How AI Powered Chatbots Simplify BI and Analytics Adoption for Decision Makers
With the rapid evolution in the field of Business Intelligence, making information more available, usable, understandable is an exercise to simplify the end-user experience. Today, most of the data is in bulk, it is not an easy task for the managers and executives to process.
In the current scenario, organizations are considering data as one of their essential assets and – if it is used wisely, then it will provide profits to all parts of the business from- financial planning to the Sales & Operations, HR, etc.
Presently, many organizations are having some sort of business intelligence/analytical applications or initiatives that takes your organization to different stages of maturity.
In the present scenario, the actual usage of chatbots is not very high. According to a survey by Gartner, Inc- 70 to 80 percent of business intelligence initiatives end up failing. And the main reason behind the low adoption rates of BI is bad user experience. Presently, BI platforms are equipped with more advanced analytics features, but they lack in providing an easy-to-use interface that gives meaningful and actionable insights.
Essentially Business intelligence is a self-service platform where employees need to access the BI systems to- download reports, filter data, switch different apps, go through multiple reports, etc. But the non-friendly experience of tools makes employees reluctant to use them for everyday decision making.
Key reasons why Chatbot initiatives fail
1. “The last Mile of Analytics” - In tech terms, the point at which users interact with analytics is known as the “Last Mile.” The entire concept is crafted to illustrate the importance of this strategically critical thought process.
Does the ‘Last Mile’ of analytics matter? In the field of analytics, where adoption typically falls off. Despite data visualization in business intelligence and analytics is vastly improving, adoption is still too low — according to Gartner’s survey. If organizations are serious about becoming data-driven, they need a lot of focus. Because, business people need timely, relevant, actionable data insights to succeed in their roles.
2. The efforts involved in finding out the right data/ insights for decision making is high. In many cases, the business user has to travel through a maze of applications, charts, select different filters to come up with the insight to take action, and in that situation, they make a gut-feel driven call, or they ask someone else to find out the data/ insights for the applications- leading to the manual point of failure.
So, how about a virtual assistant- which travels across different applications and charts and come up with the right insight at the real-time without a chance of a manual error and having no vested interests.
Improve BI and analytics adoption with AI chatbots for better decision making
80% of businesses want chatbots by 2020, Before using a chatbot, one should know the hallmark of a true AI-Powered chatbot. Today, businesses are changing dynamically, and most of the chatbots are rule-driven -where you have to code the instructions consistently at the backend. Hence, you require truly smart machine learning-driven bots that learn the different scenarios and easy to use.
Chatbots help to deliver on all these points — here’s how you can boost the BI and analytics adoption with AI-powered chatbots.
# AI for Everyone
A data-literate world is a key part of the vision, and AI plays a significant role in making analytics accessible to everyone. AI as Augmented Intelligence – combining, not replacing, human intuition with the power of machine intelligence. It brings together two revolutionary technologies: Associative engine, which uniquely supports exploration by understanding the relationships among data values across all sources; and secondly, Cognitive Engine, which suggests new insights to explore based on the data set and user-defined search criteria.
The result is a powerful collaboration between human and machine intelligence, surfacing insights that would otherwise have gone undiscovered.
# Conversational Analytics
Experience gives enterprises a faster and easier way to ask questions, generate insights, and make data-driven decisions. It can be readily accessed through the popular collaboration of tools like slack, skype, Microsoft teams, etc.
Natural Language Processing (NLP) automatically trains itself and delivers insights for not only what is happening, but also why – and where to go next. Insights include interpretations, auto-generated charts, period-over-period calculations, key drivers, predictions for measures, and even comparative analysis. Users can set alerts for KPI thresholds, share and collaborate conversationally, and even interact using voice integration.
# Secured, Multi-device deployment, and a helpful assistant
AI-Powered chatbot secures data through features such as user authentication, authorization, encryption, and access controls. The AI chatbots are available and functional on multiple device types, including laptops, desktops, mobile phones, and tablets. It must also support different operating systems such as Windows, iOS, and Android.
Chatbots act as helpful assistants to users to eliminate the need to visit BI tools and undergo sophisticated navigation flows. The easy-to-use conversational interface of bots enables users to get data by asking one question at a time.
Therefore, AI-Powered Chatbots make the purpose of a self-service BI a reality and give the much-needed element of speed to decision-making. This element of speed combined with easy and hassle-free access to multi-format data anywhere and at any time offered by chatbots make them an ideal solution to boosting a BI and analytics user adoption.
Henceforth, if you have invested a lot in chatbots, then-Chaplin AI, powered by Polestar Solutions is the one link that can help you to leverage the entire investment. So, if you’re serious about becoming a data-driven organization.
Chaplin-AI offers great potential to improve BI and analytics. Not only can it help raise adoption rates, but it can help all enterprises to become more data literate and make smarter business decisions.