How AI Will Transform Product Development, Speed to Market
The race to market is fiercer than ever. Yet many companies are hindered by outdated systems and deep-seated data silos that prevent them from leveraging the transformative power of AI.
In this interview, Reid Swanson, VP of sales, new markets at Centric Software, addresses the core data quality and integration challenges that plague the product development lifecycle. He explains how this "shadow landscape" of legacy tools not only slows down time-to-market and lowers profitability, but also actively sabotages any attempt at a successful AI strategy, emphasizing the critical need for a clean, structured data foundation.
CGT: What are the most significant data quality and integration challenges that typically slow down the product development process and prevent companies from leveraging AI?
Reid Swanson: It might be hard to believe, but most companies we speak with still have silos of information throughout the extended product development process, resulting in a lack of transparency, inefficiency and data-quality issues.
Even companies with long-standing product development platforms often face a “shadow landscape” of tools and workarounds that emerge over time. When legacy systems cannot keep pace with evolving business needs, users are forced to operate outside the system just to move products to market.
This technology landscape not only results in a longer time to market and overall lower profitability, but it also prevents companies from being able to execute a cohesive and successful AI strategy. AI is dependent upon leveraging clean, structured and reliable data, which in this case (and in many cases) is not available.
CGT: How can AI and machine learning be leveraged as an enabler to expedite critical functions across the product launch roadmap, such as accelerating product development cycles, streamlining the coordination of cross-functional teams and improving go-to-market speed?
Swanson: For those companies that have established a strong data foundation, AI is already having an incredible impact on the ability to cut time to market. We see companies able to leverage AI-powered market intelligence, comparing their current assortment to their competitors, gaining invaluable insights into pricing, discounting and overall assortment strategy. Not only does this allow them to make data-driven decisions, but it takes a fraction of the time that they used to spend gathering and analyzing this data.
We also see companies leveraging AI to supercharge their design teams, to quickly generate new styles, variations and mark-ups in seconds compared to weeks, which can be leveraged as photo-realistic images for both marketing and early prototype reviews across merchandising, sales and development teams.
From there, intelligent systems automatically generate a bill of materials, guiding teams through each stage of the process. Every AI-driven decision is clearly explained, empowering users to fine-tune and optimize development according to key goals such as cost efficiency or sustainability.
CGT: What specific KPIs and visualization methods are most effective for different cross-functional teams (e.g., design, sourcing, merchandising) to ensure a unified, real-time understanding of progress and potential bottlenecks in a launch?
Swanson: Trying to ensure a unified, real-time understanding of the end-to-end process throughout an enterprise can be achieved with a true end-to-end platform, which brings together all your cross-functional teams that are involved from the initial concept to the consumer. Being able to know in real-time what the initial plan was versus what was developed, adopted, prototyped, approved, sourced and sold will increasingly become a competitive advantage in the marketplace.
Leveraging real-time dashboards, executive cockpits and visual assortments are some of the ways that we see the market leaders harnessing business-enabling technologies to empower people to make data-driven decisions to accelerate growth and successfully navigate the challenges of bringing products to market.
CGT: As generative AI becomes more integrated into the design and product creation process, what are the projected impacts on new product launch cycles in the next three to five years, particularly in terms of efficiency gains and speed to market?
Swanson: AI is fundamentally changing the trajectory of technological advancement. Current analyses indicate that AI capabilities are doubling every three to five months, rendering traditional multi-year forecasts increasingly obsolete. This rapid evolution is poised to significantly compress product development and launch cycles over the next 18-24 months. With companies leveraging AI across all departments, including marketing, merchandising, planning, product development, R&D, engineering, sourcing and supply chain, we will see innovative new products created in a fraction of the time it takes today.
It will truly be survival of the fittest. Companies that can leverage new, AI-driven technologies will not only be faster to market, but they will have the right product, at the right price, at the right place, with the right promotion.
