Donal Dunne

Donal Dunne

Bad Data Is Criminal

Reading a recent central statistical office report showing that burglaries, theft and fraud have increased in the last quarter reminded me of a how Humberside police use data and the information they extract from it to help fight crime.

It is easy to underestimate how tenacious the modern criminal can be in avoiding attention and capture by authorities, they are not motivated to provide accurate information when questioned! Moreover, any inconsistency amongst police departments or personnel in the way in which the data was entered could add to data quality problems, inadvertently aiding the criminal. (more…)

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Posted in Data Quality, Profiling | Tagged , , , | Leave a comment

Data Quality Helps Find Missing Revenue

The establishment and maintenance of accurate customer data is the key to all revenue-generating events that a company has. A single key question is at the heart of this: Do you understand your customers? And good quality data is at the heart of the answer to the question.

As an extension every organization must know who its customers are, what do they want? What did they buy?  This question appears straightforward, but it’s not uncommon for every department within a company – finance, sales, marketing, or customer service – to have a different answer because each has their own version of the customer data. (more…)

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Posted in Customer Acquisition & Retention, Customers, Data Governance, Data Quality, Telecommunications | Tagged , , , , | Leave a comment

Beauty Is Only Skin Deep

“Beauty is only skin deep”. This old saying came to mind recently when speaking with a friend. Jane was relaying to me the amount of time she spends correcting data for management reports every month. Answering simple questions like “how many new customers did we add?”, “how many customers placed repeat orders?” or “what was the top selling product?” Without the correct answers, management ran the risk of making poor decisions on future investments in marketing campaign, capacity planning and sales and support resources.

On average Jane spent two days a month checking for duplicate customer names and standardising product codes and descriptions, just so the reports would give an accurate reflection of sales. All this was managed in multiple Excel worksheets. The reporting tool the company had invested in was still being supplemented with manual worksheets, as management did not trust the information from the tool of choice. As the months and quarters went by Jane spent more and more time managing the worksheets. (more…)

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Posted in Data Integration, Data Quality, Profiling | Tagged , , , , , | 2 Comments