(248) 735-0648

2017 was the year of discovery for the ITSM industry. Many ITSM platform providers released enhanced Discovery capabilities. When combined with existing discovery tools from technology providers (such as Cisco, HPE and Microsoft), companies unlocked a great wealth of data about their technology environments. Discovery was by far the most impactful development in the ITSM industry during the past year – increasing both the quantity and diversity of data that companies can now capture in their CMDB and harness in their ITSM processes.


Unfortunately, the developments of 2017 have left well-intentioned IT departments with a data quality problem that now must be addressed. Almost 30% of the records in companies’ CMDBs are incomplete, incorrect, redundant, obsolete and/or conflicting with other data records. Company executives were sold on the value of the decisions they could make – enabled by data from IT. 2018 is the year they expect that value to be realized. It is this expectation which is leading many IT executives to declare Data Quality a top ITSM priority for 2018.


Companies that recognize they have amassed considerable data, but are struggling to harvest the value they expect, are launching a number of data quality initiatives this year that broadly fit into 3 themes:


  1. Improving your current data – Discovery tools have been in place for a few months and are generating a larger volume of data, and companies don’t know what to do with all of it. More data is a positive thing if it is of good quality – sadly, that is often not the case. Initiatives to improve this situation are focusing primarily on the issues of accuracy, resolving conflicts and eliminating redundancy. All of these initiatives are supporting the same goal of improved data integration.
  2. Acquiring better quality new data – For companies that were late adopters of discovery tools or want to make sure newly discovered data is high quality are focusing initiatives on timeliness (how current data is), obsolescence (removing records for things that are no longer in the environment), updating existing records to avoid duplication and increasing the diversity of data being collected about relationships. With new data, quality initiatives are targeting the same goal of improved data change management.

  3. Improving the quality of insights being harvested – Data is a resource that only creates value when it is used. Many companies that have been investing in data production are now shifting focus, harvesting more value from their data. These companies are initiating quality initiatives centered on completeness of the data set, broadening the landscape to include non-technical elements and acquiring more detailed data to support specific decisions. The common goal here is improved information consumption.


We can expect data management conversations in most IT departments to start making a big shift from “What can we produce/collect?” to “What questions can we help answer?” As this shift occurs, IT leaders will realize, in many cases, less is more, and they are able to support more confident decision-making with a well-scoped small data set of high quality than larger data sets with questionable fidelity.


The good news for IT leaders is, in many cases, the hard work of installing collectors and implementing discovery to provide a source of raw materials has already been accomplished (or at least started). The next stage of refining those raw materials into value requires less brawn and more work of skilled craftspeople with the right set of tools at their disposal. This is the year that companies must realize value from their data and look no further than their IT department for the team that can deliver.