Organizations are singing hosannas to AI while their data foundation crumbles like gingerbread.
We’re all humming the wrong hymn. Companies want to herald advanced analytics before they’ve secured the basics. They’re ready for the hallelujah chorus of automation without practicing the opening verse of data quality.
The cost of skipping ahead? A $12.9 million annual loss per organization from poor data quality alone. That’s one expensive offering nobody requested.
O Little Town of Data Governance
Data-driven decision-making doesn’t start with shiny algorithms wrapped in festive paper. It starts with controls that ensure data is secure and high quality.
Most leaders skip this quiet, humble beginning. They confuse building flashy data science capabilities with enabling actual decisions.
Skip quality controls and you’re lighting candles in a sanctuary with no foundation. The data could be wrong. Misleading insights follow like a choir singing off-key. Incorrect decisions compound like snow in a blizzard.
Hark! The Data Experts Sing
Translating data into actionable insight requires two experts working together in perfect harmony. A data expert and a business expert. Both voices must blend or the hymn falls apart.
Without this partnership, predictable failures emerge faster than relatives overstaying their welcome.
Data people create technically perfect insights that solve no business problems, like offering a gift at the altar that nobody needs. Business people can’t articulate what data could do for them. Both scenarios happen constantly.
Lack of effective collaboration causes 86% of workplace failures, including in data science departments. That’s a lot of silent nights at the office.
While Shepherds Watch Their Dashboards
Most people aren’t data literate. They’re reading ancient texts in the dark, wondering what the symbols mean.
They can’t interpret basic visualizations. They need someone to proclaim the good news instead of discovering it themselves.
Data quality can be poor like frankincense left out too long. Critical information goes missing like a star hidden by clouds. Anomalies slip past unnoticed. Visualizations confuse rather than clarify.
Better dashboards won’t fix this. Neither will fancier tools wrapped in gold and myrrh. The problem lives in the gap between what data shows and what people understand.
Angels We Have Heard On High (Promising AI Miracles)
AI usage jumped from 55% to 75% among business leaders in just one year. The proclamation echoes everywhere. Yet few organizations experience meaningful bottom-line impacts.
They’re singing gloria without learning the verses that come before. They’re trying to reach the highest notes without mastering the melody.
Communication breakdowns are common as tangled tinsel. Misunderstandings multiply. The partnership only works when both experts can translate between each other’s expertise.
Joy To The World (When You Build It Right)
The actual sequence organizations need looks nothing like their wish list to heaven. Start with data quality controls and security. Add literacy programs that teach interpretation. Build cross-functional duos who speak both languages.
Only then can you build toward sophisticated analytics. Only then does the sanctuary actually fill with light.
Success requires following the right order of worship. Each capability depends on everything that came before it. Skip a step and the whole hymn falls apart like a poorly constructed nativity scene.
We keep wanting the triumphant finale with algorithms processing and predictions flowing. But true joy lives in getting the foundation right first.
Even if it means starting with the quiet, humble work of data quality. The work nobody sings about but everyone needs.