Whether it’s with baby steps or one big bang, businesses are digitalising their supply chains.

The accelerated adoption we saw during the pandemic has never eased up. The Cloud, data analytics, automation and AI – and more recently Generative AI (GenAI) – are among technologies creating new value opportunities across all industries, and the whole supply chain.

But COVID hasn’t been the only factor. Global upheaval, M&A activity and the push for greater efficiency at a lower cost are all driving change. Alongside these, there’s been a collective digital response to climate change. Not only is tech more sustainable, it can help with the raft of emerging reporting regulations that demand added transparency. 

Whether it’s for futureproofing or competitive advantage, digitalisation brings all kinds of possibilities. It opens up new channels, markets and global horizons. It makes launching new products and services simpler. It has changed how consumers consume, and sellers sell. 

As supply chains face challenges like delays, shortages and soaring prices, it enables the kind of control that’s essential for businesses to stay agile and responsive when market dynamics are constantly fluctuating.

Building dynamic, digital networks
 

Once, supply chains were a linear sequence of events. Now they’re complex, dynamic, interconnected networks.

But what do we mean by digitalisation in supply chains?

There’s a vast spectrum, but at the lower end we’re talking about internal data and operating processes, like e-invoicing. This then moves through varying degrees of e-commerce, with entry into new markets or the creation of new digital products and services. At the top end, there are full SAAS and Cloud transformations, accompanied by reimagined business models.

And we’re seeing clear trends:

1. Complementary digital retail offerings including new apps, platforms and online marketplaces that work alongside bricks-and-mortar stores.

2. Research and development, and supply chain logistics, enabled by GenAI.

3. Digital networks and Smart factories that can autonomously run entire production processes.

4. Hyper-personalised marketing cleverly tailored to consumers’ preferences and needs.

5. Monetising data and insights, allowing companies to realise new revenue streams from the information they generate. 

Take one client in the automotive industry. As part of a move away from dealerships, it’s turned its website from a marketing tool into an e-commerce platform. Now customers can choose and buy their next car online.

 A software firm has launched a Cloud-based data-sharing product. It gives users across the world, who are outside of the company’s network, access to its data in real time.  

Meanwhile, combining data and digital twin technology – a virtual replica of a manufacturing site or process – can help life sciences companies model a range of scenarios to get the right volume of vaccines to the right people in the right places.

The rapid rise of GenAI has led an increasing number of companies to explore its potential. Business cases usually fall into five categories – accelerate, personalise, automate, create, simulate – and it appears the opportunities presented by ‘trustworthy’ GenAI are boundless.

The life sciences and healthcare industry, which is facing population challenges and complex regulations among other hurdles, has been developing and testing the tech. Indications are that it could transform both the sector and patient care.

The main issues to consider
 

Whenever there’s change, businesses need to think about the impact from a tax and legal perspective, especially in a Pillar 2 world. What are the risks and opportunities and how do businesses stay compliant?If a new digital supply chain creates extra profit, what does that mean from a tax perspective? Which jurisdiction should it be recognised in? Is R&D relief available? Are there new transactional flows and are there indirect tax and customs consequences?  

Getting to grips with GenAI
 

Huge interest and investment in GenAI has led to a host of legal concerns. When it comes to the data on which the tech is trained, there are questions around quality, accuracy, bias and ownership. And there are other challenges. 

First, confidentiality. To what extent can third-party information be used within GenAI models as prompts or for fine tuning? Organisations must make sure they don’t breach Non-Disclosure Agreements or other contractual confidentiality clauses. 

Then there’s privacy. As well as the usual legal considerations around personal data processing, additional obligations can apply to the use of personal data in AI systems. There are also questions about IP when it comes to materials produced by GenAI. If organisations want to own IP rights, country-specific procedures may need to be put in place.

All of this has propelled GenAI up the list of things businesses need to think about.

Tax and Legal leaders must get involved
 

To help businesses drive better supply chain decisions, and recognise the potential impact of digital innovation and transformation, it’s essential for the Tax and Legal functions to be around the table. They need to be involved in the design, planning and deployment of tech solutions. 

David Langford¹, a director in Deloitte’s Tax & Legal Supply Chain team observes that “the key is to raise awareness, so companies are thinking about this. Tax and Legal leaders need to be having good conversations within the business, including with the C-suite. They need to manage risk and understand opportunities ”. 

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References

¹David Langford, director, leads on digitalisation and GenAI from a tax supply chain perspective at Deloitte. He is a senior member of our Tax & Legal Supply Chain team led by partners Gareth Pritchard and Clive Tietjen which helps clients across all industries to navigate the pain points and opportunities created by today’s changing landscape.