Aerospace Xelerated: Supply Chain Intelligence
tl;dr — 🛫 Applications for Aerospace Xelerated’s fourth cohort are now open, and close 2nd October 2022. Following three successful cohorts led by Boeing and supported by industry partners, the programme will now be run in partnership with Tawazun Economic Council, the defence and security acquisitions authority of the United Arab Emirates (UAE). We’re looking for world-class startups at the seed to series A stage that are building digital services and solutions. Find out more, apply online, or book an Office Hours call.
In Cohort 4, which is focused on digital services and solutions, we are looking to support world-class startups focused on several specific sub-themes. Over the next few blog posts, we will be illustrating what Boeing, Tawazun Economic Council and its industry partners are looking for from startups focusing on these themes. This article covers supply chain intelligence. We’ve also written about flight and passenger journey optimisation, and future topics include next-generation workforce and operational efficiency.
A side note: our definition of aerospace revolves around the design and manufacture of aeroplanes and the peripherals around that process, rather than spacecraft or satellites. Startups with hardware-only solutions are unfortunately out of scope for this programme. We may hold future programmes with a stronger hardware focus so do stay tuned.
Supply chain intelligence
For this sub-theme, we are interested in digital services and solutions that provide predictive and prescriptive analytics to improve supply chain intelligence. In addition, services and solutions focused on building supply chain resilience are also of interest.
As aerospace companies recover from the COVID-19 pandemic, their top priority is to develop and maintain global supply chains that are robust and resilient.
What are the challenges within supply chain intelligence?
Supply chains in the aerospace industry have become increasingly fragile due to greater globalisation, increased complexity as well as price inflation relating to global events.
It is more difficult to fulfil customer orders while controlling costs. Aircraft manufacturers are experiencing longer lead times on their production lines. This is leading to more frequent disruptions that are difficult to handle and predict. The current environment is complex and volatile. Each and every supplier is facing a host of uncertainties that differ depending on the commodity, region, type of equipment, systems and parts it services.
As aerospace companies recover from the COVID-19 pandemic, their top priority is to develop and maintain global supply chains that are robust and resilient. To do this, aerospace groups need greater visibility into the supply and delivery processes and supply chain constraints. Operational management needs real-time and predictive insights on current supply and delivery information to effectively mitigate risks and make faster decisions. Access to both internal and external information is also crucial to ensure that exogenous risks such as stock-outs or unexpected delays are factored into decisions.
What applications are particularly interesting?
Tracy Ji, a Boeing Research & Technology engineer, sheds more light on what Boeing is looking for in startups applying to this subtheme:
“To fully leverage the power of predictive analytics in managing inventory, the solution needs to be capable of analysing structure and unstructured data from multiple sources. We are particularly interested in seeing solutions that could conduct demand planning and inventory optimisation operations for airline customers based on historical data records. Solutions in this space must be able to automatically extract data from different platforms and systems.”
Application #1: Smart analytics for replacement parts
There are many particularly exciting use cases within this sub-theme. Within predictive supply chain analytics, we want to empower operators to access parts easier and faster with smart analytics solutions that can ensure replacement parts are in the right location at the right time to keep planes in service.
Application #2: End-to-end supply chain visibility for predictive analytics
Solutions using machine learning, artificial intelligence (AI) and blockchain can have a dramatic impact on supply chain operations and sustainability. For example, AI can be used to strengthen end-to-end logistics execution by connecting key activities such as planning, booking, settlement and shipment tracking across a vast network of suppliers. It can also improve onboard and offboard predictive analytics to ensure replacement parts are in the right location at the right time to keep planes in service.
Application #3: Support operators across a range of use cases
We are also interested in predictive analytic solutions that can support operators in a diverse range of use cases. Helping operators access parts easier and faster is one example. Providing better visibility into parts needed before any purchases is particularly interesting for commercial airline customers. Finally, utilising technology to quantify CO2 emissions and leverage data as a key criterion for carrier selection can also make an immediate impact.
Have you developed a digital service or solution? To apply for this cohort, head over to our website.
Learn more about Aerospace Xelerated in our FAQ or sign up for our upcoming Ask Us Anything webinar. You can also book an Office Hours callto discuss your queries with the programme team.
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