Harnessing the full potential of next-gen ERP and GenAI

Co-authored with Rohit Chandrasekhar , PwC UK Director

Businesses need step change, not marginal gains

The last decade has seen pharma companies embed AI, machine learning and robotic process automation (RPA) across their technology landscapes. In some cases, they’ve achieved phenomenal progress – for example, using AI to accelerate new drug development and save money by ensuring that clinical trials are run only for the most promising treatments.

But in many cases, new technologies have led to only marginal gains. The results have fallen far short of the wholesale transformation pharma companies need to respond rapidly to supply chain disruption, geopolitical instability, evolving compliance demands, as well as intensified competitive pressure from patents expiring and new generics makers entering markets.

Identifying roadblocks

What’s holding companies back? The main constraint is ageing Enterprise Resource Planning (ERP) applications that simply can’t provide the agility required in the digital age. In most cases, companies’ ERP solutions, such as SAP, have been heavily customised, so they’re hard to change. This in turn means they entrench rigid data structures, antiquated processes and legacy ways of working.

Tapping into the potential of Generative AI (GenAI)

Unless companies can resolve these issues and modernise their ERP environments, they may find that their AI initiatives also fall short of delivering on their promise. And unless organisations thoroughly evaluate and streamline their processes before integrating AI, they risk automating inefficiencies or even exacerbating existing problems.

This would be a huge missed opportunity, because GenAI offers game-changing potential to drive efficiencies, reduce manual work and enable process simplification at scale. Critically, it empowers pharma companies to gain flexibility without necessarily having to hire more people or keep more work onshore.

We believe that GenAI will enable powerful use cases across pharma companies’ finance, procurement and supply chain functions, driving improvements in key metrics like inventory turnover, working capital and beyond. Potential use cases include:

• Accelerating financial reporting and planning
• Proactively identifying supply chain risks by screening vast quantities of data and highlighting potential concerns
• Supporting make vs buy decisions
• Optimising supply chain routes and transportation
• Supporting scenario modelling, such as deciding how best to respond to trade restrictions or component/material shortages
• Automating customer invoicing
• Delivering productivity hacks by transforming spreadsheet-based processes, analytical reporting and content generation to streamline business operations.

Guiding the journey

Naturally, some of these potential use cases come with significant risks. For instance, in business processes involving customers, it’s vital to ensure that sensitive patient data remains confidential. As companies embark on the journey to SAP S/4HANA, having a business integrator as well as a systems integrator on board can help navigate compliance, privacy, security and ethical issues around responsible AI.

Understanding how to communicate and manage changes related to SAP S/4HANA and GenAI with stakeholders will be essential. That includes working with healthcare providers like the NHS and regulators including the US Food & Drug Administration (FDA), as well as suppliers, joint-venture partners and potential acquisitions.

As PwC’s Thomas Pulling highlighted in his recent blog, migration to SAP S/4HANA is a real opportunity to? consolidate, cleanse and restructure data, ensuring that the data landscape is optimised for AI applications. This process involves not only technological integration but also a strategic overhaul of data governance and management practices. A partner to the business should also support a smooth transition to standardised processes, and a laser focus on ensuring new technology meets business needs.

Beyond the initial implementation, it will be key to shape a GenAI strategy that can help identify new opportunities to add value and drive continuous improvement. This is important, because although some parts of the current ERP might support certain use cases, most will need to wait until the SAP S/4HANA migration is complete and the GenAI technologies are more mature.

Closing thoughts

GenAI offers a massive opportunity for the pharma industry. But unlocking its value at enterprise scale demands building the right foundation first. If companies get the people, process and data aspects of their ERP transformation right, the gain from GenAI will be exponential. And with SAP S/4HANA providing a stable, flexible foundation for future AI use cases, the sky really is the limit.

If you’d like to discuss how to harmonise operations, standardise business processes and bring your people on the SAP S/4HANA transition journey, please get in touch.

You may also enjoy the following blogs:

Putting Data at the Centre of Moving to SAP S/4HANA

The three key areas for S/4HANA migration success in Pharma

This content is for general information purposes only, and should not be used as a substitute for consultation with professional advisors.