Topic: Finance


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How to Avoid Vanity Metrics: Getting Under the Hood of Business

VanityMetrics

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Most organizations have analysts reviewing financial and operational information on a regular basis – the objective being to gain some kind of meaning from information, and to capture that meaning with a metric or metrics.  Analysts are generally providing descriptive information (telling us how we’ve done) or predictive information (telling us how we suspect we will do).

But many commonly used metrics don’t provide any actionable insight.  In other words, they’re just for show.  These are called vanity metrics.  Other times metrics don’t properly measure the underlying data, potentially resulting in what only appears to be a valid metric on the surface.  This is called an Isomorphism.

A metric is only as valuable as its ability to decipher underlying data.  When metrics are properly developed and implemented, they become meaningful because they capture the drivers that lead to the behaviors and decisions desired.

A great resource for understanding metrics is the book Lean Analytics.  Although geared to start-ups, the logic used is widely applicable to organizations large and small.  You will find much of this logic in the following paragraphs.  Read More »

Finding Angels in the Details: The Value of Information

InformationLayers

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Many of the most powerful inventions throughout human history, from language to the modern computer, were those that enabled people to better generate, capture, and consume data and information.  And at no time in our history have we captured more data than we do today.  McKinsey estimates that global data is growing at a rate of 40% per year.  The more data captured, the more opportunity for enhanced decision-making.  But in order for that to happen, data must be turned into information, and information must be turned into knowledge.  Read More »

Giving Information Meaning: The Rise of Business Analytics

BAnalytics

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Business Analytics is the scientific process of transforming data into insight for making better decisions.  Data doesn’t always cooperate with this process, as it is often massive and messy.  But no matter what condition data is in, we use business analytics to make decisions with it.

In order to make these decisions, we have to understand the ultimate value that various combinations of this data can present.  So, we measure it.  That is, we measure what data carries: information.  Measurement is what informs uncertain decisions, and almost all decisions are made under uncertainty.  Read More »

There’s No Best Age to Start a Business: The Story of Sam Walton and Wal-Mart

Walton

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After graduating from the University of Missouri in 1940, Sam Walton took a job with J.C. Penney.  He was 22 years old.  He spent five years with J.C. Penney learning the retail industry.  In 1945, Walton became an entrepreneur and bought a Ben Franklin variety store in Arkansas for $25,000.  He was 27 years old.  Walton spent five years growing his Ben Franklin store.  But in 1950, after Walton’s landlord refused to renew the five year lease he had on the Ben Franklin store location, Walton had no choice but to sell the franchise.  He sold it for a fair price, and then had to start all over again.  Walton was now 32, and it was at this age when he opened his first Walton’s Five and Dime (again in Arkansas).  But it wasn’t until he was 44 years old that he opened the first Wal-Mart.  It was a very gradual progression.  So, does age really matter when starting a business?  I doubt it.  There is no best age to start a business, no perfect time – none of that.  And Sam Walton is the perfect example of this.  Read More »