What Is The Real Cost of Bad Data?

Data cleaning can involve costs and efforts. The costs of not having clean data are many times greater. Modern general management and quality management systems rely heavily on data to run successful businesses through deliveries of cost efficient but quality products and services.

The absence of either product/service quality or competent costs can result in loss of sales and profitability. Bad data can increase logistical, labour and inventory costs

Increased labour costs

Consider the case of a web retail organization. Poor product specifications published on the internet can result in a higher number of calls to the company’s call centres increasing staffing needs and therefore costs. If the company fails to increase staffing, irate customers can switch to the competition as an alternate option resulting in loss of revenue.

Even if all information is published, highlighting important information is important. Data classification and metadata is an essential part of maintaining good data and its valuable usage.

Larger Product inventories

Product inventories have to move to the customer in the shortest possible time. Reliable and sales and marketing data is crucial to inventory planning and control. Higher and larger inventories mean substantially higher inventory maintenance and cost of capital liabilities. Larger inventories inflate logistical expenses too.

Accurate and verifiable sales and marketing data are key to a dynamic inventory scenario combined with lower costs of capital, resulting in higher profits. Bad sales and marketing data has conversely resulted in losses.

Pricing Losses

Sales Personnel often miscalculate the cost of operations and productivity or a given prospect’s long-term operational overheads. A small change in committed delivery schedule commitments alone can result in huge corresponding costs because of increased staffing to meet shorter delivery obligations.

Lower pricing based on bad/incomplete operational and logistical data leads to long term erosion in profits and potential loss of reputation with the customer thereby affecting future revenues.

Higher IT Budgets

In every organization, a large chunk of the budget is spent on data rehabilitation. Simple precautions such as removing duplicates, ensuring clear metadata and defining ownerships can see a drastic reduction in IT spending on data rehab and release of money for more critical IT modernization.

Data Management is a business challenge-using expensive IT resources to mitigate risks in a primarily business domain can contribute towards enterprise losses in the long-term.

Bad data might be an abstract concept at first glance, but costs businesses and enterprises real money and lots of it. Small steps in the initial stages of data recording and periodic database maintenance can contribute immensely to business and enterprise profitability.

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