In The Mind of Filiberto Amati |Pricing & Revenue Growth Leader

1. What do you see as the most important development currently shaping Pricing, Revenue Growth Management or Commercial Excellence in your industry?

The price-led growth era in FMCG is over, and most pricing teams are still running its playbook. Between 2022 and 2024, the large food and beverage companies grew revenue mostly through price. Volume was flat or negative. Boards accepted it because inflation gave everyone cover.

That cover is gone. What remains is a market I call Below the K. Demand has split in two. One group of consumers still trades up and pays for brands. A much larger group has moved down, to discounters, to private label, to smaller packs and fewer trips. I do not expect this split to close when inflation cools. It is structural, not cyclical.

The second force sits on the other side of the table. Retailers learned during the inflation years that they can say no. When Carrefour pulled PepsiCo products from its shelves in four countries in early 2024, it sent a message to every supplier in Europe. Discounters such as Lidl, Aldi and Biedronka now set the price reference for whole categories. Their own label is good enough for the shopper in the lower arm of the K.

Put the two together and the priorities change. The question is no longer how much price the market will take. It is which shopper you are pricing for, in which channel, with which pack. RGM teams built to model the next list price increase now have to design two price ladders. Then they have to defend them in front of a buyer with a credible own label alternative. That is a different skill set. In most organisations it sits between pricing, category management and key account sales, and nobody clearly owns it.

2. Where do organisations still leave the most commercial value on the table, and what do more mature organisations do differently?

Trade spend is still the largest unmanaged line on most FMCG P&Ls. It commonly runs at 15 to 25% of gross sales, second only to cost of goods. Yet few companies can tell you what each euro bought.

The pattern repeats from market to market. Promotions are renewed because they ran last year. Deep discounts drive volume that is mostly pulled forward, or switched from the brand's own full-price sales. Trade terms grow in every negotiation round and are rarely linked to anything the retailer must deliver in return.

Mature organisations work differently. They evaluate every promotion after it runs, on incremental margin rather than volume uplift. They tie each element of the trade terms to a counter-performance: distribution, shelf position, display, data. No performance, no payment. And they let the evaluation kill promotions, including the popular ones.

The second leak is the SKU tail. When I review a portfolio, I compare each SKU's share of sales with its share of complexity. That means changeovers, packaging variants, listing fees, forecast error and sales time. In one portfolio, 15% of sales carried 43% of the complexity. That tail also weakens pricing. Every extra SKU is one more price point to defend and one more promotion to fund. It also gives the buyer one more reason to ask for money.

Cutting the tail is rarely popular, because every SKU has an internal sponsor. Mature organisations set a clear rule for what earns a place on the shelf. They apply it every year, not only when a new CEO arrives.

3. How is AI changing your field in practice?

AI is already useful in the parts of pricing and RGM that are heavy on data and light on judgement. Elasticity models, promotion post-evaluation, baseline forecasting, competitor price tracking and anomaly checks on trade spend all belong here. Work that took an analyst two weeks in Excel can now take an afternoon. Mid-sized companies that could never afford a full RGM team can now run analysis that used to belong to Nestlé or Unilever.

The biggest impact, in my view, will be the speed of the feedback loop. A promotion can be evaluated while the next one is still being planned, not six months later in a year-end review. That alone would stop a lot of value from leaking.

Human expertise stays essential in three places. The first is choosing the question. A model optimises whatever objective you give it. Ask it to maximise volume uplift and you will get a very efficient way to lose margin.

The second is the negotiation. A buyer at a discounter in Poland or a retailer in Germany does not respond to a model output. They respond to a supplier who knows what they will trade and what they will not.

The third is the trade-off between this year's numbers and the health of the brand. No dataset tells you the moment a price point starts to damage what the brand stands for. Someone with category experience has to make that call.

So I would automate the analysis aggressively. The decisions should stay with the people who have to live with them.

4. Why do some Pricing or Commercial Excellence initiatives succeed while others fail?

Most pricing initiatives do not fail on analysis. They fail between the slide and the shelf. I describe this with the Execution Gravity Model. It names nine forces that pull a strategy back toward the old way of working once it leaves the strategy room. Incentives, decision rights, legacy systems and the habits of the sales force are among them. None of them appears in the business case.

A typical example. Head office builds a new price architecture with a clear entry, core and premium tier. The logic is sound. Then the key account manager meets the buyer, and the buyer asks for a deeper promotion on the core pack. The key account manager's bonus is paid on volume. The architecture is gone within one negotiation cycle. Nobody decided to abandon it. Gravity did.

The initiatives that succeed share a few features. Finance and sales agree the targets together, so the account team is paid on net revenue or margin, not on cases. The pricing team owns clear guardrails, and a named person can say no to a deal outside them. The rollout starts small, in one account or one category. The results are shown to the sales team before the next wave starts. And the general manager treats it as a commercial priority, not a project run by analysts.

Adoption follows incentives and proof. Training decks and dashboards help, but they come last.

5. What widely accepted belief within Pricing, Revenue Growth Management or Commercial Excellence would you challenge?

The belief I would challenge is that AI is the solution to all problems. AI can accelerate a process, either in a positive or negative way. AI is a catalyst. If you are moving with the right process in the right direction, it scales the right process. If you have the wrong process and the wrong approach, then it also scales that.

In pricing this matters more than in most functions, because the processes are often fragile to begin with. Take a company that runs promotions out of habit and pays trade terms without counter-performance. Give it an AI tool and it will plan the same promotions faster, with more confidence and better charts. The leak does not close. It grows, because now nobody questions the output.

I see many organisations buying tools before they have fixed the basics. A clean price list. A clear owner for each pricing decision. KPIs agreed between sales and finance. A promotion calendar that someone is allowed to cut. Without these, the tool becomes an expensive way to confirm decisions that were already wrong.

In three to five years, the industry will look back at this period the way it now looks at the early ERP rollouts. The winners were not the companies that bought first. They were the ones that fixed the process first and then let the technology scale it. In RGM, the advantage will go to teams that know what good looks like before they ask a model to do more of it.

Is there one final observation, lesson or practical recommendation you would like readers to remember?

Volume is the number that tells the truth. Price can hide a weak brand for two or three years, and inflation let it hide for longer than usual. If your pricing plan does not say where next year's volume comes from, and from which shopper, it is not finished.