There will always be turnover. Single-company lifetime careers have become a rarity, as talented workers seek relatively short but high-impact “tours of duty.” Retaining employee knowledge has evolved from being a nicety to being a mission-critical business requirement. How do we achieve it?
People will leave your organization for more attractive opportunities at other organizations. Sometimes that attractive opportunity is completely unrelated to what your organization does, while other times the opportunity will take the shape of a role with a direct competitor. Even while we have safeguards, such as non-disclosure and non-compete agreements, to help us prevent our competitors from gaining access to our employees’ most sensitive knowledge, there has always been the question of how to maintain our own access to that information if an employee leaves our organization. The best safeguard is curating and having access to the employee’s cumulative knowledge and work products within the enterprise, even after they move on.
Organizations are turning to analytics of unstructured data to help address this issue. To function more efficiently, the business needs to understand its own content and human talent. The potential of unstructured data analytics is to identify and highlight where and with whom expertise of specific subjects exists in an organization: an unparalleled feat in the business intelligence space. Imagine the head of research at a large consumer electronics company being able to tap into a departed researcher’s findings by typing in a single word, despite not knowing the researcher’s name, location, or employment status with the company! Without this capability, the business essentially loses that knowledge as soon as the employee steps out the door.
There are a lot of tools on the market today that are leveraging analytics to supposedly address this issue. Beware, however, not all analytics applications are created equal. Most on the market today require that data be exported and moved to them in order to be processed and analyzed. Simple enough in concept, but troubling in practice. How do you know what data to export and feed the application? What if you’re missing data? After all, if you’re looking for something, it’s not likely you already know exactly where it is, especially in the case of unstructured content. So how do we answer the question of where to look before we really know where to look?
ZL Technologies has used its holistic repository foundation to eliminate the need to export and move data to analytics application. Because it sits on top of the ZL Unified Archive® platform, the new ZL Enterprise Analytics™ solution puts the ability to run complex searches, discover and visualize relationships between data, and identify key influencers within the organization… all without requiring you to know where to look, or even what type of data to look for. By using its existing ZL Unified Archive® repository, or putting one in, an organization can solve the problems of how to govern its data (click here and download the brochure for a look at ZL’s current portfolio of data feeds) and how to make that data work for it.
Rather than taking a decidedly reactive approach by letting your limited data set dictate your results, get out in front and find exactly what you’re looking for by using all of your data. It’s time to stop being reactive and start being proactive.