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The Hidden Danger of Defective Data

Martin Doyle February 8th, 2012 Data Quality, Master Data Management

The Hidden Dangers of Defective Data
The surface dangers of bad data are obvious: it renders mailings a waste of time and money, can cause reputation damage and seriously interfere with customer relationships.

But there are other dangers lurking beneath the surface that could bite harshly into your bottom line and deliver false information that lures you into making business decisions that are financially damaging.

The Wrath of Cashflow’s Bad Side

Take cashflow – possibly the most important facet to a business of any size and a term that sends an instant shudder through those who’ve suffered the wrath of its negative side. Whether a business sinks or swims – or can prove the wherewithal to secure growth funding – will more often than not boil down to cashflow. So what if your invoices are routed to the wrong address because your data fails at the first post?

Failed Business Intelligence: Turning IT into a Dirty Word

Maybe one of the least considered – and most highly damaging – dangers of defective data is failed business intelligence.

Many organisations have information systems covering all sorts of activities, but unless they integrate the data they collect, it won’t give the bigger picture that’s crucial to making the right business decisions. Poor decisions that can be blamed on insufficient or flawed information can be incredibly costly, turning IT into a dirty word across the organisation as well as affecting the life and growth of the business.

Say your marketing campaign generates a huge response; the marketers rush to celebrate a big success. But on a profit, response and productivity level, has it been a true triumph? How much pressure did the campaign put on customer service? On the call centre? On the production line? If data covering the entire array of effects is not correctly captured and effectively integrated, how can judgement be passed?

Scenario: Thousands of Skipping Ropes versus One Hundred Horses

Take a hypothetical online toy retailer; they’re elated about the thousands of sales of skipping ropes that’s occurred after a big promotion. But had quality data been available, they’d have realised the low profit margin on this particular line, the strain the volume of sales had put on customer service and the costs involved in shipping. They’d also have been made aware it would have been more financially viable to have focussed their efforts on moving the 100 quality rocking horses taking up space in the warehouse. With consolidated business intelligence, management would have been able to redirect the sales and marketing teams into more profitable activity.

The answer: technologies designed to embed data quality mechanisms into the heart of each and every facet of an organisation, and to bring them together into an integrated format that delivers the information needed to make the right decisions for growth.

 

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Written by Martin Doyle

Martin is CEO and founder of DQ Global, a Data Quality Software company based in the UK. With an engineering background, Martin previously ran a CRM Software business. He has gained a wealth of knowledge and experience over the years and has established himself as a Data Quality Improvement Evangelist and an industry expert.