Many business leaders say no, not all the time. But with limited resources, employee turnover, or a lack of a qualified administrator or analyst to help–what should you do?

What I love about today’s technology age is the mass collection of data. It’s next to impossible not to have a trail anymore and be “found” in some way with a realm of accuracy. Which is great if you want to check in on an old friend from high school that moved away or you are lazy like me and want online forms to auto-populate your address when buying items online. And hey! Thanks for the extra suggested items that I am probably going to buy as well.

Salespeople and marketers know more about prospects than they ever did before, CEO’s are more globally informed about their business, and CFO’s have a tighter grasp on business optimization and dynamic planning. All thanks to this massive data collection.

This sounds great right? More data should lead to smarter decisions and less issues–like the prospect being out of the target market, long sales-cycles, or misaligned pricing. But this isn’t always the case. So what goes wrong? Did you doom yourself from the start with your data collection practices or did your business processes break down over time due to employee turnover and over “optimization”?

Start with Clean Data

This may seem obvious to some. But like Voltaire said, “Common sense is not so common.” You hear the phrase “dirty data” and “clean data” thrown around so much in Operations and Executive meetings that when you add up the time devoted to talking about it–for many businesses they would see months of the year disappear. But what do those phrases actually mean? It varies from business to business but in the world of technology these are the common definitions:

  1. Clean Data = comes from trusted sources; trusted partners, high value content, form-fills with required data fields, direct contact from a prospect, or company sponsored events
  2. Dirty Data = untrustworthy information; list purchases from untested vendors or data populated on form-fills by SPAM bots.


Dirty data can come from a multitude of other sources as well. Lazy or mis-informed sales members, open text fields that allow users to write in any variation or response as opposed to a specific value in a picklist, or just plain data duplication. The time, energy, and cost to fix a dirty data problem is draining. Taking the time to put precautions in place on your form-fills like adding Captcha’s, following a simple template for list loads, and simplifying your sales teams CRM experience with easy to train picklist values are just a few ways you can manage and maintain data accuracy over time.

Establish a Data Review & Cleanup Meeting

I’m traditionally the first person to tell you I’m not a fan of recurring business meetings. Especially those scheduled on a week-by-week basis. I like my meetings to get to the point and have actionables and timelines that my team and I can walk away with. Typically in a busy work environment a week is not enough time to gain insights so scheduling them week-over-week seems more like a cruel punishment in not allowing people to do their job. However not many meetings are more important than that of a data issue. And let’s face it; when you have a data issue in a business under 200 employees–it impacts everyone. I have seen situations where every department has concocted some version of a data band-aid or workaround to get the information they need. In many cases until you can see the pivot into positive change it’s best to have a recurring meeting on this topic with all senior members of leadership. But adjust it’s length based on changes that you see.

Who Should be involved? All Senior Leadership; Marketing and Sales leaders, any team members involved in data management

What questions should you be asking as a collective?

  • Where do we see problems?
  • What data sources do we trust? Why? Which ones do we not?
  • What are the effects of the data issues?
  • What business systems are potentially impacting the data quality?
  • Do we have competing workflows duplicating or causing mis-information?
  • What does success mean? What are our timelines?
  • Do we have a full scope of the issue or is this potentially the “tip of the iceberg”?
  • Do we need help? Should we hire an Administrator?
  • Would hiring a Consultant be better for us? What is our budget?
  • Who is taking point on this project?
  • And many more…

REMEMBER: Don’t get accusatory. Data integrity is everyone’s responsibility and traditionally bad data did not happen overnight. Pointing fingers and placing blame does not help. Concentrate your energy on making systemic changes.

TIP: Rank your pain-points by level of importance. This will help you prioritize your data cleanup project and help you determine where you should start.

TIP: When deciding between a consultant or an employee for assistance weigh the pro’s and con’s of your business needs. Consultants incur no overhead costs and are highly specialized, while employees provide dependability.

OK, I think my data emergency is mostly resolved–now what?

Regardless of whether you resolved this internally or with the help of a technology consulting business like SigX Solutions, LLC you need to continuously monitor and reassess your data cleanliness and validity. Put a data quality maintenance plan in place so that you don’t fall back down the rabbit hole of bad data.

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