Reckitt's Digital Science: 70% Time Savings Became 25% Bigger Innovation Projects

Reckitt, the FTSE 100 consumer goods group behind Dettol, Finish and Nurofen, announced on May 14, 2026 that its Digital Science program has delivered up to 70% time savings on lower-added-value R&D tasks — and grown the average size of its innovation projects, measured as expected incremental net revenue, by 25% year-on-year. The results, published by the company and documented in a BCG X case study, span more than 20 countries and over 2,000 trained colleagues.

The situation before: scientists buried in routine work

Inside a consumer goods R&D organization, a large share of a scientist's week disappears into routine work: compiling stability reports, formatting regulatory documentation, aggregating test data, preparing claim substantiation files. Reckitt's leadership treated that pattern as a strategic problem rather than an administrative nuisance. Physical prototyping added further drag: each new formulation of a dishwasher tablet or a disinfectant traditionally demanded rounds of lab tests, and each round consumed weeks and budget.

The company began attacking the problem in 2025. CFO Shannon Eisenhardt announced a rollout of generative AI tools across the R&D function, and CEO Kris Licht described a pilot on the Finish dishwashing brand that used AI to analyze years of accumulated research and test data to generate new product concepts. Early applications, reported by Consumer Goods Technology, showed up to 60% reductions in product development time, alongside quality improvements. Those pilots proved the mechanics. The harder question was organizational: turning scattered wins into a systematic capability across every major brand and market, as part of the company's Fuel for Growth strategy running through 2027.

The decision that made it possible

Reckitt's answer was Digital Science: a program built with BCG X, the technology build arm of Boston Consulting Group, combining three layers — predictive science, simulation technology and generative AI. The design choice that separates it from a typical pilot portfolio: workflows were reinvented end-to-end. Simulation and predictive models now stand in for rounds of physical testing, generative AI drafts the routine documentation, and experts spend their time reviewing and deciding. The program began in marketing, where BCG X built custom solutions automating time-consuming content tasks, then expanded into R&D, where AI accelerates report creation and automates repetitive steps so scientists can focus on discovery. BCG contributed change management alongside the technical build — a signal that Reckitt treated adoption, rather than software delivery, as the core deliverable.

Two structural moves stand out. First, training at scale: more than 2,000 colleagues across R&D and marketing have been trained on the solutions, in more than 20 countries. Second, executive ownership: the results were announced by Angela Naef, Chief R&D Officer, together with Bastien Parizot, whose title — SVP Global Business Services and AI Enterprise — shows that Reckitt anchored AI in a dedicated enterprise function rather than a side lab.

The result — with full context

On May 14, 2026, Reckitt published the outcomes. Time spent on lower-added-value R&D tasks fell by up to 70%. Digital Science capabilities now run across all Powerbrands — the portfolio that includes Dettol, Finish, Durex and Nurofen — in more than 20 countries, and the company plans to extend them into additional functions through 2026.

The metric SAGA finds most interesting sits above the efficiency line: the average size of an innovation project, measured as expected incremental net revenue, grew 25% year-on-year. Freed capacity flowed into more ambitious bets. Time savings were the enabler; growth in the innovation pipeline was the outcome the board actually wanted.

Full context requires three honest observations. First, the 70% figure is a ceiling — the company's phrasing is «up to», so typical tasks likely saw smaller gains. Second, the +25% measures expected incremental net revenue: a forward-looking pipeline forecast, with realized sales set to deliver the final verdict over the coming years. Third, the announcement comes from the company and its implementation partner; independent trade press has covered the program's earlier phases, while the headline results rest on Reckitt's internal measurement. Within those boundaries, the direction is consistent across sources and across two years of disclosures, from the 2025 Finish pilot to the 2026 enterprise-wide numbers.

What other organizations can learn

The transferable lesson: treat time savings as fuel, and define the destination in growth terms. Reckitt's own framing makes the hierarchy explicit — automation freed 70% of the time absorbed by routine tasks, and the strategic result is a pipeline of bigger projects worth 25% more each. Four conditions made replication possible. Redesign whole workflows end-to-end, with simulation replacing physical steps, instead of sprinkling copilots onto old processes. Invest in adoption at scale: 2,000+ trained people is a real budget line, and Reckitt paid it. Give AI an enterprise home with senior ownership, visible in a dedicated SVP role. Measure outcomes in the currency the board cares about — revenue potential per project — instead of hours saved. Organizations that stop at the efficiency metric capture cost; Reckitt's case shows the larger prize appears when freed capacity is deliberately reinvested in bigger innovation.