After a company’s people, data is many enterprises’ most valuable strategic asset. Data is unique in the way that it presents both opportunities and perils in nearly every corner of a business.
It is likely that if a person is using a datum (the singular form of data), they are going to be touching it again in the future, and when they do, they are going to want for their own purposes for it to be normalized, unique and complete.
And then, there is everyone else, and everything else like marketing automation that is going to need that datum to advance an Opportunity or find a new one, and they will also need it to be normalized, unique and complete.
Every single person with a Salesforce login should take responsibility for data quality.
Culture Won’t Work
In an ideal world culture would be enough to ensure high levels of CRM and marketing automation data quality. The truth is that in the real world, culture simply does not work, and culture alone without the technology is not enough.
A simple definition of culture is that it is the sum total of the learned behavior of a group of people. The learned behavior is passed on to new members as they join the group.
Culture is not a static thing, it is dynamic, and it evolves in an attempt to follow the behavior of the strongest personalities.
It is this tendency that diminishes culture’s usefulness as a means to ensure data quality.
Typically, the individuals interacting most frequently and directly with the Salesforce data are the salespeople, right? What a shocker. The group with the strongest personalities?
Sales, of course. Trying to teach Sales to care about data quality is generally like trying to teach a pig to sing. The pig won’t learn, you will annoy it at best and piss it off at worst, and in the process you will get covered in mud.
I don’t mean sales leadership. Good sales leadership will get it, and I don’t mean sales ops, either, they will get it, too. I mean the feet on the street, the customer facing team, the rank and file AEs.
In the late nineties I worked at DoubleClick selling banner ads on their ad network and keywords on Alta Vista. We were selling impressions CPM, no one had thought of PPC, or the technology was not up to snuff yet. Probably the latter, not the former.
For some reason we went through three CRM migrations in a few months, the last one was Onyx to Saleslogix. I remember a meeting we had with a young woman, a trainer from Saleslogix in Lisa Loeb cateyes. She spent 30 minutes on data standards and how to enter records properly. When she was finished she handed out a glossy one page Data Standards guide.
My cold calling cowboy (and cowgirl) comrades more or less made paper airplanes out of her guide as they put their headsets back on and started dialing for dollars with glazed eyes and a determined focus in their monthly pursuit of quota. Which after all, is really the desired behavior.
Getting Sales to buy in, down to the last BDR…good luck with that.
Without total buy in, and perfect compliance, the system breaks down and results in a tragedy of the commons. Sales should be enabled with solutions so that all they had to do was directly engage with prospects to find new deals and move existing deals towards Closed Won…that is the idea.
There is also the influence of marketing automation to thwart a culture of data quality. Marketo (the platform, not the company) doesn’t care one bit about your culture. If the email addresses don’t match exactly, it’s not the same person. To Marketo, a form submission where the first name is GREGG is just as good as Gregg.
In the end the ideal solution should be one that uses technology to enforce data quality and data standards, and requires Users to change their behavior as little as possible.
Put the Burden of Data Quality on Technology, Not People
A member of the LinkedIn Salesforce Data Quality Forum recently asked another member if they knew of any magic that could be used to enforce data quality.
Any science fiction fans familiar with Arthur C. Clarke’s Third Law?
Any sufficiently advanced technology is indistinguishable from magic. Unique Entry is an as-you-type duplicates prevention solution. Data Shield is a data standards firewall for Salesforce. The Marketo webhook using Data Shield is also now available in production, though we are still working on the documentation.
Don’t get me wrong…a culture that understands the “why” of data quality is very important, but it should not be looked to to solve this mission critical objective. Technology driven by a Data Plan that determines processes derived from collaboration between stakeholders and being driven by a designated Data Steward with real organizational clout is the foundation of data nirvana.
Then you should start measuring data quality KPIs. The first step towards any improvement is measurement.
But that is a subject for another post.
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