Overview

Enterprises are realizing that data and analytics are critical for business with IT being the key enabler. Rather than struggle with dated reports that provide no actionable insights, they are now looking at analytics to gain insights into customer behavior, improve order-to-cash cycles, and generate new revenue streams. With this perspective, enterprises are seriously considering hybrid architectures to address their complex business challenges.

At Infosys, our transformative service offerings help our customers achieve their business goals by:

Providing an effective data and analytics strategy with clearly defined business benefits
Using embedded artificial intelligence (AI) to accelerate and optimize business processes
Leveraging AI for augmented intelligence and process acceleration
Increasing operational efficiency using a combination of agile methodology and automation
Creating next generation architecture for scaling analytics use cases and data management

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The Infosys Data Management and Analytics solution suite is built upon four pillars:

Data estate modernization
Applied AI
Data management and governance
Business planning and financial consolidation

We provide new-age analytics solutions and services to customers through the Infosys Live Enterprise Suite. This enables customers to achieve greater agility, higher productivity and zero latency in processes.

The Infosys Live Enterprise Suite enables:

Process intelligence – embed intelligence components (AI / ML) in the core
Intelligent platforms – infinite scalability with poly-cloud and data fabric for seamless integration of data
Knowledge graphs – helps seamlessly map information across organizational silos in near real-time
Digital brain – helps capture and analyze enterprise ecosystem data using machine learning, deep learning, and automated reasoning

Challenges & Solutions

Inability to take advantage of increasing data due to disconnected systems and ineffective data management

Infosys Data Management and Governance solution helps organizations transform their analytics landscape and integrate their data by leveraging best of breed capabilities from SAP and hyperscalers. We work with enterprises to create a data lake ecosystem that enables data democratization and brings agility in analytics value delivery. This has resulted in improved customer satisfaction and enriched customer experiences.

Overstocking leading to inventory ageing, and understocking leading to lost sales

Infosys Predictive Inventory Management solution helps enterprises identify and take proactive action for two major business challenges:

overstocking leading to ageing and waste
understocking leading to lost sales

The solution leverages machine learning, and point-of-sale and shelf data to predict ageing of inventory across multiple stores.

Lack of transparency in supply chain leading to product spoilage and losses

Infosys Supply Chain Management solution was developed using SAP Leonardo, blockchain and IoT services. The solution helps resolve several issues related to perishable goods in the supply chain. It also helps reduce food decay during transportation and increases the reliability of products for customers.

Transforming years-old systems and ensuring data quality across multiple systems to support 360-degree view

Enterprises running on obsolete systems need business and analytics transformation more than ever before. Infosys has devised a new system for such enterprises to provide them with a 360-degree view of their data. With advanced analytics, we help business users make informed business decisions faster. Our Data Estate Modernization solution helps enterprises improve their overall system performance with a holistic and unambiguous view of their data.

Ineffective planning and pricing processes

Infosys Financial Planning solution helps enhance the pricing process. Finance and sales teams rely heavily on the pricing process to collaborate and report progress. The solution enables group-wide standardization of the financial planning and pricing process, thereby reducing overall planning time. This enables enterprises to shift focus from data management to business analysis.