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Industry Recovery – Digitization against the Crisis

Every industrial crisis ends at some point. Even if it seem to be endless and unique at that moment. 

Throughout history, industrial companies have always reacted quite similarly to crises. In the current crisis, however, companies also have a whole new range of data-based tools at their disposal.

These new tools not only enable better forecasting, but also provide better protection for employees, customers and partners. The current generation of industry managers may be largely inexperienced in dealing with economic crises, but they undoubtedly have experience in handling data and digital tools. And it is precisely these applications that will be the key to getting the economic aspect of the current crisis under control.

How can Big Data support industrial companies in the fight against COVID-19?  

There are some examples of data-based answers:

  • Remote asset monitoring/remote maintenance of machines and plants:
    Just because employees are no longer allowed to be on site does not mean that their work does not have to be done. In order to prevent breakdowns of machines or entire industrial plants (which would only make the crisis worse), the need for remote monitoring and remote maintenance solutions is increasing.
  • OT (Operational Technology) Security:
    Remote monitoring and remote maintenance offer a larger target for threats and the topic of OT-Security is becoming increasingly relevant.
    Downtime/quality investigations and Condition-Based Monitoring: Industrial plants currently know only two extremes: Either they are running at full speed or on an absolute low flame. Plants that are running at full speed are being used to their capacity limits more than ever. This increases the risk of a breakdown.
  • Fleet monitoring and troubleshooting:
    Trucks sometimes deliver vital products. Fleet management has thus become systemically relevant, and errors lead to much greater problems than before the crisis.
  • Supply chain optimization:
    Production stoppages and closed borders have caused disrupted supply chains, some of which have to be completely rebuilt. Data Mining contributes to the optimization of processes in the background and thus ensures operational efficiency, agility and flexibility.
  • Monitoring in warehouse and logistics:
    The need for warehouse logistics has increased significantly because during the crisis other products were prioritized and different protocols were introduced. In addition, personnel is scarce.
  • Energy Management:
    Data-supported energy management can reduce energy costs, especially by controlling peak loads.
  • Software usage analyses:
    To monitor the costs of software licenses, their use in the company can be tracked to identify areas where savings can be made.
  • Disaster recovery:
    With Big Data, disaster recovery processes can be gained. Real-time insight from the recovery processes to help improve service delivery to citizens affected by natural disasters.
  • Data for Good:
    Since the outbreak of COVID-19, many tech companies have been making their know-how available ree-of-charge to create synergies and jointly tackle the crisis.
  • Home office support:
    The sudden need for company-wide home office solutions has led to the digital transformation in Germany making unexpectedly rapid leaps. Many companies are launching solutions to support remote employees, focusing on reliable real-time transparency and the necessary security.

The future is data-driven
The effects of the pandemic are expected to be long-lasting. Entire industrial sectors that have shut down or converted their production and a purchasing power that has been reduced by short-time work and unemployment cannot be brought back on track overnight, even with the greatest efforts. But with a combination of traditional response tools and the new arsenal of digital tools, the manufacturing industry can find a long-term way out of the crisis. Data will definitely be a critical success factor.

Inspirations/ sources:
– Ewald Munz: Head of IoT & Manufacturing EMEA, Splunk

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