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The “All In” Costs of Poor Data Quality

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It goes beyond dollars and cents

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Much has been written about the monetary impacts of poor data quality. A familiar and easy to understand illustration of this is the cost of bad postal address data: The US Postal Service (USPS) estimated in 2013 that there were approximately 6.8 billion pieces of mail that could not be delivered as addressed. Beyond the fact that the USPS itself spent $1.5 billion to process that mail (e.g., forwarding it, returning it, disposing of it, etc.), that’s only a fraction of the wasted costs of postage and collateral from the businesses that sent the mail in the first place. Even assuming an unrealistically low average cost of $0.50 per mailing, we’re talking about a wasted $3.4 billion per year due to incorrect address data.

So absolutely, when building your business case for a data quality, master data management or data governance initiatives these quantitative ROI estimates on how poor quality data impacts spend, productivity, risk and growths are mandatory. But, there are other costs and impacts of poor data quality that go beyond the dollars and cents.

You must understand and evangelize the “all-in” costs of poor data quality to your business leaders. Let’s look at how bad data impacts the most critical stakeholders for any business:

  • Customers. Great products and services alone no longer guarantee customer loyalty. Whether you’re a B2B or B2C business, it all comes down to customer experience. Deliver a great, differentiated customer experience and you’ve got a great shot at a repeat customer. But, if bad data leads to a bad marketing, sales, support, fulfillment or services experience – your customer will not think twice about giving your competition the opportunity to win their business.
  • Employees. Recruiting and retaining top talent – and getting the most out of them – requires more than just a good vacation plan. The applications and tools you provide to ensure they can do their jobs effectively are all dependent on the availability of useful, trustworthy data. If bad data slows employees down, they feel their performance is suffering, they feel less job security, and their morale – along with their productivity – takes a hit.
  • Partners. Poor quality supplier data can lead to poorly negotiated supplier contracts and costly breakdowns in the supply chain, to name a few impacts. But, for many organizations, supply chain, distribution, resale and technology partners are more than a channel – they’re a strategic stakeholder that can make or break your reputation, your market share and your ultimate success. To optimize your partner relationships, you need to share relevant customer, product, and other market information. And, if that data doesn’t support the right decisions and strategies, that partnership will fail.
  • Shareholders. Whether you’re a commercial organization (a public company with millions of shareholders or a private company with key investors) or a public sector organization with legislators, constituents and regulators, you have a magnifying glass on how your business and operations are being run. The ability to both secure and protect sensitive data, and accurately report on the state of your business with trust, transparency and auditability, are massive and complex requirements for any business. If any of these stakeholders has a question on how you’re running your business, the answer “we don’t know” just won’t cut it.

Investing in data governance best practices – with help from enabling software, such as data quality, master data management, and data masking, among others – can help save you money, make money, reduce the risk of regulatory fines and beyond. To be a world-class organization with loyal customers, you must not only know the spelling of your customers’ names, but you also need to understand their preferences and habits and be able to make suggestions about items they may like. Organizations today must be masters of their customers’ data and this is what is truly required to be a Data Ready business.

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