- The upcoming SiriusDecisions Technology Exchange will feature a session on tackling sales data challenges
- Common data struggles include incomplete or inaccurate data, duplicate entries and inconsistencies
- Learn how deploying the right types of technology can help with data governance
Does accessing your sales data feel like crawling through a dangerous, overgrown jungle? If you’re tripping over duplicate entries, missing items and other data quality issues, your organization is probably not optimizing its sales productivity.
One consolation: At least you’re not alone. Sales data governance can present challenges even at high-performing organizations, and problems often multiply as a company grows and potentially acquires other companies with different systems, and as data volumes increase. In their session “Welcome to the Jungle: Taming the Wild Beast of Sales Data” at the upcoming SiriusDecisions Technology Exchange, John Donlon and Heidi Lanford will present new SiriusDecisions research on best practices for sales data governance, highlighting how processes and tools can facilitate data improvements that result in higher performance and increased revenue.
I recently spoke with John and Heidi on what you can expect to learn at their session, and why it turns out you might not want to aim for perfect sales data:
What sorts of sales data problems will your session help illuminate?
John: First, it’s important for sales to have complete and accurate data, and that is often not the case for various reasons. During our presentation, we’re going to shed light on how to assess where your data stands – where it’s good and bad – and give you some tools for being able to fix it.
Heidi: Attendees will be able to commiserate and realize that most companies are having very similar challenges. Then we’ll share as many tips and tricks as possible on how to diagnose data problems, understand what the root causes are, and prioritize where you can make the biggest impact. Improvements can often be made with process and cultural changes. Not everything requires a multimillion-dollar IT project to make it better.
So, what should organizations be aiming for when improving their data? Can it ever be perfect?
Heidi: The key is getting data good enough so that strategic and operational decisions can be made. A common misconception is that the data has to be perfect. That’s not realistic. The concept of “one version of the truth” sounds good, but it’s not achievable. Of course, you don’t want 100 versions of the truth, but we’ve never seen one version of the truth – even in companies that spend a lot of money on data. Knowing what’s good enough to make directionally correct decisions is what we’ll be emphasizing. Making decisions on good data is always better than making decisions on gut feeling alone.
John: “System of record” is another tidy phrase that sounds good, but it’s a concept that’s hard to realize, and a little misplaced. The emphasis should be on ensuring that data supporting key business processes is reliable, no matter where it originates or where it’s stored.
What specific tools and technologies can help with sales data management?
John: We’ll cover some contact data vendors – those that provide data enrichment. These vendors are increasingly popular and expanding their suites of solutions. Rather than buying a list and letting it get stale, you need to put ongoing maintenance in place and keep both contact and account info fresh so that you don’t repeat the same exercise every few years. Unfortunately, there’s no silver bullet out there. You have to assume your vendor’s data will be fresh and accurate, but having continuous data quality management is better than not doing it.
Heidi: Tools that help with auto-complete for company name, address, parent company and other hierarchy information, along with firmagraphics, are also popular. One of the biggest sales data issues is incomplete info on an opportunity or customer, and a lot of expense results from having to send out records and scrub data to make it correct. It becomes a real data governance issue. Using these tools when the record is created can enhance data quality.
John: Catching those issues before they get into the systems and start to propagate is really important. You’ll never get it to 100 percent accuracy, but if you want it as clean as possible, you need a combination of tools and human review. It’s tough to do it at scale, but that’s the best combination.
Who should be sure to attend this session?
Heidi: Understanding the impact of data and being able to quantify the value of good data are competencies that anyone in a sales operations or a sales support role needs to have. While we certainly don’t think a multimillion IT project is always necessary to remedy data problems, there is often some investment needed. Anyone in sales ops would be a great fit for this session, as would anyone dealing with any type of data governance issues. Sales finance roles will find value in attending, too.
John: While the sales ops role is probably the biggest audience, forward-facing salespeople might also look at attending so that they can see what their ops support team is up against, and also to better understand their role in the data management ecosystem.