Why Are You Struggling With B2B Data Quality? Let Me Guess …
It doesn’t take a crystal ball to predict these underlying causes.
Legendary late-night comedian Johnny Carson played a classic character named Carnac the Magnificent, a soothsayer who could correctly predict answers without having even seen the question. Over the years, Forrester analysts have helped thousands of B2B clients grapple with data quality challenges. Across those highly custom sets of business issues, a few clear patterns have emerged. Is your organization caught in a long-term struggle with marketing and sales data quality? If so, allow me to don my poofy Carnac hat and predict a few answers of my own.
You don’t have a cross-functional team of decision-makers empowered to enact data strategy.
If there is one prediction that I feel most confident about, it would be the lack of an established data governance council meeting on a regular cadence to solve data issues. If your company has not assembled and empowered representatives of sales, marketing, product, IT, finance, and legal/compliance to identify and address data challenges, your issues will continue regardless of the financial investments you make.
Your incentives for marketing and sales teams are not aligned against the same priorities.
Competing operational requirements between marketing and sales are one of the most common reasons for persistent data challenges. Broken processes and legacy work-arounds clutter the data landscape in many B2B companies, because one function or the other requires them to support a priority that the other doesn’t share. For example, one function may be struggling with duplicate accounts in a system of record that they could easily resolve, but conflicting processes mandated by another function (targeting, territory planning, account ownership, etc.) prevent it from doing the basic cleansing and account hierarchy work required.
You are waiting for technology that you can’t afford to solve your problems.
One of the truest rules of thumb for data technology is that you can’t buy technology to solve people problems. Too many companies will flinch at the complexity and internal politics involved in addressing execution processes that are introducing bad data across their revenue engine. Instead, they place their hope in a technology solution, one that won’t require them to gain agreement from departments with misaligned goals, rethink processes, or retrain resources. They chase technology that can stitch together disparate sources while continually cleansing, normalizing, deduplicating, and enriching a never-ending stream of bad data. In practice, these projects often stall out, either lacking funding or delayed by the same data complexities that up-front process reform should have been addressing.
You haven’t defined processes for integrating data across business units (especially after acquisition).
Companies working through the aftermath of mergers and acquisitions often struggle to build an efficient path to bring data and analytics together. Operations teams need a defined plan for mapping processes and data assets, developing shared definitions of key metrics, migrating systems, and retraining employees. Too often, up-front planning for post-acquisition work falls short, leaving acquired companies in limbo for years. Forrester Decisions for Revenue Operations clients can read more about this particular challenge here.
If I’ve hit the mark with any of these predictions, we should talk …
Forrester Decisions clients can work with the revenue operations analyst team for guidance and access to our full library of published research on the topic, starting with our call to Invest In A Comprehensive B2B Marketing And Sales Data Strategy To Cut Waste And Drive Revenue. My final prediction is that I will be speaking to many more Forrester Decisions clients on this topic.
