In recent months, we’ve seen existing market volatility further driven by newly implemented tariffs [1]. Rising costs in some segments and shifting consumer behaviors in others, along with advancements in AI, make it very hard to holistically steer a brand’s portfolio with certainty and speed while considering all the different constraints (e.g., maintaining a minimum margin) and KPIs (e.g., increasing market share).
Rather than scrambling to keep up with market changes and responding to these changes reactively, the companies that will thrive in these times are those that can shift from a reactive to a proactive approach. One way to do this is to harness the advancements in AI to anticipate change, protect margins, and drive sustainable growth.
During our recent webinar, industry experts Nuno Alexandre (Global Head of Operations & Planning, Unilever) and Harry Ergan (Vice President of Revenue Growth Management, Ajinomoto Foods) delved into the transformative role of AI in enhancing RGM strategies.
The expert roundtable explored how AI can unlock more profound insights into shopper behavior, enabling data-driven decisions across pricing, promotions, and more. They also touched on commonly faced challenges like data quality and organizational adoption and the future of AI in RGM, which will increase automation, improve predictive capabilities, and foster a more strategic workforce.
Here, we’ll cover the webinar's key points and give you the insights you need to successfully harness AI and thrive in these turbulent times.
As consumers are presented with more choices, more data about their purchasing habits becomes available. In turn, all businesses will face a challenge: more traditional RGM tools will become less effective, while advanced analytics will increase in relevance.
One struggle teams may experience in reaching RGM maturity without using AI is that legacy RGM tools and methods come with many limitations that make it hard to compete in today’s market. Traditional RGM methods tend to focus on each RGM lever in isolation (e.g., price elasticity lists). They cannot integrate different data sources like sell-out, panel, and survey data into one integrated operating model.
Consultancy projects, which are frequently used as the basis for RGM decisions, often take a long time and rarely provide a detailed competitive analysis. When competitors are considered, it’s usually through a broad, merged competitor effect focusing on just the top one to three competitors rather than analyzing competition at the granular SKU level. Additionally, these approaches can become costly.
During our webinar, all panelists agreed that many businesses today are still learning and developing their RGM functions. However, they emphasized the necessity of transitioning from reactive to proactive RGM strategies to maintain competitiveness and drive sustainable growth.
While every business’s approach to RGM differs, one common challenge will be finding tools and strategies to keep up with this evolution. AI can play a substantial role in this evolution, as outlined below.
As with any evolution, integrating AI and moving from reactive to proactive RGM strategies isn’t without challenges. One major challenge is getting people to trust AI-driven insights and shifting from intuition-based decision-making to data-driven approaches. This requires a change in mindset and organizational culture.
However, this challenge can be overcome with the right approach and education on how AI is used within the team, as well as an explanation of the benefits of the usage. For example, the team at Orkla worked within the business to demystify their RGM strategy, which was achieved by positioning RGM as a ‘fact-based’ approach.
A fact-based approach means making data-driven decisions that replace gut feelings with data analysis while considering human impact.
Demonstrating that an RGM team equipped with the right AI tools delivers greater accuracy than gut-based decision-making can help build trust in the shift toward a proactive strategy backed by AI. You can find out more about this in our webinar with VP NRM Strategy Kaj-Dac Tam at Orkla.
Another challenge RGM teams face when integrating AI into their strategy is that of organization silos. RGM teams cannot operate in isolation. Effective AI implementation requires cross-departmental collaboration to ensure insights are actionable and impactful across the business.
“If you want to unlock the full potential of AI, you need to kill all the silos. RGM teams cannot operate as a siloed function. They have to be the central nervous system connecting multiple, different functions.” - Harry Ergan, Ajinomoto Foods
As Harry Ergan mentioned, effective AI implementation requires breaking down existing business silos to ensure that any insights gained from using AI are actionable and impactful across the organization. Collaboration between different functions is essential to make AI initiatives high-impact business drivers rather than just academic exercises.
“Getting people to trust AI to make decisions, it's a shift in the mindset, it’s a shift in ways of working, it's a shift in how human behavior is changing.”
Advice for killing your silo approach can be found in our Webinar Mindset Shift in RGM: From Independent Tools to Holistic Solutions.
While AI adoption has its challenges, the benefits it brings make it a task worth undertaking. There are three key benefits that Nuno Alexandre stated companies stand to gain from adopting AI into RGM strategy and, in turn, moving from a reactive to a proactive approach.
As mentioned, integrating the right AI tools into your RGM strategy provides more than just a technological upgrade. It is a strategic necessity that enables forward-looking decision-making and fosters a data-driven culture. Being able to anticipate upcoming pain points allows you to proactively adjust your strategy, not just to benefit yourself but to reach a triple win that will benefit a manufacturer, retailer, and shopper.
Fostering this move beyond reactive strategies and ensuring fact-based outcomes that drive sustainable growth also opens the door for major benefits, such as collaboration with retail partners based on facts and data. Having data-backed dashboards and proof points to show and explain your team’s strategic decisions gives you a much better basis for negotiation and provides a competitive edge
Not just any tool can be used to make these decisions or reap these benefits though. As quoted in our whitepaper on GenAI in RGM:
“GenAI in RGM must combine different AI layers. Large Language Models (LLM) such as ChatGPT or Copilot cannot answer key RGM challenges end-to-end by themselves. Rather, such systems need to have access to specifically designed and trained models for the key tasks of data integration, sales forecasting, and offer optimization.”
When the right tools are used, the benefits speak for themselves. Buynomics Virtual Shoppers AI technology can help answer the question of what your shoppers will buy. Our AI-based agents, Virtual Shoppers, can integrate all your relevant data, including sales and transaction data, customer surveys, and behavioral pricing insights, to make them useful for decision-makers. When product offers are shown, they will replicate the actual buying decisions of real customers with very high precision.
Virtual Shoppers can be used to assess not only price and promotion changes but also the effects of any offer changes, such as the removal or addition of a product or the change in a product’s features, such as its size. Also, the cross-effects between products are easily identified, and any irrational customer behavior can be considered.
On top of this, tools like the Buynomics’ Decision Guide allow you to choose your KPIs and set up constraints. The Decision Guide will then automate complex analyses and provide actionable insights, which empower RGM teams to focus on strategy instead of analysis. This is a substantial step towards a proactive approach to RGM.
AI integration takes time, and leading brands like General Mills, Unilever, L’Oreal, Orkla, Danone, and others have already begun leveraging its power to stay ahead. Delaying your own adoption means risking falling behind.
Both Nuno Alexandre and Harry Ergan predict that AI will significantly change how organizations operate in the coming years. They both have expectations of enhanced automation, democratized access to complex analytics, precise customization, and hyper-segmentation of strategies.
“The future of work is going to change. There will be much higher emphasis on productivity and much higher strategic decision making.” - Harry Ergan, Ajinomoto Foods
The companies that act now will secure long-term competitive advantage and those that wait will struggle to keep up. Taking action now can help you have a better long-term strategy for revenue growth, and already assessing your current toolset will mean you’re in a better position to face the coming changes.
Buynomics can help you navigate market volatility and strategy shifts as an RGM leader with quick and accurate AI-based insights.
To start, fill out our survey and receive a personalized RGM maturity assessment to find out where you are in your journey from descriptive to prescriptive RGM. In this assessment we will benchmark your performance in key categories and give you actionable next steps to move forward.
For even more tailored advice, you can find out how Buynomics can help you maximize RGM levers and lead your organization's success by requesting a demo with our team today.