First Time Right in Data Management

The only true way out of the dilemma is the "First Time Right" principle also in data management. We all know the various incidents caused by incorrect customer, article and supplier master data.

Some examples:

The delivery goes to the wrong address. It causes high direct costs due to the wrong delivery and indirect costs due to delayed invoicing - all because the customer was not created correctly.

Or: You cannot keep your service promise of 24-hour delivery because item master data or inventory information is incorrect or incomplete.

You get an evaluation that leaves you with the vague feeling that something just isn't right. In a nutshell, poor quality data of any kind is a risk for any company.

Data quality essential for risk management

Experts believe that around 25 percent of the data in ERP and CRM systems is simply not correct - and in view of the enormous daily increase in data, the potential for danger is also growing dramatically.

Nevertheless, awareness of the need for optimal data quality was rather low for a long time. With the advancing digital transformation in companies, this is now changing.

The importance of data quality for corporate success can also be seen in the fact that regulations for risk management in the financial sector, such as Basel III and Solvency II, also deal with it.

The question now is how to optimize the quality of the data. For many, "data quality" is a nebulous term.

In a nutshell, data in the company must fulfill the intended purpose optimally and meet defined quality characteristics for this purpose - it must reflect reality in terms of content and time, be error-free, complete and consistent. Duplicates must be avoided at all costs.

King's Path First Time Right

Correcting data after the fact is a time-consuming and costly undertaking. The silver bullet in data management is called "First Time Right". The only way to get a grip on the problem is to avoid incorrect or incomplete data as early as the data capture stage.

Often, data entry directly into ERP and CRM applications is seen as laborious and complicated, and is limited only to the group of people who have a license to do so. These restrictions can lead to incorrect or embarrassing entries.

A remedy here can be to enter the data in a clear, everyday application such as Microsoft Excel, which serves as the front end for the ERP or CRM application. This approach enables the standardization and streamlining of data management processes throughout the company.

The interaction between Excel and the respective ERP or CRM system is handled by our Winshuttle platform. As an alternative to Excel, this also enables data entry via individual HTML forms that are precisely tailored to the respective process - this also allows extensive data management workflows to be implemented with the aim of further optimizing data quality.

The Winshuttle platform also takes care of the mandatory validation of the data even before it is transferred to the ERP or CRM application - optimally with the same functions offered by the ERP or CRM system used.

Data quality - a matter for the boss

Companies would do well to raise awareness of the need for data quality at all levels. This works best with clear responsibilities in a top-down approach at management and departmental level - so optimizing and ensuring data quality is a matter for the boss.