In a world of fast-changing consumer preferences and increasing choice, companies that want to stay ahead must work continuously to ensure that their goods and services satisfy the customer. In 2023, McKinsey said that big industries, including automotive, telecoms and consumer products, anticipate that a third of sales, worth $30tn over five years, will come from new products.

Advancement is key and the level of fresh funds flowing into research and development is considerable. According to the latest UK statistics, £71bn was spent on R&D in 2022, of which £50bn came from the business sector. In the US, the figure is estimated to be $886bn with business accounting for $690bn.

The return from using advanced technologies is considerable. Looking at the pharma industry, Accenture estimates that scaled use and redesigned workflows will mean that medicines can be brought to market four years faster, earning an extra $2bn for each successful drug. Costs of $2.6bn to $6.7bn could also be scythed by up to 45 per cent.

Tech for Growth Forum

With such large sums at stake, companies will have to think carefully about where and how they spend their cash to reach the consumer.

In a previous report, we studied the role of technology in marketing and how businesses can use technology tools to foster loyalty with personalised messaging and to create holistic cross-channel strategies.

Turning to the front end of the product cycle, this report will examine how technology can help providers update products more efficiently and successfully at each stage of R&D.

We are all technology companies

Mindset is an important factor in innovation. Sean Ammirati, professor of entrepreneurship at Carnegie Mellon University, Pennsylvania, says an entrepreneurial culture inside the R&D function helps companies to innovate — even the large ones. Teams with such a mindset are more likely to come up with transformational rather than incremental product developments.

Ammirati, who has founded several machine-learning start-ups, says many companies do not make the necessary investment in adjacent and transformational innovation. He cited a 2012 paper by Harvard Business Review, which stated: “Companies that allocated 70 per cent of innovation activity to core initiatives, 20 per cent to adjacent ones and 10 per cent to transformational ones outperformed their peers.”

Technology companies should invest more in these two areas, the same research said. Given today’s ubiquity of technology, Ammirati says that every business should think of itself as a technology company when it decides its R&D budget.

Identify your target

It is important to identify what a product is trying to achieve and who is the target — this might not always be obvious. Pella, the Iowa window and door maker, has designed a mechanism that treats the installer rather than the homeowner as its customer. Based on observations and responses, Pella’s new window is easy to install from the inside rather than the outside of a property, reducing the risk to workers when putting windows into tall buildings.

Targets are important for the R&D process, too. This should include deciding if the objectives include cutting the cost of materials, the cost of engineering, time to market, or all three. Having this in mind helps with setting key performance indicators to assess whether a process works.

The role of data

Customer needs should always be the inspiration for product development. The more data that is available, the easier these are to define. Data is critical to any technology strategy. It can, for instance, alert companies to what customers are seeking and what is in demand.

Online marketplaces have extensive access to data about purchasing information and shopping searches which can give them an advantage over the vendors who use their sites.

As we observed in our report on the platform economy, there is value in brands hosting their own websites as a means to retain and interpret customer data. This can give instant insights into modifying or adding to what they offer. For example the bra company Lively introduced strapless bras to its range after it found that many women were searching for these. Tommy John, which makes men’s underwear, found that women liked its products too and it added second-skin “boyshorts”, tees and pants aimed at females.

When collecting or compiling data, it is important for it to be clean. This is especially the case when deploying artificial intelligence systems which are in essence statistical models that feed on data. “This means your team needs to care about data,” Ammirati says. “If your team are being sloppy with how they enter data you’re actually causing downstream problems.”

From concept to reality

People can still come up with product ideas independently of data. Technology can help to accelerate these to market and AI is a powerful tool in that process.

While human oversight will remain as important for R&D as it is for the creation of marketing content, generative AI based on large language models will be invaluable as a “conversation starter”. Presented with an idea or even a vague concept, generative AI can help with brainstorming to help develop a product, undertake market research to find if there are similar items, identify and analyse competitors and give thoughts on how to create a difference. AI can provide many versions of a product and suggest modifications to suit a niche that a human designer might not have considered.

Once the product concept has been honed, AI can help to devise market-testing strategies as well as accelerate product testing and design. It can create and test iterations of a product at a speed far faster than a human. It can suggest materials and sourcing as well as manufacturing processes.