Making company content accessible to employees is essential to increasing productivity and providing fast, accurate answers to customers. Pigro allows you to find information in your company's knowledge base by typing a simple question in natural language.
The enterprise search meaning is related to the possibility to search for information inside the company’s repositories and databases using an enterprise search engine. It is usually developed through enterprise search software, that allows employees to retrieve the knowledge they need to carry out their work.
Good communication within the company is a fundamental aspect of a successful strategy: without it, in fact, it is not possible to work dynamically, collaborating between different departments, causing loss of time and money.
This can only be achieved through proper creation, management, and implementation of documentation, coupled with the ability to easily consult it at any time.
For employees, in fact, it is essential to be able to find the information they need in the shortest possible time, to work smoothly and without wasting time searching for documents.
In order to facilitate communication and all the problems that result from poor information dissemination, it is necessary to implement a good enterprise search strategy, i.e. making a piece of content accessible to all employees.
In this way, employees can save the time they would normally spend searching for information needed for their jobs and focus on more value-added activities.
Every company’s goal is to eliminate wasted time and manpower from its employees and enabling easy access to documentation can make all the difference.
The various tools related to enterprise search have evolved over time.
Starting in the 1970s, the concept of Enterprise Search emerged, destined to evolve and expand to play a fundamental role in document management.
The history of enterprise search begins in the 1970s and, decade after decade, defines the enterprise search we know today.
At the end of the ’60s, there was an awareness of the amount of data and documentation created within companies and the need to query them easily.
Thus emerges the necessity to study research solutions to speed up this process.
Initially, the “problem” concerned mainly the academic field, where it was necessary to develop tools to carry out research within literary texts and documents for cultural and study purposes.
Only later, with the advent of the following decade, did companies begin to understand the potential of such solutions and the benefits they could bring to the company.
The first tools did not take long to arrive: in 1973, in fact, IBM (International Business Machines Corporation), an American technology company, created a Storage and Information Retrieval System (STAIRS), an evolution of the Aquarius software, already developed in 1969.
STAIRS is a program for storing and searching text data, with a structure designed to be used in a business scenario.
The results that are advertised by IBM are incredible for the time, regarding two factors related to the efficiency of the search: precision (the relevance of most of the results found) and recall (capturing most of the relevant results possible) claiming that their results reach up to 75% – 80% between precision and recall.
In the mid-’70s, there was the boom of minicomputers, born already at the end of the ’60s, but only in the following decade, they were purchased en masse by companies as they are smaller and cheaper than the previous ones, even if, consequently, able to offer less performance.
The wide diffusion of these devices leads to an increase in the creation of digital documents, creating the need for tools capable of searching for information within them.
The first two innovations of this decade are made by Martin Porter who in 1980 created Snowball, a program designed to process strings with the aim of creating stemming algorithms, usable for information retrieval.
In 1984, instead, Porter, following research conducted at the University of Cambridge, gives birth to the Muscat search engine, bringing a probabilistic approach to information retrieval.
At the same time, IBM’s full-text search application STAIRS continues to improve, coming to offer one of the first enterprise search desktop software.
And from California comes Verity, a new enterprise search tool that will only be fully developed and successful in the following decades, which differs from IBM STAIRS in that it is platform-independent.
From the beginning of the decade, we see an increase in the purchase of computers, both for personal use and within companies, leading, consequently, to an increase in the content produced and within which it was necessary to find information.
This led to an increase in the amount of content produced and in which it was necessary to find information.
To this is added the birth of the World Wide Web (WWW) by the computer scientist Tim Berners-Lee who, on August 6, 1991, created the first website (developed in 1990 but remained for the exclusive use of CERN until the famous date).
Moreover, in 1993, Mosaic arrives, one of the most used browsers among the first to be created, conceived by two students from the University of Illinois, which makes browsing available to everyone.
In this decade, dedicated enterprise search solutions continue to evolve, such as FAST Search and Transfer, and even companies that work primarily on consumer solutions, such as Google, decide to invest in enterprise tools.
With the advent of the new millennium and the presence of personal computers in every home and business, even the problem of Enterprise Search begins to have solutions.
Companies such as Verity increased exponentially its revenues from just over 100 million dollars in 2003 to 150 million in 2005, along with Autonomy and FAST Search and Transfer, which achieved similar increases.
This data demonstrates the change in the trend of enterprise search: from the latent need we saw in the early 1970s, it is now a clear and shared need, for which various solutions have emerged, whose evolution has come down to the present day.
Over time, in fact, there has been an increase in demand and supply, with the creation of specific and suitable solutions for every need.
For this reason, artificial intelligence, now the backbone of enterprise search, has also been involved to make search faster, thanks also to the use of machine learning.
With today’s technology, setup times have become negligible, documentation can be imported in any format and content can be queried directly from the knowledge base.
