Proactive governance is the answer to our data dilemma
Let’s just acknowledge that the best time to recognize you have a data problem is before you think you have a data problem.
Why is that? Because there’s no such thing as perfect data.
Our business’s operational teams must navigate their data while simultaneously maintaining the data integrity throughout their organization. The consequence to this is that most companies don’t recognize they have a data problem until it’s too late — once their data has a chokehold on them.
With limited resources, there’s a strong temptation to patch together manual solutions to solve specific problems — whether it’s unique to go-to-market teams or throughout the enterprise. It’s an inefficient way to solve our data dilemmas and puts a strain on the data team’s resources. This scenario sheds light on the fact that data management, as a discipline, cannot function without platform and governance support.
Data management also cannot function without a strong call to action from within the business — from the functional departments that use and depend on data. In a recent Dun & Bradstreet report we asked B2B sales, marketing, and data leaders: “Which department, if any, do you consider to be the ‘data champion’ within your organization — [to be] the team that ‘speaks the loudest’ promoting the importance of data governance and stewardship across all go-to-market systems?”
The results showed that there is a direct correlation between confidence in sales and marketing performance and taking responsibility for our own data.
Sales and marketing teams that identified as “confident in their sales and marketing performance” were more likely to name their own team as the data champion within their organization. In other words: More-confident teams take responsibility for their own data rather than rely on other teams.
Data in Volatile Times
Navigating business uncertainty is a lot like flying a plane through a storm: It’s tough to see out the window and you can’t rely on instincts. You need to rely on your instruments and the data they’re consuming to plot the right course and maneuver successfully through the storm.
In any market condition, but especially during economic uncertainty, data is the most valuable asset in our toolbox. Good data helps the organization stay agile in turbulent times. Data provides the visibility needed to prioritize or curtail our focus. It helps marketing teams leverage data-driven insights to identify and qualify leads; sales teams can focus on the right customer at the right time; and the organization can minimize its supply, compliance, and financial risks.
The results showed us that there is a direct correlation between confidence in sales and marketing performance and taking responsibility for our own data.
If there is ever a time to commit to being a data-driven organization, this is it. Our data can help us survive past, present, and future hurdles ranging from entities such as COVID-19 to supply chain slowdowns to inflation. You just can’t be putting off your data initiatives any longer. Your organization will be rudderless, and your teams are already suffering. Like we stated upfront, there’s no such thing as perfect data.
But all hope is not lost! A strong data strategy can:
- Lead to better decision-making to get through volatile business climates — decisions based on data, not best-guess instincts.
- Help business leaders forge a clear forward-thinking strategy.
- Protect the business against a barrage of threats, whether regulation/compliance related, supply chain challenges, geopolitical unrest, or an economic roller-coaster.
The Trouble With Contact Data
Our study also revealed data accuracy as the top data-related challenge that sales and marketing teams said they are facing today.
Of all B2B master data, contact data may take the biggest hit when it comes to accuracy as it arguably seems to decay the fastest of our data types. Compared to product, organization, and vendor masters, contact data has further complexities attributable to factors ranging from human behavior to tightening regulatory policies.
The knee-jerk reaction of purchasing vats of contact data in bulk may help in the short term, but you’ll only end up having the same challenges you started with due to this type of data’s brief shelf life.
Contact data practically begins expiring the moment it comes on board. Collectively, it’s been believed that contact data’s accuracy erodes by 2.5% monthly — and 30% annually. The reasons are plenty: People change jobs; companies change locations, phone numbers, and domain names; mergers and acquisitions, reorganizations, and divestitures occur; and privacy changes dictate what we can use, to name just a few items.
The Cost of Data
A few years ago, IBM estimated the yearly cost of poor data quality in the U.S. alone to be $3.1 trillion! Although the number is stunning, it’s not too surprising to those of us who work with data.
Data is loaded with inconsistencies, errors, and neglect — it can start out with errors, for example, when it’s entered incorrectly, and even the best-quality “fresh” data, if not maintained, begins to decay. Decision makers must account for bad data in their everyday work — it’s expensive and time-consuming. One-off corrections and short-term solutions are made on the fly just to get through the task at hand, usually on a program or department basis where the rest of the organization isn’t made aware. Data silos worsen, problems are compounded, and the root cause is never addressed. This has to stop.
The Promise of AI and Machine Learning
Business leaders can no longer rely on traditional methods to acquire and manage data. They’re cumbersome and short-sighted in today’s business climate.
Machine learning can automate many of the manual tasks that were historically needed for a rules-based approach to master data management, making master data management at scale both attainable and sustainable across the enterprise via speed and lower cost of ownership. The result can be an interconnected, single source of truth — the elusive “golden record” — that empowers your teams to make more confident business decisions, driving growth and reducing risk with more trustworthy data.
The Art and Science of Data
Managing B2B contact data is both an art and a science. Your data management strategy must be aligned with your stakeholders and their strategies. But success begins by understanding that protecting our data assets is a responsibility that lies with the company, not just the data team.
Learn more about what sales, marketing, and data leaders see as their challenges as well as how our go-to-market teams are adapting to doing business in today’s turbulent business climate. See highlights from Dun & Bradstreet’s 9th Annual B2B Sales & Marketing Data Report or download the full report.