Poor data costs businesses around $700 billion a year, or up to 30% of the average company’s revenue (Salesforce). Conversely, effective data quality leads to better customer experience, more accurate analytics, and an increased return on technology investments, as well as less frustrated and more efficient sales reps.
In this article, we will address the three questions we need to ask ourselves when we take a step back to assess the quality of the data in our Salesforce orgs. After all, an org is only as good as the data put into it.
1. What Does Bad Data Mean for You?
Bad data means different things for different organizations. So ask yourself, what do you consider to be bad data?
- Do you have issues with data not being populated?
- Do you have inconsistent data being entered? Here’s an example of inconsistent address data:
- Do you have issues with inaccurate data being entered?
Take a deep dive into what bad data means for your organization and map it out. Check to see if bad data from an admin perspective is the same as bad data from a sales or a marketing perspective. Once you have figured out what your key pain points are, you will need to go back to the source to see how this data is making its way into Salesforce. Alongside this, make sure you establish data quality metrics so you can monitor and measure any improvement over time.
2. What Can You Automate?
Have a think about how you can automate as much data entry as possible. Leaving data entry in the hands of the user can be a dangerous move, especially if it’s not simple or benefits the user in some way.
Sit down with some users across multiple teams and note down these questions:
- How much of their day do they spend in Salesforce?
- How much of their time is spent on data entry?
- What data should they be entering versus what are they actually entering?
- What do they neglect because it is too time consuming?
Use the answers to these questions to map out exactly what you can automate to ensure the data that really matters to your organization is being entered correctly!
Want a few examples of how you can use the power of automation?
Build screen flows for a visual guided experience for data entry (this Trailhead project is a really great place to get started!
- Automate Account fields where possible (see this guide for more info).
- If you can’t find something within Salesforce, check out the AppExchange! There’s bound to be something there to help you out.
3. Do Your Users Understand Why This Data Is Important?
Make sure your users truly understand the importance of good data. Simply declaring that a field needs to be populated doesn’t give your users any understanding, motivation, or incentive to populate it. Make sure your users understand the importance of their role in data quality, and that what they are doing really matters.
This could be as simple as one line: “We need this data to run this Salesforce report for our monthly stakeholder meetings”, or “this data is related to GDPR compliance”. This instantly contextualizes and humanizes a seemingly forgettable task, because now your users understand why they are doing what they’re doing. Data quality should not just be lumbered with the admin – it’s your users’ responsibility too!
So how can we use Salesforce to do this?
- Create page layouts that will appeal to users so they will want to enter good data – see this guide for everything you need to know about page layouts, or use Dynamic Forms to create intuitive layouts in Lightning Experience!
- Utilize validation rules so users know when they are entering bad data.
- Use help text so you can tell the user more information about the field.
- Import data where possible.
Summary
With all of this in mind, hopefully you now have the motivation you need to have a good old spring clean! Just remember, even though it might seem daunting, even the first small steps on your data cleaning journey will make a real difference.