We’ve seen how the concept of Enterprise Search has changed over time, from being a necessity for a few, to be a requirement for everyone.
Enterprise Search, as we understand it today, is composed of a few fundamental features:
– content storage: it can be stored in different ways but, in any case, it must be searchable by the employee to get the information he or she needs;
– Content processing: documents, even those of different formats, are analyzed and often normalized to be more easily understood by the search engine;
– Indexing: this is the way in which the content is understood by the corporate search engine. Content is catalogued in indexes that make it easily retrievable within the repository;
– query processing: all that the user uses to query the database, both the terms typed and the actions taken while browsing;
– correspondence: once processed, the query is compared with the stored index to find relevant results.
It is good to specify, moreover, that when we talk about Enterprise search, we do not refer to a web search engine, but to an enterprise search system that differs from the first one for some aspects, such as:
– User interface: it changes depending on the purpose. in web search, in fact, the user is called to click on ads, so the interfaces are simple. On the contrary, for enterprise search, richer interfaces are made to improve user productivity.
– Faceted search: through a classification system, the user is allowed to filter the results according to some parameters chosen by him and order them in various ways. This is aimed at speeding up response times, which must be reduced to a minimum, without affecting the relevance of the result, which must always be precise and consistent;
– Tagging: it consists in labelling a keyword by giving it a meaning that will help the system find it more quickly. With the use of artificial intelligence, however, this aspect is becoming less and less common, as we can make use of systems capable of detecting the answer directly from the knowledge base, making this step superfluous;
– Controlled access: it is possible to establish individual accesses for each document, to limit the dispersion of information, in addition to a need for privacy protection.
The search for and dissemination of information within companies is often a critical issue generated by many factors. To understand how to solve them, it is first necessary to understand which elements lead to poor documentation management, thus preventing the establishment of a successful knowledge management strategy.
There are many aspects to consider when implementing a corporate knowledge management strategy. Let’s look at some of the main problems present in companies:
– disorganized information: having a lot of disorganized information is equivalent to not having any. For a corporate document to be useful, it must be easily searchable: if no one can find it or access it, it’s like not having created it at all;
– multiple repositories: using more than one repository for storing and organizing documentation is not a problem. It is a problem when the repositories are not organized and do not communicate with each other, further complicating the phase of searching for information within them;
– documents that are difficult to retrieve: if common practices for managing documentation are not established, each employee will have a personal, non-shared filing system that will make it impossible for other employees to search for such content on their own, and they will be forced to ask the person who created it each time, wasting time and energy;
– tacit knowledge: often companies have a large amount of tacit knowledge related to employees’ experience, that, in case of retirement or turnover, will be lost because it is not present in any document. This aspect can also represent a strategy on the part of the employee because, being the sole holder of such information, it becomes indispensable and irreplaceable. It is essential, therefore, that the corporate policy provides for the periodic codification of all information learned and detected;
– gaps in the documentation: if the information research produces no results, it might be for two reasons:
– the information is present but stored in a disorganized way: the employee does not know where to look for it or is doing it in the wrong place;
– that document does not exist.
If information is not accessible it is good to have certainty and understand the reason: in this way you avoid wasting time in duplicating existing information, or, on the contrary, you can fill the gap before it slows down the work of other employees.
Every enterprise search problem has implications throughout the company. For this reason, guidelines for organizing corporate documentation must be put in place so that all information can be structured clearly and precisely.
If this is not done, there is a risk that some cog in the “company machine” will get stuck, creating delays and problems.
The following are some of the negative effects that the problems listed in the previous paragraph can have.
– Delays in answers and problem-solving: searching for information within the documentation is fundamental to giving precise and accurate answers, especially to customers. The Help Desk area, for example, must be able to provide solutions to users’ problems in the shortest possible time, and this is only possible if the knowledge base is organized and easily accessible. Not being able to find the necessary information or, worse, finding that it does not exist would lead to delays in the request resolution, which can have potential impacts on both purchase and customer satisfaction.
– Communication problems: the difficulty in finding information can also create delays within the company. In fact, it often happens that different divisions draw on the same documentation or that one department produces content that is needed by another. An example is the Sales and Marketing departments, both of which focus on sales but are in different and related phases. For this reason, the documentation of one must be available to the other, to align with and reach their goals.
– Loss of information: Chaotic documentation does not allow for rapid research or the discovery of internal problems. This means that you will not have the opportunity to fill the gaps, and you will not know whether the documentation does not exist or has been misfiled.
After outlining the main Enterprise Search problems that companies face, let’s see how to solve them.
At the base of all this is necessary a good Knowledge Management strategy in which the company is called to set guidelines on the creation and updating of content by employees, establishing how and when to do it. Only an up-to-date Knowledge Base will allow the answers to be found.
