According to a 2021 study by NewVantage Partners, the percentage of businesses reporting successful outcomes following the integration of big data and AI has almost doubled in the past half-decade, growing from 48.4% to 96%. The number of firms expanding their commitment to data has also grown – the study reveals that 99% of the surveyed businesses across sectors have invested in data initiatives. Statista's latest research highlights that the value of investments in big data has increased ten times between 2011 and 2021. This number is expected to reach USD 100 billion by 2026.

The implication is clear: businesses across sectors are aware that optimal data-harnessing can deliver great value. To achieve this, however, they will need to tap into the right technological framework.

Let's understand how this works within the context of the manufacturing sector.

Achieving responsible production

Conserving natural resources has emerged as a non-negotiable priority for businesses in the face of the growing climate crisis. According to experts, we are due to cross the point of no return within the next two decades if the necessary measures are not implemented on a large scale.

Against this backdrop, manufacturers the world over are endeavoring to switch gears to responsible production by adopting sustainable practices. Companies are now exploring greener alternatives to generate energy while focusing on resource and energy conservation. For instance, Welspun India, a leading home textile brand, has reduced its fresh-water consumption, modified processes to drive water heat recovery for energy conservation, and enforced strict Zero Discharge of Hazardous Chemicals (ZDHC) guidelines.

This is where Active Intelligence, the idea of creating in-the-moment awareness of the business through real-time information to trigger immediate actions, steps in. Manufacturers can use this tech framework to maximize the efficiency of their sustainability initiatives. By analyzing up-to-date, real-time information sourced froman extensive IoT-driven framework, Active Intelligence, for instance, can help companies to accurately calculate the rate of resource usage and depletion. It can also help them determine, in advance, the quantity of raw materials required to achieve the delivery targets that are subject to change in a volatile market landscape, especially in the post-pandemic era. The seamless workflows enabled by Active Intelligence improve the interactions and flow of data between manufacturers, distributors, and retailers for more accurate and efficient decision-making and demand projection.

The insights generated can also be used to minimize wastage while sourcing materials from the primary sector. Additionally, these insights can empower manufacturers to enhance the intermediate processes to ensure optimal utilization of non-renewable resources. The granular level of analyses enabled by adopting Active Intelligence can help companies come up with innovative strategies aimed at recycling the refuse to create divergent revenue streams – thus boosting their overall profitability.

Smart automation to augment product engineering

Traditional design procedures involve many levels of scrutiny and fault testing that are not only difficult to maintain manually but can also lead to human errors. Top manufacturers leverage the power of automation and analytics to overcome this challenge while optimizing the efficiency of product engineering generative design.

A vast amount of data is involved in the process – and the greater the volume, the more efficient the algorithm. Active Intelligence can help companies leverage dynamic content and logic through AI and ML to drive innovation while minimizing costs and time as well as eliminating errors from the production process.

For instance, a company designing a three-legged chair can feed a detailed design brief into generative design software. The Active Intelligence-powered AI/ML algorithms then come up with all possible configurations and, aligned with ergonomic constraints fed by engineers, produce the best set of solutions. Following the testing phase, the system finalizes the optimal solution.

Driving predictive maintenance

Machine breakdowns are costly affairs – not only because of the cost incurred to replace/repair the machine but also in terms of hours lost due to the operational disruption. What compounds the challenge is that, in the absence of the right technology, predicting equipment failure is difficult. As per a 2017 survey,70% of companies struggled to determine which machine or part needs maintenance, upgrade, or repair.

Active Intelligence can empower manufacturers to achieve this. Industrial machines generate huge volumes of real-time and historical data – which can be analyzed with AI/ML to predict and trigger proactive maintenance. In doing so, manufacturers can ensure peak performance and business continuity. Top companies such as Mitsubishi Electric, are already using intelligent and interconnected systems to drive predictive maintenance to minimize costs and downtime while augmenting productivity and responsiveness.

Adapting to the changing demands of the industry

While the pandemic is a one-off event, disruptions in the supply chain are not. Armed with the power of Active Intelligence, manufacturers can determine with precision how much further they should advance a delivery date in line with the delay in procuring the raw material.

Besides calculating how disruption will affect their operations, both in terms of time and finances, Active Intelligence can help businesses to determine the regions/markets where they can divert their supplies to – or source their raw materials from – in order to mitigate the negative effects on their unit economics.

For instance, Active Intelligence empowered Qlik customer Multipack, an Australian packaging services provider, to strategically scale up and down its operations in line with fluctuating demand cycle in the wake of the pandemic. By reducing the decision-making time from days to minutes, the platform helped the brand take just-in-time decisions to efficiently streamline its production processes.

using active Intelligence to eliminate operational bottlenecks and optimizing processes, industries can start tapping into the superior financial benefits while improving their ESG scores. To navigate the increasingly digital-first post-pandemic business ecosystem, enterprises across sectors will need the aid of technology to collate, combine, and analyze incredible volumes of information to make optimal business decisions swiftly – and Active Intelligence is the key to unlocking this capability.

Author

Varun Babbar, Managing Director, Qlik India