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Implementing a data quality improvement plan

 

Understand your data’s value and prioritize where attention is needed

Once you’ve audited your data, it’s time to prioritize the issues identified and implement an actionable data quality improvement and management plan.

The challenge with data is that there are often large volumes of it and your audit may highlight several issues across different areas, so how do you prioritize what should be addressed first?

You need to understand the value of the data to your organization and the impact that it has.

Data, like a business’ equipment, is an asset that holds a value. To provide perspective, imagine if all the data in your organization was lost tomorrow, what impact would this have? How much would it cost to replace it?

Assigning a monetary value will not only help you prioritize where your attention is most needed but will also help you defend and justify investments in data management.

The focus when determining the value needs to be on the concept, securing the understanding of data’s worth, and the need for regular maintenance, rather than the specific details of whether your company’s data is worth $5m or $5.2m.

 

Here are three possible approaches that can be taken to ascertain the value of your data:

 

  • Consider how much your company would be worth if it was sold without customer data. Take the company’s market value and assign a percentage of this to your data – this calculation is rudimentary but can make people think and start discussion.
  • You could look at the incremental sales that are driven by data added to the cost savings from the use of quality data. This is a more precise, but harder to achieve calculation. You are looking at response and conversion rates, but other factors such as collateral, special offers, and salesperson effectiveness can also impact results.
  • Lastly, you can calculate its value based on the volume and completeness of your data. This is a middle-ground calculation between options one and two, and it’s not overly time-consuming or complicated to calculate.

Let’s run through a worked example calculation of Company A:

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The customers at Company A are worth $200 each and we know that they need to renew every year. You allocate 20% of this value to the data, then split this amount equally across four variables – customer name, customer address, email, and phone number.

You allocate 20% of this value to the data, then split this amount equally across four variables – customer name, customer address, email, and phone number.

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Once you have applied this calculation, you will have three figures to present to senior management:

  1. The value of your data
  2. The potential increase in value if the inaccuracies were fixed
  3. The investment required to maintain data accuracy and quality
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