The battery on my 18-month-old lawnmower recently died. Blame the Vegas heat. Rather than buy a new one and possibly face this dilemma again next year, I decided to go electric.
After doing some market research, I knew which model I wanted. On a warm summer day in Las Vegas, I ventured into my local Lowes. I saw the model I wanted on the shelf but didn’t see any in stock. I finally found an employee, and he punched the product number into the computer.
Voila! Four are in stock, but where are they?
As it turns out, that is the two-hundred-dollar question. Lowes employee number one searches in vain, but he can’t help me. Nor can numbers two and three. The mowers are here, I’m assured, but we just don’t know where.
After 30 minutes of puzzled looks from Lowes’ personnel, I leave the store miffed that we can’t find one of four 50-pound lawnmowers. We weren’t looking for boxes of TicTacs, after all. Employee number three told me that “Dave” probably knew where they were, but he was out at lunch.
Not exactly confidence-inspiring. Think of this as the anti-Amazon.
All Too Familiar
Sound familiar? It does to me. Fifteen years ago, I worked for a Fortune 50 company that couldn’t tell you how many people it employed in any given week. (No, I’m not kidding.) Approximating headcount became a two-week endeavor, and readers of my blog know that I’m not the most patient person on the planet.
How much is suboptimal data management costing your organization?
As I left the Las Vegas’ Lowes, I felt an odd sense of relief. At least other lines of business were struggling with basic data and inventory management.
Big Data, KPIs and advanced analytics are amazing. Remember one thing, though, as you enter the era of Big Data: boring data management still matters. Big time. In this case, it cost Lowes a sale.
What is suboptimal data management costing your organization? Do you know? Do you care?