How MECBot’s Knowledge Graph Helps CXOs Make the Right Decisions Just-in-time
2023-02-27 05:53:12
Need for Augmented Analytics
The scope of business analytics has been growing by leaps and bounds, and by now, artificial intelligence (AI) has made its inroads into the boardrooms of businesses of all sizes across diverse sectors. However, there is a catch.
To elucidate this, let us take an example - let’s say your sales grew by 20% last year from the previous year. Now, this information in itself is meaningless without the right insights. What factors have has caused this increase? Is this your average growth rate? - which probably means you didn’t accomplish anything extraordinary. Is this an industry trend? - which again means you are just another player in the market. Is this unprecedented - not just in your firm but among your competitors? - Kudos! But how would you repeat it? As soon as any of these possibilities are extracted as insights, these insights would then have to be converted to goal-oriented business decisions.
So, where’s the catch?
The challenge today is that existing algorithms are still neither fully automated nor seamlessly integrated with the business. Getting data on its own feet without continuous intervention by a data scientist and without the cushion of expensive IT infrastructure is the real challenge - and rightly so. According to the Mckinsey Global Institute, the U.S. economy alone would face of shortage of 2,50,000 data scientists by 2024*, not to mention that they are also expensive. Even if you have a data scientist on board, he will still have to waste 80% of his time on cleaning the data to make it analysis-ready. Last but not the least, since data modelling and storytelling with insights continues to be human-driven, the process remains susceptible to manual errors and errors due to human bias.
Luckily for us, AI is one of the most dynamic sectors, challenging itself and evolving everyday.
So, what’s brewing in the kettle?
Augmented Analytics - Explained
Gartner’s report titled, ‘Augmented Analytics Is the Future of Data and Analytics’, published in July 2017 established ‘augmented analytics’ as the anchor of future machine intelligence. Simply put, augmented analytics is the next-gen intelligence delivery model running on mature platforms that automate and integrate activities like cleansing the data and making it analysis ready, detecting data patterns and layers, correlating with business ontology and workflows, creating models around data clusters, and deriving insights from the models for easy digestion by decision makers - all in a plug-and-play format without the need for supervision by a data scientist.
Accordingly, augmented analytics works on your business at 3 different levels: Smart Data Discovery, Augmented Data Preparation and Actionable Analytics.
FORMCEPT’s Augmented Analytics Solution - MECBOTPlus
Our latest innovation MECBOTPlus is an augmented analytics product that seamlessly combines authentic and comprehensive smart data discovery with auto-visualization of data patterns. The establishment of logical patterns then lead to the extraction insights (both predictive and diagnostic) which are automatically fed into an easily retrievable pipeline. To make these insights actionable, powerful search algorithms and comprehensive human-language query are the mainstay of our cutting-edge analytics solutions. This, combined with business workflows and domain intelligence is a revolutionary decision-making tool for any business. Further, natural language narration may come into play for contextual storytelling.
Use-cases of MECBOTPlus
1. Target Beneficiary-BFSI companies, for example, ICICI Bank & Standard Chartered Bank
2. Target Beneficiary: Insurance Companies - for example, AXA, MetLife & Zurich Insurance Group
Example from a Recent Project:
FORMCEPT has validated MECBOTPlus with one of the leading online insurance policy comparison platforms in India.
- Our solution builds insights from text data derived from voice data that is generated when customer service agents handle customer queries. Identification of policies is also done from chat data when agents response online to customer chats.
- The top policies mentioned in the overall conversation data are then clustered by time, top trends and ngrams (phrase variations) are detected over over time excluding the noise, Intent Analysis is carried out based on the data collected and processed, and other features are loaded on top of it, such as chat statistics like total chats, average chat segments, conversation ratios, along with a fully functional keyword search around the policies - i.e. to identify the respective chats in which a searched policy has occurred.
This application is highly useful for Business Executives, Agent Leads and Business Managers to understand the various analysis around the customer queries, agent service, response time, product performance, policy analysis, and overall effectiveness of agent response.
Concluding Note
Augmented Analytics is not just a new technology - but a new paradigm in the making. It is intended not just to mimic but to internalize the intelligence of a data scientist and the contextual awareness of a CXO. FORMCEPT is poised to be a front-runner in this domain by taking the lead in embedding enterprise-scale augmented analytics solutions into highly mature platforms that users can plug-and-play for accurate insights and decision-making on the go. To know more about what we do, our range of products and how we can help you, please visit www.formcept.com.
