Most companies and organisations find hardware asset management particularly challenging because a significant proportion of an asset’s lifecycle is ‘undiscoverable’ by automated discovery tools. This is a particular problem after purchase but before deployment, when an asset is in storage or being repaired, and after decommissioning and before final disposition, when the organisation is no longer accountable for the asset.
Unfortunately, these ‘off-line’ stages of the lifecycle are full of information security and regulatory risk, so it is important that hardware asset verification processes are implemented to identify when lifecycle and usage information is inaccurate and ensure that a) the inaccurate data is remediated and b) that process improvements are implemented to improve data accuracy in the future.
A key element of this process is the development of exception reports that allow equivalent data-sets to be compared to identify discrepancies between the reports. These discrepancies should be investigated, the errors corrected, and the related processes improved to ensure the discrepancies don’t occur again.
Maintaining hardware data accuracy is a huge job, and it is important that data verification processes are implemented iteratively, and with a focus on process improvement. As processes are improved, gradually, over time, the number of data errors will reduce.