Every consumer and business user loves the new world of search and query. Google-type searches offer the ability to ask a question in simple form, and receive an answer you can understand. You don’t have to be a data scientist, a rocket scientist, a statistician or a data guru to perform the search or to understand the results!
Gartner predicts that ‘… augmented analytics will be ubiquitous, but only 10% of users will use it to its full potential.’ One of the primary reasons that augmented analytics is not adopted and leveraged to its full capacity is that the business chooses a solution that is not easy enough for team members to adopt – one that is restrictive, inaccessible or requires sophisticated skills.
Every business owner and manager understands the problem of limited resources. Today, you have fewer team members and you must do more to compete in the market. To enhance productivity and collaboration and ensure that every team member is making better decisions, it is wise to implement augmented analytics within your organization.
If your business is trying to incorporate data analytics into the fabric of day-to-day work, you will need to get your users to adopt analytical tools. The way forward is not all that complicated. The solution you choose must take an augmented analytics approach, one that includes simple search analytics, ala Google search. Natural Language Processing (NLP) and NLP Search tools are key to this approach as they allow business users to ask simple questions and get answers. If a user does not have to create complex queries or look to business analysts or data scientists or IT professionals, that user can incorporate data into information sharing, reporting, presentations and recommendations to management.
Your senior management team has decided to engender digital transformation and improve data literacy across the enterprise. As a primary step in this process, the team wants to implement an augmented analytics solution that will encourage business users to get involved in data analytics, to use data to make fact-based decisions and to present, report and collaborate using real, current and clear information that will support collaboration and improve results.
Smarten announces its Smarten Clickless Analytics, a Natural Language Processing (NLP) Search Analytics tool designed for every business user, no matter their technical expertise or data skills. Natural Language Processing Search Analytics (NLP) is an easy-to-use search analytics technique that allows business users to create complex searches without endless clicks and complex navigation and commands. Using this familiar Google-type Clickless Analytics, users can leverage these tools to discover trends and patterns, receiving results in simple, clear language the user can understand.
You have selected an advanced analytics solution and deployed it across your enterprise, but your business users are not cooperating! One of the primary reasons for poor user adoption of this type of tool is that the tools are too restrictive and too difficult to use. Perhaps IT created the dashboards and they do not meet the needs of your business user, perhaps the business user needs help to engage with the system. Your users may have tried their best to use the system but the results they receive when they search are not accurate or do not meet their requirements. An advanced analytics system that is not intuitive, is complex or requires programming skills just to perform a simple search is not going to work for your business.
Your business users probably fight you on improving data literacy and on implementing digital transformation. Many business users have a fear of analytics and envision having to become a business analyst or a data scientist in order to fulfill the vision of the business and its Citizen Data Scientist goals.
If your business wishes to enable Digital Transformation, it must create a roadmap to achieve results using new or modified technologies, streamlined workflow and processes that will leverage these technologies to enhance information sharing and ensure a consistent, uniform approach to business objectives and goals. It must also encourage and advance Data Literacy within the ranks of its teams. Why is data literacy important?
