Change management with TIQChange

Getting fit for change!

Nowadays the management of data quality is above all looked at from the technical and organisational point of view. Questions relating to corporate culture and the related aspects of change management only rarely play a role in this. However, if this is the case data quality management runs the risk of being structured in a mechanical way and of being restricted in its ability to create an active and sustainable culture. This data quality culture represents the basic attitude of the workforce to the subject of data quality as this is demonstrated in their everyday conduct. Change management with regard to data quality is oriented towards activities and targets aimed at influencing the patterns of perception and behaviour on the part of employees and executive personnel.

The challenge consists of:

• gradually breaking down territorial thinking which places restrictions on processes and networks
• enabling staff to look beyond their own horizons
• and developing better appreciation of the importance of data quality to the company as a whole.

The basis for enabling change is created in part by suitable communication, but also by training and the appropriate measures for creating awareness. In contrast a readiness to accept change has to be developed by the relevant motivational activities and the exertion of influence within the organisation.

Focusing on people!

Because it is not possible to simply 'organise' a data quality culture, we provide you with specific approaches which are aimed at supporting your staff in positively accepting and implementing the necessary changes on the basis of their individual level of data quality awareness. In addition to methods and checklists for analysing the situation, we have available a framework with a wide range of control levers which enable specific aspects of the corporate situation to be influenced. In addition a range of instruments are applied in order to 'pick up' your staff at the exact level they have reached in terms of data quality