Drivers of Value Creation.

Exposure to AI has become ubiquitous, but it is far less common as a driver of investor value. In 2022 over 1.6bn people engaged with AI on a daily basis but, even though use in business processes is growing and there are now several AI unicorns, in 2019 it was estimated that 40% of European ‘AI start-ups’ didn’t actually use AI/ML in a way that was material to the investment.

Cybersecurity is a specialist art of daily maintenance and investigation, but it is also common sense – not educating staff on how to spot phishing emails and failing to set role-based access controls accounts for the majority of cybersecurity breaches that result in punitive fines and lasting reputational damage.

A single proprietary hardware device is actually a collection of third-party components, mostly off-the-shelf and almost all sourced globally. What makes it proprietary is the customised assembly and control software, and possibly bespoke design of some components. It is the components, known as the ‘BOM’ (Bill Of Materials), and not the sales effort that typically dictates the investment feasibility.

Generative Pre-trained Transformers (GPTs), such as OpenAI’s ChatGPT, are a revolution that has arrived. When paired with bespoke interfaces, these large-scale AI language models can deliver ultra-high value at relatively low cost in almost any operation – from writing effective marketing strategies to designing products and providing high-quality service delivery at scale. In short, adoption
of GPT technology offers significant investor value.

Customer demand over the past 10 years has shifted away from Capex hardware purchases towards Opex-based solutions, delivered as a service which includes tools, applications and management systems in addition to the hardware. In some markets the hardware device itself is now expected to be a virtualized software solution.

Product Management, Engineering and the CTO office all drive long-term shareholder value through the optimal use of technology. But the roles exist for very different reasons: Product Management designs, Engineering develops and the CTO office optimises.

SaaS products are all about the end users, which is not always the customer, and are generally assessed by Customer Lifetime Value (a leading indicator). Enterprise technologies, such as process management systems, are driven by the technology itself and usually assessed on Return on Assets (a lagging indicator).

Building proprietary technology is capital-intensive and requires time. Buying proven technology is often safer, quicker and an Opex consideration but seldom generates asset value at exit. The middle ground is partnering with third parties to develop your IP. But what generates the maximum value across the entire investment thesis?

Blockchain is now an established technology solution in a wide range of industries. Its ability to verify and trace multi-step transactions is used to guarantee the transfer of assets, such as IP and legal documents, and the delivery of services, from finance to healthcare. Compared to using a centralised authority, it is a cheaper and more reliable single source of truth.

Data Science predicts behaviour, Business Intelligence provides data-driven insights for operational improvement, and Data Management creates and manages the infrastructure to do both.

Under GDPR and other data regulations, the UK and EU routinely fine companies not just for data breaches but also for unnecessary data collection and data processing, even when no sensitive data is actually leaked.

Hardware innovation is a long-term process, typically taking up to 4 years from concept to market launch, with a 2 year refresh cycle of in-market products. Unlike software innovation, which is fast enough for rapid feedback and iterative corrections, hardware requires an innovation strategy that is right from day one.

Product Management is a commercial discipline, not technical, and its sole purpose is to maximise investor value. Its focus should be net EBITDA across the investment period plus the perceived monetary value of service delivery assets at the point of exit.

Many proprietary technology platforms are sufficient to deliver the revenue milestones and market penetration planned for mid-cap investments. But not all have the architecture to support a step change in scale required by the next acquirer. In these cases, extensive re-engineering is need to maximise ROI, which requires a clear technology strategy as part of the initial investment thesis.

Whilst proprietary software and hardware can create shareholder value, other organisational tenets are essential to enable and deliver that value – a successful technology investment requires a fully functioning ecosystem that includes people, processes, data and, increasingly, third-party technology.

The most senior person typically sets the strategic direction of technology development, and the strategy they choose is likely to be biased towards their area of responsibility instead of what is best for investors.