Enterprise search is a problem-solving tool, and for companies contending with large quantities of data, documents, and other assets, it’s one of the most effective tools out there. Enterprise search tools have dramatically increased productivity and made it easier to coordinate efforts company-wide. By using an effective enterprise search tool, users can quickly hunt down relevant information.
Yet enterprise search developers and the programs themselves face many challenges. Some challenges stem from the nature of the technology itself. Other challenges emerge from the outside world. Either way, obstacles tend to restrain productivity.
The following are a handful of the biggest challenges faced by enterprise search tools.
Unstructured data: Unstructured data is data that does not have an already-defined data model or at least isn’t organized in a predefined manner. Much of the data people work with daily through analytic programs is structured and organized. This makes it easy to work with. Yet somewhere between 80-90 percent of the data an organization generates is actually unstructured. It can be challenging for search engines to sift through and work with such data.
Poor understanding of search user behavior: The world is data-empowered. If you run a website, you can install Google Analytics and take a deep dive into your customer’s behaviors and, ultimately, outcomes. While most enterprise search engine developers have been digging into user behavior, many lack access to good analytics programs. Ultimately, enterprise search engine companies don’t know as much about users as they’d like.
Imprecise Metadata: How often do typical users update their file’s metadata? Not often enough. Metadata, such as author fields and individual blog post tag lines, can be automatically set and forgotten for future projects. When new blogs are written or a new author takes over, the user must update the metadata so the enterprise search can properly index the file. Inaccurate metadata creates large enterprise search challenges. Data that’s improperly labeled cannot be found so easily.
Inadequate employee training: An enterprise search engine is only as good as the user behind the keys. While enterprise search engines have become far more user-friendly in recent years, many employees still don’t know how to use them. This can restrain productivity. As enterprise search tools become more fully integrated within organizations, expect usability to move to the forefront.
An ever-growing deluge of data: Companies are collecting more data, more often, and demanding results more frequently. In fact, this is one of the biggest enterprise search challenges. Businesses seek a management solution for this massive, always changing, data search. It is important for enterprise search functions to be user-friendly, widely available, and up to date with the latest technological advances. Deploying a modern enterprise search platform can eliminate the issues around an evergrowing, evolving data set by consistently searching, sorting, and compiling information for users.
Employee-strapped IT departments: Many IT departments are struggling to fill roles. So when it comes to implementing, maintaining, and expanding enterprise search solutions, it can be difficult to find the needed time and labor hours. This is true for companies big and small. Likewise, search engine solution providers are struggling to find the staff needed to refine their products.
Security risks: Like any IT system, and especially one connected to the web, enterprise search solutions must constantly contend with security matters. Hackers would love nothing more than to hijack an enterprise search solution and dig through a company’s data and documents. Indeed, in the wrong hands, an effective enterprise search engine would compromise much of a company’s most vital information.
Inaccurate search results: Using a basic keyword search creates enterprise search challenges. Search provides an effective way of finding pertinent information from large amounts of data, but only if the users know what to search for. A user enters a keyword to search for relevant data. The information they are looking for may not be optimized for the proper keywords and therefore not show up in search results.
Additionally, the conventional enterprise search cannot take keywords in context. Out of context, irrelevant data may come up because of shared keywords making it harder to sort through.
Difficulties accessing content: Data can be stored in countless formats and in numerous locations. Some data/content may be corrupted, and other files run the risk of falling through the cracks. It’s a constant battle to keep abreast of everything.
Disparate and scattered hardware systems: Ideally, enterprise search will allow you to access content and data across the entire organization, whether global or local. However, the huge number of devices, occasional lack of Internet access, and other challenges make it difficult for enterprise search engines to crawl every device and hardware system.
Miscommunication between employees: What if an employee goes on vacation or falls ill, and was unable to hand off crucial information and documents? Employees will often turn to enterprise search to hunt the documents down. However, if the information wasn’t uploaded to the cloud or otherwise made accessible, it can be hard, if not impossible, to find.
Balancing access and restrictions: Who should have access to what? Who should be restricted from what? Defining permissions is difficult both for search engine solution providers and employees who help oversee them. Nonetheless, it’s vital to ensure that the appropriate controls are in place.
Properly setting up the proper access to content for each user is a crucial management solution for corporations and small businesses alike. It’s important to keep the access up to date and accurate.
Irrelevant results: Enterprise search results have become far more accurate and useful in recent years. However, that doesn’t mean that every problem has been solved, or search results are always perfect. Solution providers continue to strive for more accurate and relevant results, but perfection may never be obtained.
User role and context can improve the relevance and accuracy of search. Session-based personalization technologies are already available in enterprise search software from leading vendors. In addition, having a user-friendly enterprise search function that offers semantic search and language processing technologies is important to allow users to find relevant, accurate data for their specific keywords, in the applicable context.
Integrating new technologies: Both artificial intelligence and machine learning have made waves in the search engine field. Yet, developing AI and ML technologies is easier said than done. And even after these technologies are created, integrating them with search engines remains a present-day challenge.
Consolidating systems: Many companies use a myriad of different enterprise search engines, each with its own purpose and strengths, as well as weaknesses and limitations. Bain has found that over 60 percent of knowledge workers must use at least four different systems regularly to access relevant information. Consolidating search systems would be an improvement for all parties involved.