Mar 2, 2020 the future of manufacturing with enterprise AI

Georgia Wilson
3 min logo helps leading manufacturers address core manufacturing goals with the use of enterprise artificial in... helps leading manufacturers address core manufacturing goals with the use of enterprise artificial intelligence.

By integrating data from enterprise systems, operational sources, sensor networks and external providers, uses this information to power machine learning models, to generate predictive insights for the manufacturing industry. As a result the technology increases a company’s throughput, supply chain efficiency and service revenue.

Applications for the manufacturing industry

C3 inventory optimisation

Using advanced artificial intelligence, machine learning and optimisation techniques,’s inventory optimisation technology reduces a manufacturers inventory levels, while ensuring that they still have stock when and where it is needed.


  • Real time recommendation, time monitoring and data

  • Ability to specific maximum acceptable risk of stock-out for parts

  • Summary views

  • View, compare and benchmark individual parts and suppliers

  • “What if?” scenario planning 

  • Individual optimisation and scalability of parts and inventory levels

C3 inventory optimisation demo video:

C3 predictive maintenance

Using advanced machine learning,’s predictive maintenance technology provides maintenance planners and equipment operators with comprehensive insights for asset risks. 


  • Access to real time asset health 

  • Asset failure prediction algorithms 

  • Asset risk management across entire portfolio

  • Diagnostics and projection 

  • Ability to track, benchmark and rank performance

  • Comprehensive closed-loop workflow and coordinated alerts and notifications

C3 predictive maintenance demo video:


C3 energy management 

Also using machine learning, AI and optimisation algorithms,’s energy management technology helps company’s gain energy expenditure visibility, as well as the ability to prioritise actions to reduce operational costs.


  • Streaming analysis of energy

  • Peak demand forecasting

  • Ability to analyse end use disaggregation

  • Complete optimisation

  • Ability to detect anomalies

  • Alerts and recommendations to improve operations

  • Tracking and reports 

  • Ability to maximise finance 

  • Real time analytics

  • Integrate data from multiple sources to drive high value insights

C3 energy management demo video:

C3 sensor health

Using advanced machine learning,’s sensor health technology integrates and analyses data from multiple systems to ensure IoT devices and network infrastructures are operating effectively during the deployment and the operational life cycle of the devices.


  • Executive dashboard

  • Ability to identify deployment issues, malfunctions, forecast future deployment progress and optimise field service

  • Ensure installation data is correct, consistent and current

  • Reporting and analysis

  • Ability to visualise planned deployments, actual deployments, provisioning progress and issues


By applying advanced machine learning and AI,’s CRM technology provides its users with a real-time predictive customer relationship management (CRM) application to drive operational excellence.


  • Improved revenue forecasting accuracy, in near real time

  • Recommended best actions for sales representatives

  • Predictive lead quality and lifetime value 

  • Ability to leverage geolocation and mobile device data for timely and accurate recommendations

  • Analyse and monitor performance

To find out more about’s enterprise AI services for the manufacturing industry head over to the website.

For more information on procurement, supply chain and logistics topics - please take a look at the latest edition of Supply Chain Digital magazine.

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Jun 21, 2021

Pandora and IBM digitise jewellery supply chain

2 min
Jewellery retailer Pandora teamed with IBM to streamline supply chains as sales of hand-finished jewellery doubled across ecommerce platforms

Pandora has overhauled its global supply chain in partnership with IBM amid an ecommerce sales boom for its hand-finished jewellery. 

The company found international success offering customisable charm bracelets and other personalised jewellery though its chain of bricks and mortar retail destinations. But in 2020, as the COVID-19 outbreak forced physical stores to close, Pandora strengthened its omnichannel operations and doubled online sales. 

A focus on customer experience included deploying IBM’s Sterling Order Management, increasing supply chain resiliency and safeguarding against disruption across the global value chain.

Pandora leverages IBM Sterling Order Management as the backbone it its omnichannel fulfilment, with Salesforce Commerce Cloud powering its ecommerce. Greater automation across its channels has boosted the jeweller’s sustainability credentials, IBM said, streamlining processes for more efficient delivery. It has also given in-store staff and virtual customer service representatives superior end-to-end visibility to better meet consumer needs. 

Jim Cruickshank, VP of Digital Development & Retail Technology, Pandora, said the digital transformation journey has brought “digital and store technology closer together and closer to the customer”, highlighting how important the customer journey remains, even during unprecedented disruption. 

"Our mission is about creating a personal experience and we've instituted massive platform changes with IBM Sterling and Salesforce to enable new digital-first capabilities that are much more individualised, localised and connected across channels and markets,” he added. 


Pandora’s pivot to digital 

The pandemic forced the doors closed at most of Pandora’s 2,700 retail locations. To remain competitive, it pivoted to online retail. Virtual queuing for stores and virtual product trials via augmented reality (AR) technology went someway to emulating the in-store experience and retail theatre that is the brand’s hallmark. Meanwhile digital investments in supply chain efficiency was central to delivering on consumer demand. 

“Consumer behaviour has significantly shifted and will continue to evolve with businesses needing to quickly adapt to new preferences and needs,” said Kareem Yusuf, General Manager, AI Applications and Blockchain, IBM. “To address this shift, leading retailers like Pandora rely on innovation to increase their business agility by enabling and scaling sustainable supply chain operations using AI and cloud.”

Yusuf said Pandora’s success was indicative of how to remain competitive by “finding new ways to create differentiated customer experiences that protect their enterprises from disruptions to help mitigate risk and accelerate growth”. 

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