Grieben vs Data Management Accountability via Jigsaw Data Fusion

So this is a followup to my previous post about the Jigsaw acquisition by Salesforce. I commented on some potential reasoning behind the merger and potential PR pitfalls that could result. The strategy is now self evident based on the resulting products being offered, but I think the potential for bad PR still remains. That being said what they have come up with is some pretty exciting stuff, at least from this data coordinators perspective.

Pop over to their site to get the overview, Jigsaw Data Management There are 4 products so far, Jigsaw Team,Jigsaw Lists, Jigsaw Unlimited, and Data Fusion. The products are pretty self explanatory, Team gives you a multi-user account to view data, lists is easy list generation for marketing and telesales, and unlimited is well, unlimited.

The most exciting product from my standpoint however looks to be Data Fusion this is the tool that i skeptical guessed was coming in my previous post, it compares your corporate CRM data to the cloud sourced database held within jigsaw and gives you an overview of potential incorrect and out of date data.

I find this to be a pretty exciting tool from a data management perspective. In many organizations data management is seen as a double edged sword. Data users assume poor data quality and blame it on IT for poor cleansing, and operations blames users for poor cleansing for entry. This tool allows both sides of this discussion to stop pointing fingers and work together to clean the database.

Rather than assuming data is of poor quality, this tool references a third party to identify potential problems within your CRM. Using this tool not only can data that is verified as incorrect be identified and removed, but potential problem data can be easily added to campaigns for verification and re-engagement.

Part of the problem with data management is accountability, who is responsible? weather on the operations or user side of the discussion what to do with potential problem data is a decision has system wide implications. depending on how many stakeholders there are, cleansing can be an impossible task and the resources required to identify let alone act on data management initiatives can be staggering.

This tool can potentially become a lighting rod, rallying all sides of the debate changing the issue from, "how do we identify the dirty data?", to "here is the dirty data, how can we fix it."Its the Rosetta stone both sides have been searching for because fixing an identified problem is much easier then agreeing on what problem should be solved.

So far there is only one case study available, but I'm excited to see how this tool develops and what results customers are able to realize as a result of it. If you have any real world examples of how this or other data tools have impacted your organization from a data quality or user philosophy standpoint, I would love to hear from you.