all the data available online. Indiscriminate collection of data means that some companies have so much data that it is hard to find meaning or to identify the useful data. Data analytics is a tool that is constantly being developed to help businesses identify useful data, and to cross reference between knowledge and statistics in a database.
Undoubtedly, we need to collect data. The industry needs information and knowledge so that it can progress. Without data, we would be lost at sea without a map. Data helps us to make informed decisions based on facts and knowledge. However, we must never forget that our role as innovators and market leaders is not to simply follow the crowd but lead it too. Steve Jobs said “Innovation distinguishes between a leader and a follower.” Data gives us information. Innovators and leaders know how to read that information to gain insights, to fuel their creativity and ultimately to innovate.
