Most business leaders today are familiar with the concept of knowledge management. The term itself has been around since at least the 1980s and the practice of building systems for distributing institutional knowledge throughout an organization is much older.
Data discovery is a newer entrant on the scene. It arose in the era of big data, when organizations found that they had mountains (or maybe terabytes) of valuable data about their customers but no easy way to turn that data into the insights that could guide business decisions.
In this post, we’ll offer details about how each of these solutions work, explain how they’re different, and identify common use cases for each. After reading, you’ll have a clear sense of whether your organization needs a knowledge management solution, a data discovery solution, or both.
Before we dive in, though, let’s offer some high-level definitions.
Knowledge management is a way of organizing, searching, and socializing all of your unstructured data assets, including PDFs, PPTs, and images.
Data discovery is a way of accessing more than what’s in final reports. It lets teams search across, analyze, and democratize structured data files from their customer surveys and market research like .SAV, SPSS, .CSV, and more.
Both aim to make information more readily available to stakeholders throughout an organization, but knowledge management is more about helping teams quickly access known knowledge and data discovery is more about deriving valuable insights from data that would otherwise sit unused.
What Is Knowledge Management? Details & Use Cases
In its broadest sense, knowledge management is sometimes described as “collecting stuff and connecting people.” Knowledge management platforms aim to pull together the many types of information that people within an organization have and generate over time. For insights teams, that information typically includes…
- Final reports compiled by third-party research vendors.
- Curated presentations that address specific business problems.
- Infographics that have valuable data points and information on your customers.
- Recent, relevant news items and syndicated data.
- Valuable information from other departments (product descriptions, process guidelines, etc.).
Knowledge management lets organizations be more efficient by creating a knowledge repository that enables stakeholders to self-service with already-known customer information. This means they don’t have to constantly ask their insights team things like, “What was that one stat you shared in that presentation last week?”
Here are some common use cases where knowledge management can prove valuable:
- Sharing insights across a team or organization. Whether you’re new to the team, you missed a key meeting, or you just can’t remember that one stat from the presentation last week, a knowledge management platform can give you access to all the knowledge everyone else on the team has.
- Ensuring knowledge isn’t lost when experienced employees move on. With a knowledge management platform, there’s no need to worry that key reports will disappear when the employee who received them via email and stored them on their hard drive moves on to another role.
- Streamlining document storage. If your research comes from multiple sources (third-party vendors, self-service platforms, public data, etc.) a knowledge management platform makes it possible to store everything in one place where all stakeholders have ready access. This can save a lot of time and effort you might otherwise spend hunting down reports you’ve already found and used.
Broadly, then, knowledge management platforms tend to benefit organizations looking for an efficient way to communicate to employees what their people know.
What Is Data Discovery? Details & Use Cases
Data discovery has a similar overall objective: to empower businesses with information. But data discovery takes a data-first approach. This enables organizations to extract additional value from data they already have by translating that data into insights.
How does that process happen? Data discovery platforms make it possible to quickly search raw data sets, see visual responses to questions on the fly (think: dynamically generated charts and graphs), and socialize customer data with relevant stakeholders.
It’s important to note that the best data discovery platforms are different from traditional analytics platforms. Traditional analytics platforms are designed for a few experts within an organization. They’re typically able to run highly powerful but also highly complicated statistics that require training to understand. Data discovery platforms, however, are designed for business users and stakeholders rather than data specialists. Any stakeholder within an organization can use a well-designed data discovery platform to query data and derive easily digestible answers, often in the form of charts, interactive dashboards, and other visualizations.
Data discovery benefits those in insights functions who collect substantial amounts of customer research data but don’t have a systematic way to query that data en masse. If most of your customer data lives in siloed systems, static reports, or impossible-to-search banner books, you could likely benefit from data discovery.
Its benefits are easiest to understand through use cases.
Use case 1: Make data-driven decisions faster
A product development lead has a hunch that they should eliminate a feature in the next version, but wants to know exactly how customers are reacting to that feature first. Without data discovery, that person might have to wait days for a member of the insights team to find the right report(s), dig up the relevant data points, and parse what they mean.
In many instances, the insights team may even have to go back to their vendor to provide a new cut of the research, which can take days (and in some cases, even weeks).
With data discovery, the product dev lead could type their question into the platform directly and instantly see visual representations of product feedback among various demographics. Within minutes, the product dev lead would know whether their gut instinct was right and would be able to confidently make a decision about whether to keep or eliminate the feature.
Use case 2: Maximize the value of foundational research
The insights team poured their heart and soul into creating a quarterly brand tracker. It’s amazing. In fact, the only problem with it is that it offers so many insights there’s no way the team can sum them up in a single report, which makes it nearly impossible to communicate to relevant stakeholders in a digestible format.
The only solution: slides on slides on slides… right?
Nope! A data discovery platform can ingest the full data file from each quarterly wave. As new waves of data become available, the team can…
- Build interactive dashboards that show trends over time and update as data refreshes.
- Empower other stakeholders (even those who aren’t data-savvy) to dig into the gold mine of information available in your tracker – whenever they have questions!
Use case 3: Connect the dots across disparate data sets
Like many organizations, you’ve found that you need more and more customer information these days – often at a moment’s notice. Because of that, you’ve started supplementing your quarterly brand tracker (which you run through Ipsos) with ad hoc surveys run through Qualtrics. You have also sourced multiple other vendors to perform various customer surveys. You can never have too much information!
The information you gather is all valuable, but it ends up in silos so that it’s hard to get a unified view of what’s going on with your customers.
The solution: a data discovery platform. Because these platforms are provider-agnostic, you can examine your vendor research from any and all vendors you work with, including DIY platform vendors. With everything in one place, you can build out cohesive, all-encompassing dashboards that paint a 360-degree view of your customers.
Which Do You Need: Knowledge Management, Data Discovery, or Both?
If you're looking for a systematic way to share existing reports, presentations, and banner books throughout your organization, you’re probably in need of a knowledge management solution.
If you’re needing to maximize the ROI of your research efforts by finding a way to efficiently dig into and analyze the data underlying those reports, you’re in the market for a data discovery solution.
It’s also possible that your organization needs both. Some form of knowledge management is essential once an organization grows beyond a single person; as organizations grow in size and complexity, they’re more likely to need software dedicated to the task. And any organization that relies on data to make decisions – and especially those organizations that pay for the data they rely on – can glean additional value by using data discovery.
If you do need both, integrations exist to combine the two functionalities into a single platform.
If you’re still not sure which solution is right for you, or if you’d like to hear more about how KnowledgeHound’s data discovery platform can help your organization, schedule a demo. We’d love to show you some options.