Unlocking Growth: The Transformative Role of Revenue Growth Management (RGM) in the Future of Consumer Products

By Mugdha Khare, Miles Preston and Luke Cross
The authors would like to express their gratitude to CPG leaders interviewed for their insights and Haris Nadeem, Natalia Antropova, Xindi Li, Juan Horos, Rithika Lakhwani and Egbert Ngabirano for their support in this research.

As consumer preferences shift and market dynamics evolve, Revenue Growth Management (RGM) becomes more critical than ever for Consumer Packaged Goods (CPG) organisations. We foresee a world where data-driven decision-making, collaboration, and agility converge to revolutionise revenue growth management in the CPG sector. But with challenges abound, how can CPG companies navigate the complexities and unlock their true growth potential? Join us on a journey to discover the untapped potential of RGM and how it can propel your business forward in an ever-changing landscape.

CPG Outlook for 2024 and beyond

Persistent inflationary pressures have resulted in Consumer Packaged Goods (CPG) relying on pricing actions for continued revenue growth. In the last year, most CPGs have reduced prices to provide impetus to category volumes with mixed results[1]. With prices remaining high and consumers looking to spend less[2] growth in the CPG sector is going to be a closely fought battle on retail store shelves.

In 2024 and beyond, CPG companies will need to find growth across their P&L through a mix of revenue growth levers. Holistic Revenue Growth Management (RGM) will take centre stage as reducing inflation limits the price-led growth, declining volumes and challenging trade negotiations further squeeze margins.

At CAGNY 2024, two thirds of consumer product companies indicated that revenue growth management remained a priority for them. The key focus areas are envisioned in price-pack architecture to drive range optimisation as well as premiumisation through close links with marketing. Taken together, the focus on volume and premiumisation highlights that for long term value CPGs need to rethink how their RGM function is designed and connected with the rest of the enterprise.

Fast moving technological disruptions such as GenerativeAI (GenAI) have created opportunities for CPGs to evolve their RGM capabilities and make them better suited to deliver the commercial outcomes. In this article, we look at how RGM needs to evolve to serve the CPGs of the future.

Revenue Growth Management (RGM) as a function and capability has seen a significant transformation over the years. As the scale and complexity of data available to CPGs for commercial decision making changed, data science and analytics became a prerequisite. RGM was then established as a differentiating capability separate from sales, marketing, and finance functions.

Over time, RGM functions have improved data management, better integrated commercial processes across the enterprise, and enhanced technology in pursuit of revenue and margin growth. However, the journey of RGM as a distinct function has not been without its challenges. RGM teams excel at generating insights but lack direct control, execution accountability, or customer relationships. This has led to a perception among sales and marketing teams that RGM teams do not fully understand the nuances of working with customers. On the other hand, sales and marketing teams typically have a more compartmentalised view of their customer’s contribution to business performance. This has led to a perception among RGM teams that sales and marketing teams are not doing enough, especially not all the things that are needed to deliver commercial results.

These perceptions reveal the underlying tensions in the operating model that surface as tactical challenges for RGM functions. The separation of execution and accountability from insight and strategy has created a gap between what RGM teams should be able to achieve and what they can actually achieve. This gap is driven by several factors: the inability of RGM to drive the execution of all the strategies based on different views of priorities, a lag or absence of feedback between the strategy and its executability, a lack
of agility and ability to respond immediately to opportunities apparent to sales, and missing data, particularly qualitative leading indicators such as knowledge that a particular retailer is going through a range review.

Moreover, some of the reasons for separating RGM into a distinct capability may seem less compelling now as data and analytics skills become table stakes across all functional areas, including sales, marketing, and finance. Additionally, RGM is now a much more process driven capability. It’s no longer a set of unstructured problems requiring dedicated resources to solve. Instead, processes are set, data is well understood, models are built, and tools are available. So, what is the role of RGM in the evolving CPG sector?

