It doesn’t come as a surprise to most people that when it comes to the CRM, there are definitely some data quality issues. In fact, according to Salesforce about 70% of CRM data “go bad” or becomes obsolete annually.
Incomplete, inaccurate and out-of-date data are all forms of bad data and it is often an overlooked problem. Management knows it’s a tremendous task to take on some form of data cleansing, but it’s something that has to be done. It is a lot of work to cleanse the data, but data is the lifeblood of a CRM system, and when that data is inaccurate it infects the entire system, outcomes, and sales effectiveness.
Many organizations are aware that data quality issues exist, no organization is immune to it. However, few realize the significant costs involved with ignoring bad data and fewer implement proactive measures to combat and treat the source or cause of bad data.
Is Bad Data Really Worth Worrying About?
The answer is a resounding yes.
According to a survey conducted by Experian Data Quality, they found that inaccurate data had a direct impact on the bottom line for 88% of responding companies, with the average company losing 12% of its revenue because of it.
Another study conducted by DiscoverOrg found that sales and marketing departments lose approximately 550 hours and as much as $32,000 per sales rep from using bad data.
When it comes to data quality issues, it isn’t just about the money that is lost. It’s also about the time that is lost for those sales representatives and management who are working with inaccurate data and the decisions made by bad data.
What are Some Problems Caused By Bad Data?
There are numerous problems that can be caused by bad data in a CRM. We could write an entire white paper on all the problems caused by bad data, but for this blog, we will only highlight a few of them.
Neglected Sales Opportunities
Poor visibility and haphazard allocation of opportunities is one reason for sales oversight. The purpose of the CRM is to help sales team stay on top of qualified opportunities and move them down the pipeline. If sales teams are working with inaccurate and out-of-date data, then perfectly good sales opportunities could go by unnoticed. Or the focus could be placed on the wrong opportunities, which also lets those good ones get away unnoticed.
Skews Forecast Accuracy
To ensure forecast accuracy, there also needs to be data accuracy. There are cases when sales representatives may forecast the same opportunity multiple times in different fiscal periods, which skews the forecast. If an opportunity has been forecasted multiple times, this means it hasn’t closed in the original stated fiscal period and the revenue that was supposed to close hasn’t.
When data is missing, inaccurate or difficult to track, this doesn’t help to build forecast accuracy.
Longer Sales Cycles
When sales teams don’t know where to prioritize their time or spend time on outdated opportunity information, this causes an efficient sales process. Inefficient sales processes cause sales cycles to slow and stretch which results in spiraling costs. Bad data can sometimes lead to organizations to design its internal and external processes inefficiently, which will, in turn, affect the ability of an organization to serve its employees and clients efficiently.
Practice Good Data Hygiene
There’s no time like the present to make a change. Bad data is never going to fix itself, and most likely it will continue to get much worse. Tackling this type of task is daunting, but it’s something that has to be done. Good data hygiene means taking the time to clean up, verify and organize the data. Starting here allows companies to tackle major issues and remove elements that may be plaguing the system. This can start with something as simple as telling sales teams that this week they need to clean up all expired close dates in the CRM.
What really matters is how data, technology, and analytics can help sales teams and leaders improve fundamental sales decisions and processes.
Use a Sales Enablement Technology
Sometimes it may not be enough for management to rely on end users to update their data consistently and accurately. By leveraging sales enablement technology, some of the responsibility to keep track of bad data is taken away from sales teams which frees up their own time to sell. It also gives management more oversight because they can also see bad data flagged in the system.
Vortini highlights and warns management about bad data in the CRM. Individual opportunities are color coded based on the severity of the issue. Vortini highlights Action Required Items such as:
- Forecast opportunities that have been won/closed in the future
- Inactive sales representatives that still have opportunities linked to them
- Opportunities still open in the past fiscal period
- Opportunities open in past date but still in the current fiscal period
Sales teams need to work with accurate and up-to-date information. Management needs to be sure that opportunities expected to close are actually going to close and aren’t past the open due date.
Request your no-obligation demo with Vortini today to see how we highlight and track bad data in the CRM.
Jess is a communications professional and Vortini’s lead content/web developer. Her current interests lie in the intersection of sales technology and machine learning. In her free time she reads a book-a-week, practices yoga, and is an avid gardener.