See the unknown, think of the impossible, & shape your tomorrow with Augmented Analytics

What you see is what you get. What you don’t see, gets you! 

This is exactly how the world of data is manifesting all around us with global data creation expected to grow beyond 180 zettabytes by 2025. If today’s data-conscious enterprises can access the right data at the right time to drive the right decision then success stories will be written. Else, data hidden in obscurity is just a ticking time bomb. 

Traditional Business Intelligence (BI), as we know, is the technology solution that generates insights leveraging data through dashboards and reports, but it served its purpose a decade ago and is not user persona centric. Often, users who adopt this technology solution are faced with underutilized reports and dashboards that are not quite actionable, thus creating disconnected BI and business outcomes. As a result, it ends up introducing business siloes, data discrepancies, and usage complexities for business decision-makers.  

Augmented analytics responds to this challenge by embedding artificial intelligence (AI) and machine learning (ML) into traditional BI. This provides the ability to augment data exploration and find meaningful explanations to insights before consumption. Integrating augmented analytics into an existing stack of analytical tools is easier than you think. Earlier, enterprises engaged exclusive skill sets to interpret data. However, augmented analytics is leveling the playing field for all users through these key features:

-It automates data preparation (i.e. data quality, enrichment, cataloging, and profiling) and augments the process of data discovery. Analysts can now invest more time in extracting deeper insights

-Analytical insights can be seamlessly embedded as part of enterprise applications such as enterprise resource planning (ERP) systems, customer relationship management (CRM) solutions, and support and productivity tools. This improves the adoption of analytics without additional effort

-Users are empowered to make data-driven decisions through contextualized insights rendered while they are executing an operational process

-Conversational interaction with the help of natural language processing (NLP) enables users to access insights, hassle-free

-Business users can now quickly understand outlier data points without the need for data scientist-like capabilities 

Contextualizing these capabilities to answer business functions’ need 

What makes augmented analytics revolutionizing is its capability to continuously learn and improve insights. Its smart recommendations can be absorbed across an enterprise to establish cross-functional alignment and accelerate decision making.

Customer Service: Every business treasures its relationship with its customers. Hence, it is no secret that delivering a superior customer experience is crucial for maintaining customer trust and loyalty. Augmented analytics is quickly gaining traction in helping customer service professionals proactively identify a customer’s intent and predictively track maintenance issues. These steps go a long way in improving a brand’s perception. Support channel operations can be streamlined by analyzing call volumes, sorting incoming requests, and directing them to appropriate bots or personnel. This reduces the wait time for customers to access the right solution. 

Sales: For a sales team, ML algorithms running in the background can sort through volumes of historical customer data to identify buying patterns and recommend ways to improve value delivery. Sales personnel can easily and quickly find answers to relevant questions like which micro factors are influencing a demand, how to analyze sales results for assigned territories, what are the key performance indicators (KPIs) to monitor for successful home runs, where lies the upsell and the cross-sell opportunities; this list could go on. Augmenting AI-led explainable answers to such questions will narrow down the key measures to be tracked by humans for continuous sales improvement. 

Marketing: Navigating the world of consumers is complex. It is ridden with emotions and influenced by competitions. And this doesn’t make the life of a marketer any easier. But with augmented analytics, a marketer can have better control over personalizing campaigns based on demographics and millennial preferences to create meaningful pockets of offerings for attracting and delighting a prospect. With faster access to granular insights on multichannel performance, marketers can focus on optimizing customer journeys. Further, they can work in tandem with sales teams to identify loopholes and target the right set of decision-makers.

Human Resources (HR): As one of the key supporting functions, an HR department is constantly up against the urgency to find the right talent for an enterprise. Augmented analytics can help in identifying HR challenges and suggest ways to address them. HR professionals can strategize on improving engagement, employee retentivity, and sieving through a large bunch of profiles to identify the right fit, without any requirement of in-depth analytics knowledge. Thus, injecting augmented analytics into decision-making can make time-consuming hiring processes nimble and improve candidate experience.

Finance: With ever-changing guidelines and regulations, locale-specific processes, and currencies, financial reporting can get painfully cumbersome and error-prone. Augmented analytics promises to improve financial processes by churning out insights on an internal financial environment while ensuring the accuracy of financial reports by considering non-financial data points and enabling continuous risk analysis. With automated customized reports, it is possible for users to perform deviation analysis to understand relationships between budgets and actuals. This will help businesses to stop revenue leakages. 

Supply chain: Sudden changes in market conditions and consumer preferences directly impact supply chain management. Moreover, integrating the internal supply chains with supplier networks has always been an age-old problem. Augmented analytics can smoothen the process links to create a digital community of partners. It allows a business to operate confidently by forecasting trends, predicting weather conditions, and optimizing route allocation to maintain uninterrupted deliveries of products and services. With better inventory management, supply chain planners can respond better to fluctuating markets.

Time to embrace the unknown

Humans are curious beings by nature. It is our innate necessity to discover spectacular solutions to new and existing problems. And augmented analytics adoption is a way to respond to such  a need for exploration. Today’s enterprises are living entities and augmented analytics is destined to make the human aspect of a business think, understand and act better. It is sculpting citizen data scientists out of business users. The future belongs to augmented consumers, augmented learnings, and augmented experiences. And the journey to visualize the unknown has already begun.

The article is authored by Venkat Ramasubban, SVP (Head- Data & Analytics), Enquero- A Genpact Company