3 out of 4

consumer products RGM leaders expect trade terms negotiations to be very or extremely challenging this year

Strategy& Research, RGM 2024

Next generation of RGM capability

Our research highlights the following as key challenges faced by RGM function leads:

Which have a determining influence on the short term imperatives and long term ambitions for RGM capabilities across CPG organisations:

Short term imperatives and long term ambitions for RGM capabilities across CPG organisations. Short term: AI enabled RGM tools and solutions, democratisation of RGM insights, closer collaboration with customers. Long term: X-functional capability set-up, strategic interplay between RGM levers, more prescriptive and predictive RGM outputs

“The goal is to leverage technology to do the heavy lifting, driving continuous improvement in data harmonisation and quality, which in turn through intuitive automated reporting and visualisation enables sales and RGM teams to collaborate with richer, deeper insights, challenging the status quo and optimising investment decision making”

Nick Jones,Britvic

A closer look at these ambitions reveals the three themes that are defining the new approach for revenue growth management. RGM is increasingly seen as a critical enabler of commercial processes. Hence, an evolved RGM operating model to address the above
ambitions, needs to be more precise, more embedded and more agile with strong links across functions such as innovation, marketing, integrated business planning, sales and finance.

The next generation of RGM capabilities will be enabled by leveraging data driven decision making, democratising RGM capability and insights and by enabling more responsive decision making and execution

Enabling the next generation


Precision

Precision in RGM involves leveraging multiple disparate data sets to develop and execute targeted revenue actions while being confident in their outcomes. The key challenges include making optimal decisions across five levers (price, pack, mix, promotions, and trade terms) and accurately measuring the impact of these decisions. Traditional methods relying on historical data often fall short due to market complexity and variability, consumer behaviour, and competitive actions.

To enable precision, companies need to integrate traditional data sources with new ones, such as loyalty card data, social media data, web analytics, and geospatial data. An integrated approach provides granular insights into consumer behaviour enabling precise
segmentation and tailored RGM tactics. Advanced analytics, simulation tools and AI can then quantify the causal effects on key performance indicators and help optimise actions across various scenarios and uncertainties.


In Practice:
A leading Europe-based beverage producer leveraged advanced geospatial analytics to strategically deploy sales resources, resulting in a 15% growth in volume sold through managed independent stores.

“History shows that even the most advanced analytics can fail to deliver results. The key missing link is often the seamless integration of analytics, insights, and processes. Without embedding precision RGM into business processes, even groundbreaking analytics ends up in the junkyard”

Amitesh Sinha,Haleon
80%

of RGM leaders believe they do not have the capability to implement precision RGM, mainly driven by data issues, lack of resources, and skill shortage


Embedded

Embedding and democratising RGM capabilities and insights enables a long term growth focus by proactively shaping market conditions as well as upskilling the frontline commercial teams across sales, marketing and finance. Building an embedded RGM  capability involves a phased transformation within CPG organisations, affecting processes, governance, incentives, and toolsets. 

This transformation will need to:

  • Empower commercial teams with insights from combined data sets used in precision RGM.
  • Provide intuitive tools for data analysis, with GenAI productivity assistants aiding in data synthesis, insight generation, and crafting compelling selling stories.
  • Shift accountability to sales for their annual plans and aligning sales incentives with profitable revenue growth.
  • Ensure effective category-level governance to balance account objectives with overall category growth.

In Practice:
A prominent European drinks manufacturer used predictive analytics to monitor key performance indicators, enabling tailored strategies that reduced churn and targeted high-potential prospects, resulting in a 5% annual growth in outlets.

“The relationships and how RGM is wired into the sales team as well as GM in the organisation are crucial for decision making, which allows them to be more risk-taking and more flexible and fast in making decisions which requires accepting a higher degree of risk with limited information. The RGM function can not work without the support and inputs from all the other functions, and they need to understand RGM and understand how their pieces fit into the puzzle.”

Taylor Hall,Tropicana Beverages


Agile

Agile RGM prioritises flexibility, responsiveness, and iterative processes to enhance revenue growth. It capitalises on data analytics, cross-functional collaboration, and continuous improvement to swiftly adapt to market changes and optimise revenue strategies.

Enhancing agility in decision making will require that CPG organisations enable iterative processes for continuous testing and refinement, data-driven decision-making leveraging real-time analytics, cross-functional collaboration across sales, marketing, finance,
and other departments, and a customer-centric approach that focuses on delivering value and understanding customer needs.


