AVIR – Thinking outside the box

Motto: Everything we teach and advise to our clients should be part of our philosophy, the way we work. We set ourselves the standard, and we would like to be the standard for our clients. Being the first to meet the standards set by ourselves is not only a responsibility, but also an opportunity for all our process owners to do the right thing to our clients and to do their work better with each passing day. [c.f. DFT.HU]

The AVIR workgroup has been founded to create a cybernetic organization capable to face the challenges of the 21st century, based on the domestic and international data-asset management experiences of the last 25 years. Employees of the university (and all who cares about the work of the team) will be witnesses to the finalization of a modern ERP methodology (UNI_BSC = University Balanced Scorecard). Therefore, the anonymous results of the workgroup will be used as the teaching material in the education of both HRM and ERP systems.

The tasks of the AVIR workgroup (according to its motto and mandate):

	To support the accreditation of agricultural courses, to gather the data assets needed for the self-evaluation, with special attention to the ISZAM (agricultural computing) course, which course produced the AVIR workgroup itself...
	To prepare the institutional accreditation, therefore to plan the steps of expanding the data assets of the course-accreditation.
	To prepare to observe the new law on higher education.
	To measure the data asset needs in case of the international accreditation of SZIU.
	Continuous monitoring of the quality of data assets: automated internal and public reporting.
	Analysis of the data needed for decision-making.
	To ensure efficient flow of data in the institution.

Our work is considered successful if:

	There will be proof for every piece of information in every spreadsheet report: by clicking on any cell that contains aggregated numeric data, the components of the aggregated value will be shown immediately.
	Initially, the employees of the institution will hardly notice the group's work, because the object is not to 'brainwash' employees, but to structure the data that has been collected on an ad-hoc basis so far.
	Employees will be subjected to less administrative burden in the long run, and administrative tasks will be more predictable.
	The possible consequences of decisions will be clearer to decision-makers (cf. data- driven policy/decision making).

Gödöllő, 2010.12.18. (PL)