Process Intelligence involves tools and techniques that deep dive and map out processes, to help organizations identify bottlenecks and improve operational efficiency.
By monitoring and analyzing processes on a historic or real-time basis, Process Intelligence software provides accurate data on work items, people responsible, duration, average wait time and typical bottleneck areas. PI is very useful for managing nonlinear processes with multiple dependencies.
Process Intelligence components
Discover and Automate Mundane Processes
Ensure Business Process Transparency
Undertake Process Simulation & Cost Optimization
Process modeling is a detailed, end-to-end graphical visualisation of all the tasks in a business process. It allows every process to be examined in-depth, so as to understand the workflow and find areas for improvement. The key takeaway from process modeling is defining business objectives and mapping processes to accomplish the same.
By streamlining the process & removing bottlenecks, process modelings help employees save time and increase productivity
There is a clear overview of entire processes, from start to finish, with all the steps mapped out
Ensures best practice
Using process models ensures consistency and standardization across the organization
Better understanding & communication
A common language and template for processes makes it easier for users across the organization to communicate with each other
Process modeling supports the coordination of people, systems and information across the organization to support business strategy
Process automation goes beyond conventional data manipulation and record-keeping activities to automate complex business processes and functions. PA uses advanced technologies and tools to automate regular, event-driven, mission-critical, and core processes. Focussing on ‘run-the-business’ processes, automation removes or reduces human inputs, achieves greater speed of delivery, higher quality, decreased errors, lower costs and simpler processes.
Customer Support Software
Receives Customer Complaint
Sits in the common inbox waiting for the executive to retrieve process
Integrated Project Management Software + Customer Support Software
Receives Customer Complaint
Automatic forward to Customer executive in charge
Process mining analyzes, monitors, and optimizes business processes, by using algorithms to extract knowledge and develop insights from existing data sets. This information significantly increases a business’s ability to spot inefficiencies, re-engineer, and deploy targeted training to run the business effectively.
Task Mining is the technology that leverages Optical Character Recognition (OCR), User Keystores system functions and machine-learning algorithms, to capture desktop interactions and find relevant actions that impact business outcomes. It helps businesses understand how their people are getting work done and how to optimise it.
Task Mining combined with process mining gives the fullest picture of how processes run, including those steps which are not captured in conventional logs
Frees up valuable human workforce time for more human intensive productive tasks
Ensures governance and compliance to minimizing organization risks
Human-BOT synergy and provide end-to-end visibility of activities and customer journeys
Automation is the creation and application of technologies to produce and deliver goods and services with minimal human intervention. Automation frees up employees from routine & repetitive tasks while improving the efficiency, reliability, and speed of many business processes.
Represents brand’s quality and speaks the brand language consistently
Combats customer churn by providing a robust customer experience
Seamless systems integration enables and empower front line teams to serve customers better
Robotic Process Automation
Robotic Process Automation
Robotic Process Automation is a productivity tool that can mimic or emulate selected tasks (transaction steps) within an overall business or IT process. These may include manipulating data, passing data to and from different applications, triggering responses, or executing transactions. RPA uses a combination of user interface interaction and descriptor technologies and can be overlaid on one or more software applications.
Today Ennuviz has successfully implemented RPA to a great extent in both general business functions like HR, Finance, IT, Governance, Risk & Compliance as well as for Industry-specific processes.
Banking & Financial Institutions
Purchase orders & invoice management
Insurance Provider management
Intelligent Process Automation (IPA)
Intelligent Process Automation (IPA)
While RPA deals with specific tasks, IPA refers to a set of technologies that combine to manage, automate and integrate digital processes. These primarily include Digital Process Automation (DPA), Robotic Process Automation (RPA) and Artificial Intelligence (AI).
IPA represents the huge shift to fully automated technologies like driverless cars and autonomous drones. In business, IPA is transforming customer interactions and workflows through automated tools like desktop assistants for example. IPA works in this space, helping organisations digitise their operations and deliver services in an automated world.
Intelligent Decision Engines are transforming the way businesses take decisions by automating the decision making process. Decision engines evolved from traditional complex rule models to Ai powered platforms that recognise patterns and provide valuable insights to business leaders.
In the automation context, Intelligent Decision Engines help automate processes which need some human decision making like processes like Email Classification, Document Classification and Dynamic Case Routines.
Today they find widespread use in industries like Insurance and retail lending.
Intelligent Decision Engines bring speed & scale to operations while providing valuable data inputs for business analytics.
Conversational AI refers to the technologies that power automated messaging and speech-enabled applications. Conversational AI employs Automatic Speech Recognition (ASR), Natural Language Processing (NLP), Advanced Dialog management, and Machine Learning (ML) to recognize speech and text, understand intent, decipher different languages and respond in a human-like way.
The quality of Conversational AI tools is critical, as it is often the first or only customer touchpoint for most brands. If the service delivered falls short, companies risk losing a prospect or existing customer within minutes.
Ennuviz uses the latest tools and the art of conversational design to create responsive, 24x7, seamless and personalised customer experiences, that lower cost and power service focussed businesses to increase customer retention
Conversational AI components
Represents the brand’s quality and speaks the brand language
Increases website engagement and customer conversion
Generates better quality of leads
Combats customer churn by providing an enhanced customer experience
“May I help you” is a prompt we often see when browsing sites. This automated customer service technology is simply called a ‘Chatbot’. Chatbots can guide users to their end goal with little or no effort from the user. Today, chatbots are deployed widely across customer touch points.
Ennuviz helps design intuitive and intelligent Chatbots using a mix of AI and Natural Language Processing tools.
Chatbots that follow pre-designed rules to answer queries.
A more evolved option, where the bot automatically learns and understands after an initial ‘training’ period.
Used for Sales and Development, these bots manage simple, real-time chats.
Most companies are saddled with legacy Interactive Voice Response (IVR) systems. Studies have shown that IVRs offer an unwieldy and frustrating customer experience, to the extent of losing customers permanently! Temporary fixes like Automatic Speech Recognition too fail the test after a point.
Voice bots are an optimal solution to remove the niggles of IVR, by overlaying AI-powered software that removes the need to listen to long menus and press numbers on a keypad. Voice bots simulate the experience of talking to a live operator and guide the caller to their desired outcome. Voice bots use Machine Learning to continually improve and deliver a better customer experience.
83% of customers avoid a company after a poor experience with an IVR
- State of IVR, 2018
Provide modern, quick and personalised customer care with Intelligent Virtual Assistants (IVAs). IVAs use conversational AI to replicate the experience of talking to a person, and do better as they can hear and record customer details accurately, even with background noise, accents or poor connections.
IVAs are important customer service touch points as they help disseminate the brand message to consumers. Companies use IVAs to help understand customer intent and extract insights on brand-specific jargon or keywords that customers use in their natural speech.
With IVAs brands enjoy the ability to personalise an automated solution, while getting valuable customer data inputs.