Faculty launches “Frontier” to drive better organisational decision making

New decision intelligence software to help solve supply chain crisis.

  • 1 month ago Posted in

Businesses should benefit from better decision-making after AI firm Faculty launched new technology showing executives what will happen in their organisation and why.



“Frontier” is decision intelligence software that describes what is happening in an organisation, predicts what will happen, and prescribes what they should do next.



This means a manufacturing business will know not only how much stock they need to service their customers, but also avoid having too much cash tied up in inventory, or too many old products when there is a new one ready to ship.


Commenting on Frontier’s launch (18 May), Faculty CEO Marc Warner said:



“The ways decisions are made today are out of date, prone to error, and not fit for purpose.



“Decision intelligence is a new category of technology, helping organisations see the best course of action and drive high performance.



“The world is increasingly uncertain and complex, which is why now is the perfect time to launch this product and help organisations make better decisions.”



The product comes as supply chains across the world struggle to manage customer demand due to uncertainty caused by the pandemic, war in Ukraine, the energy crisis and raw material shortages. This is exacerbated by outdated forecasting methods.



According to Gartner®, 65% of decisions made are more complex (involving more stakeholders or choices) than they were two years ago. Furthermore, according to the Gartner 2021 Reengineering the Decision survey, 47% of respondents expect their decisions to become more complex in the next 18 months.



Frontier brings together both human and machine intelligence, as well as internal and external data, and existing software and systems to provide a complete view of an organisation from top to bottom.



Faculty Frontier is the culmination of years of research and development in the Faculty Research Lab, and hundreds of custom builds for customers.



The company has worked with one of the world’s largest food manufacturers and a global medical device company, among others, to forecast supply chain demands and mitigate disruption.



Frontier is already being used in the NHS to forecast and manage demand for both elective care and in A&E, and Faculty believes now is the right time to launch the product to help firms deal with the supply chain crisis and global volatility.



Frontier integrates into existing systems and processes, and the results are clear and easy for users at all levels to interpret. Frontier is cloud-agnostic, enabled via Faculty’s partnerships with AWS, Microsoft Azure and Google Cloud, and is able to integrate seamlessly with existing data and software platforms such as Snowflake, Salesforce, Databricks, and more.



It brings a robust scientific approach to decision-making, helping an organisation observe, understand, decide and act. It is this loop that allows for continuous learning and improvement, through both human and machine learning.



It also allows organisations to scenario-plan without disrupting their day to day operations, so they can see the likelihood of the outcome before making a decision. This ability to know what will happen before putting it into action is game-changing for organisations, who are struggling with rising costs and a global talent shortage.



The move comes as Faculty continues to grow after it raised £30 million in growth funding from the Apax Digital Fund last May. The company now has over 200 staff and has recently moved to a new office in East London. Staff numbers are projected to double in the next year, with revenue continuing to grow significantly.



One of the most well-known examples of Faculty’s predictive technology was in the NHS, helping both clinicians and senior managers make decisions about where to allocate resources in the pandemic. This has recently been rolled out and is now available across all A&E departments too.

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