In Practice:
A leading multinational consumer products organization established a Centre of Excellence to drive agile, data-driven retail execution innovations, resulting in increased shopper conversion rates across the omnichannel path to purchase.

Finding your strategic fit

In our research, we found that there is not a single view of RGM capabilities that would work for all CPG organisations. It is not advisable for all CPGs to either get a SWAT team of RGM experts nor to attempt devolution of RGM insights and decision making onto other commercial functions.

When determining your unique blend of precision and agility you should consider the following 3 contextual elements:



Category

  • Highly commoditised categories with typically lower margins requires high precision and agility, focusing more on data and operational efficiency.
  • Differentiated products with higher margins requires focusing more on customer- centric strategies and responsiveness.


Competition

  • Fragmented market requires the highest levels of precision and agility due to intense competition and diverse customer needs.
  • A monopoly market requires lower levels of precision and agility in competitive terms but still needs to maintain a strong focus on customer satisfaction and adaptability.


Channel

  • Converging channels, e-commerce and omnichannel operations demand the highest levels due to their dynamic nature and reliance on real-time data.
  • Brick-and-mortar and B2B channels tend to have more stable environments and longer sales cycles, leading to slightly lower immediacy in adjustments.

Taken together, these will inform the strategic choices needed to achieve the right degree of precision, agility and embeddedness in your RGM capability. These choices come with significant operating model implications for CPG organisations. It is important for CPG organisations to find the right balance of standardisation and accountability when determining the RGM operating model that will support the end-to-end commercial cycle.

Decentralised decision-making typically enhances agility due to the ability to respond quickly and tailor strategies to local conditions. However, it also requires precise, localised insights to ensure these decisions are well-informed.

Centralised decision-making, while benefiting from standardised processes and holistic insights, often sacrifices some degree of agility due to slower, more hierarchical decision-making processes.

Similarly, the assignment of accountability for commercial outcomes to either the Sales or Revenue Growth Management (RGM) function will significantly impact focus areas required in the operating model. Sales accountability emphasises customer insights, immediate responsiveness, and tactical adjustments, whereas RGM accountability will need to focus on data-driven strategy development, adaptive revenue management, and cross-functional coordination.

The evolved RGM operating model represents a transformative approach that can propel companies into a future of sustainable growth and competitive resilience. It is important to realise that this next horizon of RGM capability is not merely a set of new tools or processes, but a comprehensive shift in how companies plan, execute, and measure their success. It requires a deep-seated cultural change, a reimagining of team structures, and a commitment to leveraging data and advanced technology like never before.

CPG organisations embarking on this journey will need to understand the pivotal role of technology and data in driving business performance while ensuring their capabilities work together to realise the coherence premium from a capability system. Addressing the dual fronted problem of data literacy and data explainability will be critical to success by providing executable insights and making the data easy to interpret/understand for ‘non data’ people. This blueprint serves as an essential guide for leaders aiming to optimise their RGM function to foster growth, innovation and collaboration.

“You need to invest in the execution/sales capability first and then invest in the technology/analytical capability to accelerate it. The biggest driver of your success and driving the profitable growth are people with right Business Acumen to be able to marry the practical matters and RGM planning, and execute the plan you built. A key question.. is how can you drive a robust system/enterprise system that drives RGM processes, an equivalent of Workday that embeds into business routines.”

Akshat Pipersenia,Unilever
RGM capability driven strategy and unlocking coherence premium - table stakes capabilities, differentiating capabilities, coherence premium. Unified data foundation and RGM analytics. AI-enabled advanced analytics, iterative processes and feedback loops. Cross functional collaboration and decision agility. Empovered autonomous decisions, accountability and superior execution.

RGM capabilities that fit their business and market context can position organisations to be more resilient, better equipped to handle market uncertainties, and more effective in driving sustainable revenue growth. The journey towards this evolved capability is complex and multifaceted, but the rewards are clear: a competitive edge in a rapidly changing business environment and a robust financial foundation for the future. Get in touch to find how PwC Strategy& can accelerate your journey to a precise, agile and  embedded RGM capability!

Contact us

Mugdha Khare

Mugdha Khare

Director, Strategy& UK

Emma Burton

Emma Burton

Director, Strategy& UK

Follow us