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The Knowledge Organization

Every enterprise has an elite team of dedicated knowledge workers. Each member of that elite team is familiar with content creation, management, and retrieval best practices. There are also dedicated experts for taxonomy, content management, search, and text analytics. The knowledge management group acts as advocates and internal consultants to help employees become enough of a knowledge worker to create, manage, and retrieve content effectively.

Gotcha! If you know anything about knowledge management in the modern enterprise, you know the above statement is true a very small percentage of the time. In most cases, you will find a librarian (if there is one) who builds the enterprise taxonomy, enhances the corporate search tool, and probably only dabbles in text analytics at best. While this single person is knowledgeable and probably has the right skills to perform all of the aforementioned tasks, chances are he or she doesn’t have the time to dedicate fully to all these areas. After all, we’re talking about one resource role for what should really be multiple roles.

I have been the single taxonomy and search expert for a company of nearly 20,000 people. While it’s easy to come up with a unified taxonomy and search program (Ahren, does this seem like a good search query to add to a best bet? Yes, other Ahren, it’s in the taxonomy, so that’s a great choice), the sheer velocity and volume of a large organization’s information can overwhelm a single resource.

So, what do you do? Fortunately, your management is going to completely endorse the idea of adding headcount to the budget for all the necessary roles to staff a complete knowledge management swat team.

Gotcha again! No they won’t. Well, ok. They might, but there will be a lot of work on your part, and likely the part of a hired consultancy, to gather the information and thoroughly scope out a knowledge management program at your organization. It is no small feat to establish an enterprise-wide knowledge management program endorsed by the executive level. It’s not impossible. I’ve seen it done, and I’ve seen it done well. However, this blog is going to focus on the resources part of this overall grand scheme. More pointedly, I’d like to talk about what kind of person makes a good candidate for a text analyst role.

Is There a Text Analyst Role?

Back up. Is there such a thing as a text analyst role? A search for “text analyst” on Glassdoor reveals there are five job openings in the United States. Of those, only three would qualify for what I think a text analyst would do. On LinkedIn, there are 146 people with Text Analyst somewhere in their job title. Perusing through these results, some do indeed look like roles who perform text analytics as the majority or part of their daily work. There are only three jobs listed here, and only one of those looks like what we’d be describing. There are many other job titles which would do text analytics, such as natural language processing engineer/ scientist, data scientist, machine learning scientist, and many varieties of these titles. There are far more results for job roles with these titles.

A rather unscientific methodology, but it reflects what I have seen in the industry. There is rarely a full-time dedicated text analyst role embedded in the business. More often, another information worker performs text analytics duties as part of their usual work and may or may not have deep expertise in the field.

What Does a Text Analyst Do?

There’s a lot of crossover with other knowledge worker roles, but a text analyst would likely perform the following tasks:

  • Identify valuable sources of unstructured text for analysis,
  • Identify structured information sources which complement the unstructured content,
  • Perform text analysis on unstructured content for insights,
  • Work with the taxonomist and search manager to identify content descriptors for classification and retrieval,
  • Perform auto-categorization on content,
  • Train users on text analytics software, and
  • Build applications for specific business needs.

The above list is by no means exhaustive, but it does underscore the need for a specific text analytics role. Other full-time resources couldn’t adequately address the above tasks due to time constraints. In addition, while there is overlap with other roles, there are unique skills here suggesting an independent role.

What Skills Does a Text Analyst Need?

What skills does a text analyst need and who is suited for this role?

A text analyst should know language and the inherent complexities and challenges of analyzing unstructured content versus structured content. He or she should be familiar with the business applications for text analytics. A text analyst should also be able to use software which can potentially have a steep learning curve or even require some degree of programming skills.

Candidates for a text analyst role can include librarians, taxonomists, content managers, or linguists. Most of these roles are business rather than technically oriented, but, depending on number of years of practical experience, are also probably familiar with the technologies needed for text analytics.

Likewise, more technical roles such as computational linguists, data analysts, data scientists, and machine learning engineers have the skills required, but tend to be roles which might be found in an IT department. Why the distinction between a technical and non-technical text analyst? In my opinion, the latter roles are more technically skilled and are capable of building text analytics applications. These technical skills find a better home within a technical department and allows for separation between the business and IT. I think this clarity is essential for balancing the requirements and demands of the business with the actual implementation. Business roles such as librarians and taxonomists facilitate direct engagement with business users on a daily basis to define requirements and overall knowledge management. They are good facilitators and can act as liaisons between the business and the technical roles needed to build or buy software.

Of course, these are sweeping generalizations about the skills and job titles which may fill a text analyst role. The real key is to find a candidate from the host of job titles listed above who has the blend of business knowledge and technical skills to apply text analytics within the organization.

Should there be a text analyst role? If you are forward-looking, yes. When I started in taxonomy, the situation was similar with many librarians acting as part-time taxonomists with very few full-time taxonomy roles. Now, there are many full-time taxonomist roles, with a company like Amazon employing hundreds of taxonomists. I foresee as the text analytics market grows–which it is projected to do–full-time text analyst roles will increase.

In the second part on this topic, I’ll discuss the larger knowledge organization and discuss where the text analyst role fits.