How well do you really understand your data? What are your data sources? Does your organization take an active approach to cleaning your data regularly?
Take a moment to think about the marketing dollars spent by your organization and how many of those dollars are used efficiently. For your organization to have a successful marketing strategy, your data needs to be accurate and consistent.
In fact, Ovum, a global analyst firm, estimates that poor data quality costs U.S. businesses at least 30% of revenues. Bad data is also estimated to cost our economy over $3 trillion per year. Got your attention yet? Before your data gets out of control, let’s touch on a few things that will get your organization moving in the right direction.
4 Ways to Start Improving Your Data Quality
1. Leverage Your Team.
The people within your organization who work with your data day in and day out likely have a good idea of what’s missing or what’s unnecessary. Conduct a few focus groups to collect painpoints around your customer data.
2. Appoint a Data Analytics Group.
Build a team of thought leaders in the data analytics space. This could include your existing employees and new hires, or choose an industry expert to assist your team with nitty-gritty data science.
3. Implement Standard Operating Procedures.
To be effective, it’s important that everyone within the organization is on board with your strategy. This is most important for users who generate the most data, such as a sales team who meets with prospective clients and enters information into your CRM platform. Since that may be where your data trail begins, make it your standardized process to foster consistent data initiatives.
4. Connect Your Data.
With the increase in connected systems, any organization can benefit from a standardized data repository that integrates with all systems. By integrating all of your systems with one centralized source of customer data, you’ll also minimize errors and maximize value – creating more efficiency and accuracy.
Case in Point: How It Works in Action
Want to talk about real-world, hypothetical scenarios? Let’s say you’re a manufacturing organization and you have the following systems: Enterprise Resource Planning (ERP), Customer Relationship Management (CRM) and Human Capital Management (HCM). First, the ERP is collecting data on supply chain, production scheduling, quoting and ordering. Second, the CRM is collecting customer data and marketing campaign statistics. Finally, the HCM is a collection of data of your internal workforce.
What’s the beauty of these systems working together? Once a customer requests a quote via your company website, the process will look something like this:
- Lead is generated with customer data in CRM.
- Lead is routed to sales team in charge of that region as per the HCM data.
- Quote is created in CRM utilizing connection to ERP.
- Quote is automatically sent to customer with CRM integration.
- Customer electronically agrees to sale.
- CRM converts opportunity to Closed – Won.
- ERP is notified and order is added to production schedule.
- ERP updates shipment and delivery confirmation to CRM.
- Customer Success Team is notified by CRM to follow-up.
- Six months later, a new district manager is updated in HCM.
- All customers in CRM under the previous district manager change ownership to the new one.
Sounds like a well-oiled machine, right? Exactly. That’s the whole idea.
And Remember …
Data quality is really all about understanding your data, creating a consistent standardized structure, collecting only what’s relevant and giving the right personnel access to the data – right when they need it.
