Invest In Improving Your Data Quality

Caleb Shull 7 minute read
Multiple devices representing data.

This blog is part three of a five part Training Budget Defense series. This article focuses on how improving the quality of your team’s training data can improve your standing in the budget season.
For specific, data-driven recommendations tailored to your team’s needs, we encourage you to take our Scalability Index Assessment. It’ll give you a deeper view of how your team compares to a baseline of hundreds of other Training teams.

What Do We Mean By Data Quality?

Your data’s quality consists of several factors that determine how useful and reliable your data is. Different sources provide different dimensions of data quality, and not all of them are relevant to learning and development. In fact, there are dozens of possible factors to consider. But the most important dimensions related to the learning and development field can be summed up by the following:

  • Accuracy: Does your training data accurately reflect what you are reporting on? Are there errors in your data, caused by poor measurement or management?
  • Completeness: Does your data completely describe what you are reporting on? Are there factors you missed, or parts of the sample you did not measure?
  • Timeliness: Is your data up-to-date? Are outdated entries making your databases cluttered or unwieldy?
  • Compatibility: Is your data stored in systems and formats that can be easily accessed and compared? Are your data management systems well-integrated?

Behind each of these major concepts are hundreds of smaller questions. But they serve as a good framework for assessing whether your data quality needs to be improved. With these factors in mind, let’s consider the downsides of low-quality training data. Then, we’ll see what a training management system like Administrate can do to help.

How Can Low-Quality Data Impact the Training Budget?

Errors in your training data are expensive no matter how you look at them. The process of finding and fixing them is time-consuming and resource-intensive. But letting them persist in your data sets is a recipe for disaster.

Obviously, when employees have to take the time to investigate and correct errors in your data, that represents an opportunity cost. They could have been doing more productive, high-value work. After all, budget negotiations revolve around demonstrating strong ROI from training operations, using data. Every little bit of inefficiency and inaccuracy potentially drags those numbers down. But there are more serious, fundamental threats to the health of the Training budget from poor data quality.

Inaccurate, inaccessible, outdated, or incomplete data will turn an audit, or even just routine reporting and transparency, into a nightmare. If you’re in a heavily-regulated industry, even simple errors can trigger expensive and embarrassing investigations. Many Training teams avoid that kind of issue by investing a disproportionate amount of time and resources into constantly verifying their datasets. But perpetually fixing the symptoms is much more expensive than addressing the problem at the source.

While these impacts are direct and obvious, they actually aren’t the greatest risk to the Training team that poor data quality creates. A reputation for low-quality data will isolate the Training team from the rest of the business. Other departments are unlikely to want to use or rely on training data that they can’t trust or verify. And with training data’s huge potential to boost the entire organization, a lack of trust can seriously undermine Training’s impact.

That in turn makes it difficult for Training to justify its budget needs. When an issue comes up – and an issue will, one day, come up – Training needs to have the support of the business behind it. Unreliable data is a surefire way to erode trust and leave the team chronically undervalued by the organization.

What Causes Low-Quality Training Data?

The single biggest issue causing low-quality training data, and undermining the Training budget, is poorly-designed learning technology stacks. They introduce errors and make data management much more difficult than necessary.
Each of the four factors that we previously identified can easily be caused by a bloated, disconnected learning tech stack. Let’s break them down:

  • Accuracy: Disconnected systems require manual data transfers through spreadsheets to remain synched and to communicate with each other. Every manual interaction with your data is an opportunity for human error. A single typo, misclick, or other minor issue can potentially disrupt entire datasets if this isn’t carefully controlled.
  • Completeness: Having your data distributed across multiple systems that are poorly-connected can make it difficult to get a full view of your operations. If accessing all of your data is difficult, then you’re likely missing key visibility and insight.
  • Timeliness: In the same way that disconnected systems make it difficult to access data, they also make it difficult to keep it updated. Maintaining a large number of parallel training data sets across multiple systems increases the chances of entries becoming outdated.
  • Compatibility: Having an oversized, disconnected tech stack makes it more likely that at least some of your systems will have incompatibilities. The culprit may be filetypes, formats, or fundamental data architecture decisions. But the result is the same: difficulty comparing data across multiple systems.

Improving Training Data Quality with Administrate

One of Administrate’s core missions is improving the way that Training teams interact with their data. We’ve built our training management system to make data management, access, and analysis as simple and powerful as possible.

Our focus on integration means that often, companies can handle almost all of their training operations from within a single software system. Administrate has a built-in LMS, CRM, scheduling tools, financial tools, and more. That means you can trim down your tech stack, saving money on software licenses and improving the quality of your data.

But suppose you want to stick to some of the software that you have. Perhaps you have proprietary or legacy systems that were designed to fit your specific needs. Maybe there are security or operational constraints that would make giving up a certain system very difficult. Administrate can still be a powerful tool for coordinating your tech stack and centralizing your data.

Administrate has an open API and extensive developer support tools. Along with our commitment to connectivity and integration, that means our training management system can be linked to any software. We also have existing integrations for many commonly-used software systems. We are always striving to increase the connectivity of our platform with new integrations and an improved developer experience.

All of that connectivity enables Administrate to pull data from all of your systems into a single place. The result? Greater visibility, and no more need for error-prone manual transfers and duplicate data sets.

By trimming down your tech stack and centralizing your data, Administrate can boost the quality of your data. And with data quality being key for gaining the trust of the organization, that could mean the difference when budget season comes around.

Perhaps you’d like a deeper, more personalized look into your own team’s data quality. If so, consider taking our Scalability Index Assessment. By taking a few minutes to fill out the assessment, you can get a detailed overview of where your team stands in five key areas. We’ve identified these areas as common obstacles to maintaining healthy budgets and scaling up training operations.

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Or, check out the other blog posts in this series:

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