Archive for 'Data Quality'

The Decision Wobegon Effect

The Decision Wobegon Effect

May 15, 2013 by

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In his book The Most Human Human, Brian Christian discussed what Baba Shiv of the Stanford Graduate School of Business called the decision dilemma, “where there is no objectively best choice, where there are simply a number of subjective variables with trade-offs between them. The nature of the situation is such that additional information probably won’t even help. In these cases – consider the parable of the donkey that, halfway between two bales of hay and unable to decide which way to walk, starves to death – what we want, more than to be correct, is to be satisfied with our choice (and out of the dilemma).”

 

Data Quality, Trust and Consumer Behaviour

Data Quality, Trust and Consumer Behaviour

May 10, 2013 by

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Most businesses obsess over their sales performances. Nowhere is this taken to more extremes than the retail sector. They increasingly employ ever more sophisticated means to track, cajole, entice, motivate and understand their consumer purchasing behaviour.

 

Change = WIIFM > WMETP

Change = WIIFM > WMETP

May 08, 2013 by

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My previous post about change management, which advocated nudges not mandates, received an excellent comment from Karen Way: “What I’ve found that works to nudge people into accepting data quality as part of their norm is to demonstrate the benefit to them, the WIIFM (what’s in it for me) factor. This is especially true…

 

Why Poor Data Quality is a Business Certainty

Why Poor Data Quality is a Business Certainty

May 03, 2013 by

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Although I do far less on-the-ground consulting than I used to, I still occasionally get to sample the delights of walking into an organisation, performing a data quality assessment and watching the occasional jaw hit the table when the client sees the actual state of their data.

 

Getting Schooled on Measurement

Getting Schooled on Measurement

May 01, 2013 by

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In previous posts, I explained how measuring is intrinsically fuzzy and what is being measured is intrinsically fuzzy. In this post, I want to take on the common adage: “you can’t manage what you can’t measure.”

 

Where to Start with Overloading

Where to Start with Overloading

Apr 26, 2013 by

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When we design systems, there is always a desire to build something that will support the business for some considerable time. A lot of banks, for example, still run on mainframe systems that have banking software that goes back literally decades.

 

Bursting Your Filter Bubble

Bursting Your Filter Bubble

Apr 24, 2013 by

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In a previous post about data visualization, I discussed how our expectations can distort the data we visualize a lot more than we may realize, causing us to mistake dashboards for magic mirrors reflecting back our own image of what we want our data to show us.

 

Want to Become a Better Data Quality Practitioner? Change Your Lens

Want to Become a Better Data Quality Practitioner? Change Your Lens

Apr 19, 2013 by

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How do you become a better data quality professional? I get asked this question a lot and it’s often by those who are looking to learn new skills in technology, tactics and methodologies for data quality.

 

Use a No Brown M&M’s Clause

Use a No Brown M&M’s Clause

Apr 17, 2013 by

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There is a popular story about David Lee Roth exemplifying the insane demands of a power-mad celebrity by insisting that Van Halen’s contracts with concert promoters contain a clause that a bowl of M&M’s has to be provided backstage with every single brown candy removed, upon pain of forfeiture of the show, with full compensation to the band.

 

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