Webinar | The 2026 RGM Playbook: Trends, Traps & Tech to Watch

The 2026 RGM Playbook: Trends, Traps & Tech to Watch

When price stops carrying growth, RGM becomes a precision discipline

When Inflation Stops Covering for Weak RGM Decisions

Across CPG, the last two years masked weak RGM fundamentals. Inflation allowed many organisations to grow despite blunt decisions, wide error margins, and over-reliance on price as the primary lever. That window is closing.

This session confronts what happens next: slower inflation, higher shopper price sensitivity, and tighter corridors for error. It focuses on how RGM teams must change how they decide, not just what tools they use, when growth must come from coordinated levers, sharper modelling, and materially higher decision accuracy.

What You'll Learn

Slower inflation turns pricing into a high-risk decision.
Narrower inflation corridors mean even small price moves now carry outsized volume and profit consequences.
Price-only growth is no longer a viable default.
As inflation fades, revenue growth increasingly depends on coordinated use of mix, PPA, and promotion rather than headline price increases.
Diversified RGM strategies outperform isolated lever moves.
Combining levers creates better outcomes than optimising any single one in isolation, particularly under rising shopper price sensitivity.
Shopper behaviour must be modelled, not inferred.
Static assumptions break down as shoppers actively trade between brands, sizes, and formats under financial pressure.
AI only delivers value when applied to demand prediction.
Technology matters most when it improves how teams anticipate shopper response to offer changes, not when it automates analysis without decision impact.

For senior CPG leaders responsible for growth decisions, this session clarifies what must change when price no longer does the work for you.

Meet The Speaker

Ingo Reinhardt

Co-founder and Managing Director at Buynomics

Before Buynomics, Ingo was a Senior Director with Simon-Kucher & Partners, a global leader in pricing. He holds a Ph.D. in Management from the University of Cologne and Master's degrees in Management and Mathematics. Ingo was a PostDoc at the University of Oxford and published in the Strategic Management Journal.

Session Highlights

Lower inflation increases risk, not comfort [11:33]
When price corridors narrow, even small misjudgements drive disproportionate volume and profit losses. Precision becomes non-negotiable.

Price carried growth only because everything else was muted [13:22]
The post-COVID period masked weak volume fundamentals; that dynamic is already reversing.

RGM value now comes from orchestration, not optimization [21:11]
Isolated price, PPA, or promotion moves fail when cross-effects between products and competitors are ignored.

Shopper behaviour must be modelled, not assumed [16:48]
Aggregate elasticities break down when shoppers trade across brands, sizes, and formats under pressure.

AI matters only where demand uncertainty is highest [20:28]
The real value of AI is in simulating how shoppers respond to offer changes, not in automating reports or slides.

Mixed lever strategies outperform cleaner price moves [28:35]
Combining downsizing with moderate price increases can deliver higher revenue with less unit loss than price alone.

Q&A

How does slowing inflation change the way RGM teams should operate?
It removes the buffer that previously absorbed weak decisions. Teams must operate with higher precision because competitors and shoppers react more sharply to smaller moves.

Is PPA now the primary alternative to price increases?
PPA is one lever, not a substitute. Its effectiveness depends on how it interacts with price, mix, and promotion within the category context.

Why isn’t AI delivering results in many RGM pilots yet?
Most pilots focus on surface-level applications. Value only emerges when AI is applied to predicting demand responses to concrete offer changes.

How should companies handle volatile commodity costs without destroying volume?
Start by quantifying the true cost impact, then test how different pass-through strategies affect demand. The right response depends on category norms and competitive behaviour.

Are elasticities still relevant in advanced RGM modelling?
They are useful outputs, not reliable inputs. Shopper-level simulations capture behaviour that static elasticities cannot. [34:55]

Is customer experience an RGM lever?
It acts as a value driver rather than a direct lever. Its impact must be reflected in demand modelling, not treated as a separate control.