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Data Quality Management for SMEs - Part Three

By Kiran Gill

November 27, 2011 | 3 min read

Last time we looked at the essentials of Data Collection. Now, we’ll take a look at the five main points to address to achieve higher levels of data quality. Data quality begins at source which is the key when establishing best practice around data quality verification.

1.Discuss, create and finalise a business strategy: What are you trying to achieve as a business? Work with all relevant teams to establish what the data can be used for and how. This step is essential and shapes the way the rest of the data quality management programme works.

2.Data fields - Capture: After the business has established what it wants to do and why, the data capture needs to be defined. The business needs to be sure that it is capturing information that will ultimately lead to better decision making. This will ensure that the business is working more efficiently.

3.Humans: Human error and deliberate human actions can lead a database into a dark infestation of inaccurately recorded data. The element of human error needs to be identified and reduced, and this is only achievable by undertaking a series of internal audits and observations. Create procedures for data capture and incorporate the training into your induction and development plans.

4.Machines: The software you use may be relatively dated but still does the job. However, some rules can easily be put into place to make this system more effective. Decide what data is essential.

5.Hygiene at point of capture: Despite the necessary controls being in place, bad data will still get through. Bad addresses never seem to go away but there are a few free and low cost solutions available in the marketplace to support your data quality endeavours

Duplication – free: Your database is more than likely to have the capability to identify duplicates. This can be done when the user tries to insert a new customer. Duplicates should be checked for from point of capture before new records are transferred into the database. Automation is the key to performing duplication checks

Verification – low cost: Verifying the correct postal address at point of capture is easily achievable and goes a long way in ensuring that the data you put into your database is not garbage. These services are available to bring in-house, but also accessible as an online service e.g. QAS Pro.

Next time I will be discussing how to avoid data degradation.

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