Data Quality Management

 60% of all invoices generated contain errors due to data quality.

 Every invoice error costs $40-400 to reconcile¹.

As companies grow, organically or through acquisition, their valuable data becomes more disparate and difficult to manage. Accessing the right data when it’s needed can become increasingly frustrating.

Defining Data Quality...

Consider these facts:

• a major wholesaler has estimated that 37% of its 2.5 million invoices a year are incorrect because they display the wrong product number.
• in the consumer packaged goods industry, 47% of annual purchase orders cannot be matched to supplier invoices.

All this - the result of poor data quality - is costing industry millions in lost revenue and unnecessary costs.

With sobering statistics such as these, data quality management, strategy and assessment clearly need to be higher on the agenda for many companies. Accessing the right data when it’s needed can become increasingly frustrating.

A further symptom of rapid growth is the difficulty in determining precisely who is to assume responsibility for data quality management, strategy and assessment. Sales people often prefer to own their own data since it defines their role – yet they may not understand in detail the importance of entering data in a specific way; a way that will render it useful to other departments.

Even if you are confident that your data is sound now, according to PricewaterhouseCoopers, it degrades at nearly 30% per annum.

Datactics Product Suite can locate missing data, errors, duplications and inconsistencies regardless of data type (e.g. customer, product, financial transactional). 

¹ A.T. Kearney