One of the most challenging issues facing businesses today is employee turnover. According to the U.S. Bureau of Labor Statistics, the total separations rate in 2021 was 47.2 percent of U.S. jobs. Roughly 70 percent of those were voluntary, resulting in a tremendous, unplanned loss of both knowledge and experience.
Companies can minimize losses by creating information repositories. These can train and support new and existing employees. For example, you may have a field service engineer who specializes in one product line. By enabling them to work with others, you expand the flexibility of your workforce, making it easier to meet unexpected demands. There are challenges though, some include:
- It can be difficult to get buy-in from employees to build, maintain, and use the information repository.
- Building an information repository takes time and effort.
- Content quality can vary. For an information repository to be useful, content needs to be both clear and concise. It also needs to be accurate and kept up to date.
But how can organizations devote less time and energy to maintaining information repositories?
One tool that can help is cognitive services, which are a set of cloud-based APIs that offer AI capabilities such as:
- Vision: identify objects, detect faces, and read text.
- Speech: transcribe speech, translate languages, and use voice commands.
- Language: understand natural language and generate text.
- Decision: make predictions, identify patterns, and recommend actions.
Cognitive services help generate a more valuable information repository, from automating routine tasks to streamlining unstructured data sources.
- Extracting information from unstructured data: IFS uses cognitive services to extract information from unstructured data. Examples include text documents, images, and videos. We then add this information to the information repository. In doing so, we make it more comprehensive, valuable and save time.
- Organizing and structuring data: We use cognitive services to organize and structure data in a way that makes it easier to find and use. We do this by creating indexes, tagging data, and creating relationships between different pieces of data, making it easier to find.
- Making data more accessible: We use cognitive services to make data more accessible to users. We do this by creating APIs, developing chatbots, and creating other tools. These allow users to interact with the information repository in a way that is convenient for them enabling productivity and efficiency.
- Improving the quality of data: We use cognitive services to improve the quality of data by identifying and correcting errors. We do this via natural language processing. We identify grammatical errors, spelling errors, and other types of errors.
Cognitive services in manufacturing:
Over time, manufacturers create a lot of materials to support the products they make. These materials include manuals, brochures, white papers, and Q&A documents. In addition, the maintenance and repair services they offer generate both structured and unstructured data. The latter consists of service reports, images, and videos. By using cognitive services, IFS can go through this data and extract relevant information for your information repository. For instance, suppose a company has created a FAQ document that covers common issues and how to resolve them. Typically, FAQs have questions and answers paired together, one after the other. They may also contain links to other parts of the FAQ or even external websites. IFS Cloud can crawl through the FAQ, extract and categorize the questions and answers, and incorporate any linked data that is relevant to the results.
Of course, collecting and organizing the data into a repository is only the first step. Equally important is making it quick and easy for users to find the information they need. IFS usescognitive services in three ways to present an ideal user experience:
- We use natural language processing to understand the meaning of users’ questions. This provides the context that we use when searching for answers. It also makes it easier for users, as they can ask questions in whatever way is natural for them.
- We use machine learning to infer the relationships between different pieces of information. This helps us improve the relevance of the search results we return.
- We use text analytics to extract key terms and concepts when building the repository. This makes it easier for users to discover the information.
It’s no secret that employee turnover rates are at an all-time high, leaving companies with the daunting task of rapidly onboarding new hires to keep up with the demand for their products and services. And with the rise of remote work, the challenge only becomes greater. By using IFS’s cognitive services and leveraging structured and unstructured data, IFS’s information repositories offer a centralized location for organizing and collecting information. This, combined with the power of cognitive services, creates an unparalleled user experience, making it easy for employees to find the answers they need quickly and efficiently.
SOURCE: Andrew Lichey. (2023.November 20). Generating and Using Information Repositories to Support A Changing Workforce. IFS Blog. https://blog.ifs.com/2023/11/generating-and-using-information-repositories-to-support-a-changing-workforce
