kelly.bailey (7/13/2015)

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I know this was a re-run of an old editorial, but...

How should people be using data? In general:

1) Big important strategic decisions should be made using long-term data that is carefully analyzed. Although such decisions can be time-sensitive, the need to make them is (or should be) known in advance. If senior leaders are looking ahead as they should be, there should (usually) be enough lead time to say, "Get the database back up for operational needs first."

2) The kinds of decisions that require real-time information are more of the day-to-day operational. If people rely on the database to make such decisions, downtime is the killer. Incomplete data is no big deal, if the immediately essential data is available and accurate.

3) Assuming we have good historical data, the laws of statistics tell us that a relatively small number of recent datapoints shouldn't change "the big picture" signficantly - and if they do, then yesterday was probably just an outlier and we shouldn't conclude much from it.

Henry Ford reputedly said that if he'd asked his customers what they wanted, they'd have said a faster horse. And unfortunately, in real life, leaders aren't always looking ahead as they should and they don't necessarily understand significance or good decision-making. So in a sense, it becomes a question of whether we're going to try to understand our customers' needs enough to actually help them, or if we're going to be co-dependent "enablers."