TLDR: Bloated, inaccurate databases cause all sorts of problems: lost revenue and productivity, risks of data privacy violations, and unreliable decision-making. Everyone from the CEO to your SDRs should think critically about data hygiene. Standardize how data is collected and handled across systems and conduct periodic audits to check the quality of your data. This will drive the business forward, allowing teams to support each other and reach customers as effectively as possible.
Data runs the world, and it also runs your business.
Many leaders know this and have strategies for data hygiene and protection, but too often, the enforcement of policies and best practices is inconsistent.
This creates a culture where teams don’t know how to collect, handle, and categorize data, and lack insight into why data hygiene is so important.
The results? Inaccurate data and bloated databases—sources of pain for people in many different roles and threats to the revenue and reputation of your business.
If you’re feeling the strain of dirty data, this article for you.
You’ll learn to explain to leadership the deep impact of bad data and influence a shift to a data-centric culture, suggesting policies, practices, and perspectives on data that help everyone in the team do their jobs more effectively.
A database filled with entries that are inaccurate, outdated, miscategorized, or duplicated has a profoundly negative effect on the business.
People doing tactical work burn hours to correct and clean data.
Concerned with the quality of their information, SDRs get distracted from reaching out to people, which slows down the sales cycle. CX-wise, missing pieces of information compromise your interactions with customers, who’ll know when your outreach is less than seamless.
Between marketing operations and sales operations, bad data and unclear accountabilities cause infighting, as teams blame each other for disarray. Everyone who needs reporting, from C-Suite downwards, simply cannot surface or grasp the performance and impact of their work.
With a messy database, extracting the insights to fuel strategic decisions becomes a near-impossible effort.
Bad news for the productivity, revenue intake, strategic potential, and inter-team collaboration of your business.
Then factor in some more explicit financial costs. You’re getting charged for your database per row—bloat = dollars spent.
Excess data also heightens the risk of breaching data privacy compliance requirements.
EU regulators have issued an average of €1.4 million per fine to companies in breach of the GDPR, so if your database includes old and duplicate records of people who’ve opted out of communications or asked to have their data deleted, you need to clean up ASAP.
The larger your tech stack, the greater the likelihood (and consequences) of disordered data.
Coming up with and implementing a system for data hygiene may seem like an effort that’ll slow you down in the short term, but it’s the smart choice every time over tolerating a messy database and all its chaos and revenue loss.
Data hygiene is a company-wide project—everyone from the CEO to your SDRs is responsible within their remit for thinking critically about how they handle data and contributing to policies.
The first thing to think about is how data enters your system. Your sources are often things like:
But could also include people like SDRs manually inputting information.
With each new entry, verify that the source is reputable and the data is both factually correct and accurate (e.g. checking for spelling errors and duplicates). And take extra care with data obtained from gated content—in the earlier stages of the cycle, people are more likely to offer untrue or incomplete information to easily access your content.
Lots of different people touch data when it’s in the system, and without a strict policy on how to handle and categorize it, things can quickly get out of hand. Standardizing the data types you collect and fields used across your systems can help to ensure you’re handling only the most relevant information and organizing data consistently.
To further help keep things clean, advocate for a dedicated data compliance team. This team comprises a board of people who assess the impact of introducing any new field, data type, or source into your database.
It’s also worth interrogating your approach to data collection. More data doesn’t necessarily make you better informed, and it’s certainly not worth the excess storage costs and risks of violating data privacy requirements.
Additionally, not all data created or data sources are equal. You may have one or several usual suspects for creating bad data. Get ahead of it by shutting those sources down so you’re not creating bad data to start with.
Ask of each piece of data you solicit:
Auditing your systems and data on a regular basis (e.g. monthly, quarterly) is crucial to determine what your baseline for hygiene should be. This is your opportunity to detect and remedy any flaws in your database.
Steps you can take to improve data hygiene:
The way you handle data can make or break your business.
Dirty data results in losses of revenue, productivity, and decision-making power—to avoid the fallout, C-Suite should treat data hygiene as a priority initiative for everyone in the organization to partake in.
Clear, enforced policies that standardize how people collect and handle data across systems, and periodic audits to check the quality of your data and sources, will drive the business forward and allow teams to support each other and reach customers and prospects as effectively as possible.
Struggling with systems and data in disorder? Drop us a line. We’re here to help.
