Data analytics: How data-driven decision-making is transforming organisations

Published: December 5, 2018 1:09 AM

Robust enterprise-wide data analytics capabilities help organisations develop new products and services or optimise existing ones, utilise assets better, increase operations efficiency and improve customer experience.

Virtual personal assistants and automated data analysts are a few similar examples that leverage big data and analytics solutions.

By Sudipta Ghosh

Technological breakthroughs, together with a global shift in economic power, are reshaping businesses and accelerating change around the world. Advanced analytics and machine learning—which once seemed like futuristic solutions—are increasingly available and accessible to businesses.
PwC’s recent Global Data and Analytics Survey involved the participation of more than 2,100 global executives and more than 100 Indian executives, ranging from C-suite leaders and departmental heads to managers and analysts. The results suggest that Indian organisations are more confident about the future as 83% of the respondents felt that the changes would be gradual, as opposed to the global figure of 66%.

Usage of advanced analytics such as predictive and prescriptive analytics in organisations to support decisions was associated with greater certainty and optimism among Indian executives with respect to their next big decision and its likely impact. Cost reduction and market share gains are the big focus areas for Indian firms while leveraging advanced analytics solutions.

In the future, analytics-driven applications will know consumers so well that they will be able to look beyond their usual preferences and discover new ones. Millennials are already attuned to this trend: They expect more than customer service assistance and are looking for bots to make entertainment recommendations. According to PwC’s Bot.me report, more than half the respondents (55%) said they would be open to their media list being curated heavily or even completely by a recommendation engine. Virtual personal assistants and automated data analysts are a few similar examples that leverage big data and analytics solutions.

Advanced analytics and machine learning techniques help companies to complement human instincts and experience to make better decisions and gain a competitive edge. Within an organisation, HR, sales and marketing, finance and manufacturing operations functions are seeing a huge shift in the way they operate with the advent of data-driven decision making using advanced analytics. From an employee perspective, several of the organisational processes are being impacted by advanced analytics.

People analytics solutions are helping the HR function to proactively plan a strategic workforce for the organisation, use data-driven inputs during hiring, predict frauds and identify the training needs across levels. Organisations are no longer making instinct-based hiring decisions but are using several data points and advanced forecasting techniques to model future demand for talent and skills based on business growth forecasts. Using advanced statistical techniques, attrition risk is predicted, which in turn is used to predict the expected tenure for each of the prospective candidates.

Advanced analytics is also being leveraged to analyse employee data and identify possible incorrect practices or non-compliant individuals. Predictive analytics is being used to profile an employee and design training programmes for various identified segments. This, in turn, will help companies achieve higher employee satisfaction.

Sales and marketing analytics solutions are using internal and external data to perform customer segmentation, recommend products, increase customer lifetime value (CLV) and design personalised marketing campaigns. Analytic solutions use predictive and prescriptive modelling techniques which are capable of capturing various decision-influencing factors and their interconnections, and uncovering hidden relationships. Developing customer clusters and customising marketing and sales strategies accordingly helps organisations plan better marketing campaigns and optimise the marketing spend. Increasing the customer’s cart size by making meaningful product recommendations helps increase the ROI on marketing spend for the organisation. Calculating CLV and focusing on retaining high-value customers help increase the average customer spend from this segment and increase profitability.
Manufacturing analytics solutions like predictive asset maintenance (PAM), warranty analytics and demand-driven forecasting techniques are transforming operations, and improving the quality and efficiency of various manufacturing processes. PAM helps to accurately predict events that could cause outages and to run assets at peak performance. The solution helps to boost uptime, performance and productivity while lowering maintenance costs and the risk of revenue loss. A warranty analytics solution integrates warranty claims with key customers, products and geographic information; detects issues earlier; and reduces time to correction. It also lowers warranty costs and increases customer satisfaction, enabling improved product quality. A demand-driven forecasting solution drives consensus forecast in conjunction with the sales and operations planning (S&OP) process. Analytics solutions generate unbiased and accurate forecast and help to improve forecasting accuracy across product hierarchy, reduce finished goods inventory and stock-outs, and enhance accuracy with forecast-value-added (FVA) and reporting.

Several government data and analytics solutions are also being designed to improve the revenue realisation and efficiency of service delivery to citizens. Widening the tax base and increasing compliance have always been the goal for revenue-earning departments like state tax departments which are responsible for levy of indirect taxes across various businesses. Tax analytics solutions that link data from multiple sources to provide a 360-degree view of transactions help in identifying patterns and trends. A risk-based approach is adopted to identify and categorise high-risk businesses based on specific metrics. The tax department’s process of selecting businesses for audit has been completely transformed by the tax analytics solution. A citizen dashboard with sentiment analysis helps government departments to gauge citizens’ views on various public issues, to analyse trends on key topics like education and health, and highlight areas of improvement for concerned government officers.
Robust enterprise-wide data analytics capabilities help organisations develop new products and services or optimise existing ones, utilise assets better, increase operations efficiency and improve customer experience.

Ghosh is Partner and Leader Data & Analytics, PwC India. Himanshu Ghawri, Director -Data and Analytics, PwC India also contributed to this article. Views expressed are personal.

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