Another key aspect, however, is the tools needed to ensure that this content can be easily queried and allows for quick, up-to-date answers.
To realize a good Knowledge Management strategy, tools are needed that allow to:
– ask questions in natural language: to speed up the research phase, it is useful to be able to query the company’s knowledge base by directly reporting the question we need to answer or that the client has asked. Without having to rephrase it or extrapolate keywords or tags from it, you save time and avoid the risk of using the wrong keywords. For example, systems like Google Enterprise Search retrieve information by taking advantage of keywords, so by asking a question there is the risk of receiving a long list of documents that contain the same keywords. Thanks, instead, to intelligent enterprise search (systems that combine AI technology, such as Machine Learning and Natural Language Processing) it is possible to leverage the potential of natural language as if communicating with a human;
– have fast and accurate answers: To be truly effective, searches within the knowledge base must be fast and allow employees to get, and consequently give clear and correct answers. This is simplified by a search that, as mentioned above, allows you to extrapolate the precise answer from the documentation. Thus, it will not be necessary for the employee to read pages and pages of content;
– have relevant and consistent answers: to solve the problem, you need an answer that is relevant to the question and contains the necessary information. Especially for customer service, it is critical that the answers are consistent, even if they are asked differently through different business channels;
– access to all types of content: A search cannot be limited to just a few types of content. In order to perform at its best, it is necessary to make the entire knowledge base available to the employee, of every content and format, in order to have all the essential elements to solve the problem at hand;
– discover the gaps: it is important to know if someone has searched for information without finding it, so as to become aware of the gaps in the knowledge base and fill them in time to avoid creating problems;
– have up-to-date content: what is the use of orderly and easily searchable documentation if the information in it is outdated? For this reason, the knowledge base must be continually updated, so that the answers can be provided by viewing the latest version of the content.
A good Enterprise Search strategy allows differentiation of the enterprise search experience according to the user who is performing it.
In fact, the way in which the results are used and the reference documentation from which the answers are extrapolated vary depending on the purpose of the search and the user who performs it.
There are mainly three types of Enterprise Search solutions: for customers,
for employees, for departments.
The customer experience has undergone various evolutions, in parallel with the technological and business changes that have emerged over time and that have undergone considerable acceleration in recent years.
In fact, the customer experience is not the same as it was 10 years ago, and every company is forced to keep up with the times, adapting to new developments and providing services that are increasingly tailored to users.
In fact, when customers have a problem or, more generally, need answers to their questions, they are no longer willing to make phone calls and wait a long time to speak to an operator.
Since we solve our problems every day with a simple online search, the same method must be applied by companies.
Customers prefer to solve their own problems, without having to go directly to the assistance or to an operator, and it is up to the companies to make available to the user the means to find such information.
In this way, the client can find the answers to the simplest requests with a self-service solution, lightening the workload for employees, who can focus on other areas of work.
As we have seen, employees search for a large amount of documentation daily, which is mandatory in order to do their jobs properly.
If this information is not easily accessible, it will be impossible for them to complete their tasks quickly, creating interruptions related to waiting time and long searches in scattered repositories.
Employees can search for information for two purposes:
– internal use: they search for internal company documents they need to continue their work;
– for customer service: they search for precise and accurate information they must provide to the users to solve requests or problems.
In both cases, time is of the essence and only with a good enterprise search strategy can documentation be found quickly.
In addition, an organized and easily accessible documentation system avoids wasting time, energy, and manpower, allowing employees to work smoothly and without interruption.
External communication is important, especially within divisions such as the Help Desk, where response and resolution times need to be minimized.
But even within the company, it is necessary to adopt practices and tools that enable fast and effective communication between departments.
The various areas within the enterprise, in fact, often work in a connected way, with intersecting steps that are binding on one or the other division.
For this reason, a good Enterprise Search strategy is concerned with simplifying this internal information sharing by organizing documentation and using tools that allow it to be consulted efficiently, ensuring fluidity in the working process of departments.
In fact, divisions often work closely together, and slowing down one division can cause problems for others, leading to inefficiencies in several areas of the organisation.
Documentation is the cornerstone of the company. Every decision made, every procedure, every protocol, etc. is based on internal and external information.
Since it plays such an important role, it is necessary to devise an enterprise search strategy, supported by tools that make it efficient.
Documentation that is difficult to consult is useless: not being able to provide the necessary information is as if it did not exist, leading the employee to create new information, wasting time and energy.
It is only by paying the right attention to the organization, establishing common practices for all employees and periodic document updates, combined with the use of knowledge management software, that it will be possible to implement a successful enterprise search strategy.
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Enterprise search solution as part of a knowledge management strategy The management of information in the company, which we have already dealt with in a previous article, allows you to do the job smoothly and without wasting time and resources. Company information must always be easily accessible to employees wherever it is stored.